Race, Ethnicity, and 

Participation in the Arts 
Race, Ethnicity, and 

Participation in the Arts 

Patterns of Participation by Hispanics, 

Whites, and African-Americans in 

Selected Activities from the 1982 

and 1985 Surveys of Public 

Participation in the Arts 

Paul DiMaggio Francie Ostrower 

Princeton University Harvard University 

Research Division Report # 25 

National Endowment for the Arts 

Seven Locks Press 

Washington, D.C. 
Race, Ethnicity, and Participation in the Arts is Report #25 in a series on 

matters of interest to the arts community commissioned by the Research 

Division of the National Endowment for the Arts. 

Library of Congress Cataloging-in-Publication Data 

DiMaggio, Paul. 

Race, ethnicity, and participation in the arts : patterns of 

participation by Hispanics, Whites, and African-Americans in 

selected activities from the 1982 and 1985 surveys of public 

participation in the arts / Paul DiMaggio, Francie Ostrower. 

p. cm. -- (Research Division report / National Endowment for 

the Arts ; #25) 

ISBN 0-929765-03-6 

1. Arts surveys--United States. 2. Arts audiences--United States. 

3. Ethnic arts--United States. 4. Minorities in art. I. Ostrower, 

Francie. II. Title. III. Series: Research Division report 

(National Endowment for the Arts. Research Division) ; 25. 

NX220.D56 1992 

700’ .973’ 09048~c20 92-31145 

CIP 

Manufactured in the United States of America 

Seven Locks Press
 

Washington, D.C.
 
Contents 

EXECUTIVE SUMMARY	 vii
 

Differences in Participation	 viii
 

Demand for More Participation	 xi
 

Additional Findings from November/December 1982 xiii
 

1:	 RACE, ETHNICITY, AND PARTICIPATION IN THE ARTS 1
 

Defining Our Terms 2
 

2:	 RATES OF PARTICIPATION BY RACE AND ETHNICITY 10
 

The Core Activities 10
 

Differences in Core Participation
 

Among Hispanic Ethnic Groups 16
 

Participation in Other Artistic Activities 16
 

Use of the Media for Exposure to the Arts 21
 

Musical Preferences 27
 

Childhood Experience in the Arts 30
 

Summary 36
 

3:	 NET EFFECTS OF RACE AND ETHNICITY ON
 

PARTICIPATION IN SPPA CORE ACTIVITIES 39
 

Explaining Racial and Ethnic Differences 40
 

Racial/Ethnic Effects Net of Sociodemographic Differences 44
 

Differences in Predictors of Participation by Race/Ethnicity 49
 

4:	 RACIAL/ETHNIC DIFFERENCES IN UNSATED
 

DEMAND FOR PARTICIPATION 56
 

Demand for Greater Participation 56
 

Why People Don’t Attend More 64
 

Conclusions 68
 

5:	 EVIDENCE ON RACIAL AND ETHNIC DIFFERENCES
 

IN PARTICIPATION FROM THE NOVEMBER/DECEMBER
 

1982 SUBSAMPLE 71
 

Measures 72
 

Intergroup Differences in Socialization, Taste, 77
 

and Participation Scales
 

Race, Ethnicity, and Parental Guidance 77
 

Race, Ethnicity, Musical Taste, and Television Arts Viewing 80
 
Contents 

Race, Ethnicity, and Artistic Participation 80
 

Differences in Models Predicting Artistic Socialization,
 

Do Intergroup Differences Vary by Gender, Educational
 

Summary of Findings Thus Far 84
 

Taste, and Participation by Race 86
 

Attainment, or Age? 92
 

Summary 98
 

6:	 CONCLUSIONS 101
 

Do Rates of Participation Vary? 102
 

Does Participation Vary Net of Sociodemographic Factors? 103
 

Does Demand for Artistic Participation Vary? 106
 

Summary Conclusions 109
 

Further Research 110
 

NOTES	 113
 

APPENDIX TABLES	 123
 

About the Authors	 201
 

vi 
EXECUTIVE SUMMARY
 

This report uses data from the 1982 and 1985 Surveys of Public 

Participation in the Arts (SPPA) to describe and explain differences 

in patterns of participation in selected artistic activities by AfricanAmerican, Hispanic, and non-Hispanic white respondents. The surveys 

permit generalization to national populations of whites and AfricanAmericans because the SPPAs were designed to be nationally representative 

of the U.S. population with respect to age, gender, and race. Because the 

sample was not designed to be representative with respect to Hispanic origin 

or other ethnic categories, conclusions about the participation of HispanicAmericans must be more tentative. Asian-Americans were identifiable only 

in the 1985 data, but too few were included in the sample to permit 

generalization about this group. Native Americans were not identified separately, thus making analysis of their participation impossible. 

Data on socioeconomic and demographic background and on participation in ten "core" activities were collected from all respondents in both years. 

The core activities were: attending jazz, classical music, opera, musical 

theater, theater, and ballet performances; visiting art museums or exhibits; 

reading works of imaginative literature; playing a musical instrument in 

public; and dancing or singing or acting on stage. The SPPAs also asked 

subsamples of respondents each year about: (1) participation in "other" 

activities, including visiting historical or science museums or monuments, 

reading poetry, taking art lessons, painting or drawing, engaging in various 

craft activities, and working backstage in the performing arts; (2) consumption of arts programming on television, radio, or sound recording; (3) desire 

for additional participation in the core activities and reasons for not participating more; (4) socialization into the arts as children and specific kinds of 

art lessons taken throughout the respondent’s life; (5) and attitudes towards 

13 kinds of music. 

Descriptive statistics on the core questions were derived from analyses 

of the full samples for both years; descriptive statistics on the other questions 

were derived from analyses of subsamples of whom these questions were 

vii 
Race, Ethnicity, and Participation in the Arts 

asked for both years; and multivariate analyses employing data from two or 

more of the intermittently asked questions are based on data from November 

and December 1982, the only months during which the same respondents 

were asked all of the questions. 

Differences in Participation 

SPPA Core Activities. With the exception of attendance at jazz concerts, for 

which African-American rates of participation exceeded those of whites or 

Hispanics, white respondents participated more in all of the core activities 

than did African-American or Hispanic respondents. ]Most absolute differences between groups with respect to core activities were relatively small, 

with spreads ranging from one-tenth of 1 percent (Hispanic ballet attendance 

in 1982) to, at most, almost 24 percent (Hispanic fiction reading in 1982) 

between minority groups and the non-Hispanic white majority. Most absolute percentage differences were low in large part because, except for reading 

literature, relatively few members of any group participated in core activities. 

If one looks not at gross differences between the percentages of groups 

participating, but rather at the ratio of percentages participating for different 

groups (odds ratios), for some activities the differences in rates of participation for whites, on the one hand, and African-Americans and Hispanics, on 

the other, were sizable. For example, in both years whites were more than 

twice as likely as African-Americans to report attending a classical music 

concert, an opera performance, a musical theater performance, a play, or a 

ballet. Non-Hispanic whites were also more than twice as likely as Americans of Hispanic origin to report attending a play (in bc,th years) and in 1985 

attending a classical music concert or an opera performance.~ 

Rates of public performance on musical instruments or by singing, 

dancing, or acting were lower than those for attendance at arts events for 

members of all groups. Differences between whites and other groups were 

smaller for these art-producing activities than for most core art-consuming 

activities. 

Other activities. Whites were substantially more likely to visit museums or 

exhibits than Hispanics, who were somewhat more likely to do so than 

African-Americans. Differences between African-Americans’ and whites’ 

rates were substantial for visiting history or science museums, historical 

monuments, and arts or craft fairs. White respondents were also substantially 

more likely than others to engage in needlework crafts, .and much more likely 
Summary 

than African-Americans to participate in other crafts activities. By contrast, 

whites were only somewhat more likely than others to have read or listened 

to poetry, taken art lessons, or engaged in printing and drawing, photography, 

or filmmaking. Some of these participation rates for African-Americans and 

Hispanics fluctuated between 1982 and 1985. (For example, Hispanics in 

1982 were more likely to report creative writing than whites, whereas they 

were less likely than African-Americans or whites to indicate participating 

in this activity in 1985.) 

Evidence from the core and other activities indicates that minority group 

members were less likely to attend cultural institutions, relative to whites, 

than to be found among amateur creative artists. Nonetheless, the tendency 

of white Americans to participate at higher rates than others manifested itself 

in responses to most of these questions. The exception of jazz, for which 

African-American attendance rates were well above those of whites or 

Hispanics, indicates that these differences are genre specific, and that intergroup patterns of difference should not be generalized beyond the activities 

about which the SPPA asked. 

Use of the Media for Arts Consumption. More people encountered the arts 

covered in the SPPA through the media than in live settings. The proportionate gap between white and minority attendance was smaller in consumption 

of the arts through the media than in live attendance. In other words, although 

members of all groups were more likely to watch the arts covered by the core 

questions than to attend them, this tendency was more pronounced in the case 

of minority group members than in the case of whites. 

People who watched an arts program on television were more likely than 

others to attend comparable live events. Viewing and attending tended to be 

more closely associated for African-Americans and Hispanics than for 

non-Hispanic whites. Smaller intergroup differences for viewers than for 

nonviewers were evident in both 1982 and 1985 for Hispanic respondents 

with respect to classical music, musical theater, ballet, and art, and for 

African-American respondents with respect to opera and musical theater. 

Musical Preference. Respondents were asked if they enjoyed listening to 

each of 13 musical genres: classical, opera, jazz, show tunes, big band, 

soul/rhythm and blues, rock, country western, easy listening, folk, bluegrass, 

hymns/gospels, and barbershop. Their responses indicated significant differences associated with race or ethnicity within the context of a national 

musical culture dominated by commercially produced genres. AfricanAmericans were particularly likely to report enjoying such forms as jazz, 

ix 
Race, Ethnicity, and Participation in the Arts 

blues, and gospel, which have deep roots in the African-American experience, whereas white and Hispanic respondents were more likely to choose 

country western, easy listening, and rock. But even commercial genres like 

rhythm and blues or country western, which are associated historically with 

specific racial or ethnic groups, appear to have become part of a national 

musical culture. Thus, approximately one in four whites liked jazz and blues, 

and an equal proportion of African-Americans enjoyed country western. 

Preferences were neither sharply segmented by race nor indicative of an 

undifferentiated mass culture in which racial and ethnic differences have 

atrophied. 

Few respondents in any group reported enjoying opera, although substantial minorities liked classical music, jazz, and show tunes. Although 

whites were considerably more likely than African-Americans to report 

enjoying classical music, Hispanics were almost as favorable in 1982 and 

more likely to report enjoying classical music than whites in 1985. 

Parental guidance. White respondents were considerably more likely than 

either African-American or Hispanic respondents to report that their parents 

took them to art museums or listened to classical music when they were 

children. Whites were only somewhat more likely than African-Americans, 

who were more likely than Hispanics, to report that their parents took them 

to plays, dance performances, or classical music concerts, or that parents 

encouraged them to read when they were young. 

Lessons and classes. African-Americans and whites were almost equally 

likely to report having taken many kinds of classes in the arts during the high 

school years, whereas whites were more likely to report taking classes before 

and/or after high school. By contrast, Hispanic-Americans were less likely 

than whites or African-Americans to report taking many kinds of arts classes 

when they were young. Differences were particularly marked with respect 

to music lessons and music appreciation courses.2 

Net Differences Between African-Americans, Hispanics, and Whites. To 

what extent were differences in participation rates in the core activities the 

result of differences in the socioeconomic standing and demographic characteristics of African-Americans, Hispanics, and non-Hispanic whites? Logistic regression analyses were used to predict participation in core activities, 

with attention to the effects of group membership (African-American and 

Hispanic as compared to white), controlling for age, gender, educational 

attainment, occupation, family income, marital status, and SMSA residence? 

X 
Summary 

Even with these controls for sociodemographic factors, whites were significantly more likely than African-Americans to participate in most of the core 

consumption activities, but not in attending jazz concerts (for which African-Americans were significantly more likely to participate). Whites were 

also significantly more likely to participate by performing on a musical 

instrument or as actors, singers, or dancers. 

With respect to the consumption activities, a substantial portion (but, 

with one exception, less than half) of the gross difference (i.e., without 

controls) in participation rates between African-American and white Americans stemmed from sociodemographic, especially socioeconomic, differences between the races. When one looks not at probabilities of participation 

in specific activities but at a measure of the range of performing arts 

attendance (excluding jazz) in which respondents participated, more of the 

gross difference between African-Americans and whites is explained by 

sociodemographic factors. 

Although these interracial differences survived the inclusion of numerous controls, they are small relative to differences associated with other 

determinants of participation. With respect to all of the activities for which 

being African-American was associated with significantly lower participation (relative to whites), the direct effect of race is dwarfed by the impact of 

educational attainment and (except for reading in 1982) exceeded by the 

effect of family income. Similarly, once other sociodemographic factors are 

taken into account, participation rates of African-Americans and whites are 

more similar than are rates for men and women for all such activities except 

visiting art exhibitions. 

Although gross rates of participation in the core activities were similar 

for Hispanic and African-American respondents, larger proportions of the 

differences between Hispanics and whites than between African-Americans 

and whites stemmed from intergroup differences in sociodemographic attributes. Controlling for socioeconomic and demographic factors left significant differences between whites and Hispanics in both years only for reading 

and attendance at musical and dramatic theatrical performances -- the only 

ones of the 10 core activities for which command of the English language is 

often essential. 

Demand for More Participation 

Some respondents in each year were shown a card listing the core arts 

attendance activities and told: 

xi 
Race, Ethnicity, and Participation in the Arts 

"Few people can do everything they would like to do. But if you could 

do any of the things listed on this card as often as you wanted, which ones 

would you do more often than you have during the last 12 months?" 

Those respondents who said they would like to have .attended a given kind 

of performance or exhibition more than they had in the past year were then 

asked to indicate what prevented them from participating more. 

The percentage of respondents in each group who had not participated 

in each activity but who reported that they wanted to do so was added to the 

percentage who reported having participated to estimate a potential participation rate. These potential participation rates were much greater than actual 

participation rates for all groups. Except for white attendance (in 1982 and 

1985) and Hispanic attendance (in 1985) at classical music concerts, and 

white and Hispanic visits to art museums and galleries (in both years), 

potential rates were at least twice the actual rates of attendance and, in many 

cases, were much greater. 

Demand for participation in the seven core consumption activities appeared to be cultivated by attendance. People who already attended were 

much more likely to want to attend more than were people who had not. 

Thus, although there was much apparent unsated demand for these activities, 

most of it came from attenders rather than nonattenders. Because, with the 

exception of jazz performances, whites were more likely to attend than 

African-Americans or Hispanics, unsated demand appeared to be greater 

among whites. Moreover, nonattenders from groups that had the highest 

attendance rates (African-Americans for jazz, whites for everything else) 

were more likely than nonattenders from other groups to want to attend. 

Consequently, if everyone had done what they said they wanted to do, the 

absolute margins in participation rates between whites and everyone else 

would have been wider. (For the exceptional activity, .jazz, the gap between 

African-Americans and others would have widened.) For most activities, 

however, the ratios of white to both African-American and Hispanic rates 

would have declined. 

This could be interpreted as meaning that eliminating barriers to attendance would exacerbate intergroup differences in participation in the SPPA 

core activities (if one focuses on gross differences) or at best moderate only 

some differences, and these only slightly (if one focuses on ratios). This 

conclusion is questionable, however, on at least two grounds. First, the most 

important barriers to participation may be those that influence demand, not 

those that influence the ability of persons to satisfy demand they already 

have. Second, respondents to the SPPA "want-more" questions may have 

xii 
Summary 

responded on the basis of taken-for-granted understandings about the costs 

associated with getting more of what they wanted, thus artificially suppressing demand among groups facing greater barriers. 

For members of all groups, cost and lack of time were the most important 

reasons given for nonparticipation. With respect to most activities, white 

respondents were more likely to give time as a reason than cost, and Hispanic 

respondents were more likely to cite cost than time. In 1982, African-American respondents were somewhat more likely to mention cost than time for 

most activities, whereas in 1985 they were somewhat more likely to cite time 

than cost. Lack of availability was frequently cited by whites and lack of 

accessibility was often mentioned by Hispanics. African-American respondents frequently mentioned these and also cited inadequate transportation as 

an impediment to attendance more than whites and, for most activities, more 

than Hispanics. For most activities, Hispanics were more likely than African-Americans or whites to cite child care problems as reasons for not 

attending. Fear of crime, being handicapped or having health problems, poor 

quality of available activities, inadequate publicity, work-related reasons, or 

inconvenient times of performance were rarely cited as reasons for not 

participating by respondents in any group. 

Additional Findings from November/December 1982 

Because all respondents to whom the SPPA was administered in November and December 1982 were asked all the questions, this subsample is 

useful for investigating a broader range of questions than could be addressed 

using data from the total 1982 or 1985 samples. 

Net differences in parental guidance/lessons. Two scales were created: one 

to count the number of kinds of parental arts socialization each respondent 

reported receiving as a child, and one to count the number of kinds of arts 

lessons or classes taken by age 17. (Because the survey failed to distinguish 

between lessons at home and those at school, these are treated separately 

from parental guidance.) Although African-American and Hispanic respondents received fewer parental-guidance experiences and took fewer arts-related classes or lessons in their youth than whites, these differences were 

entirely a result of the fact that African-American and Hispanic respondents 

had parents who had received fewer years of formal education than did the 

parents of white respondents. Controlling for parental education, AfricanAmerican and Hispanic parents gave their children more kinds of home 

xiii 
Race, Ethnicity, and Participation in the Arts 

guidance experiences than did comparable white parents, and no differences 

remained in the number of kinds of lessons. 

Taste for art music and related genres. Factor analysis isolated a cluster of 

musical genres (classical and chamber music, opera, show tunes, big band, 

and easy listening music) which were summed into an additive scale. White 

respondents scored significantly higher than African-Americans and Hispanics on this scale. Controls for sociodemographic factors reduced the sizable 

African-American/white difference by almost half, bull a modest significant 

difference remained. Sociodemographic controls eliminated all of the differences between Hispanics and whites. 

Viewing arts programs on television. A scale was created as a simple count 

of the number of kinds of arts programs that each respondent reported having 

watched on television. White respondents reported viewing slightly but 

significantly more kinds of televised arts programs than African-Americans 

or Hispanics, but these small differences were entirely the result of sociodemographic differences between whites and the other groups. 

Participation scales. Factor analysis of combined responses to the SPPA’s 

core and other participation questions generated five scales consisting of 

participation items reflecting, respectively: performing-arts attendance (including and excluding jazz); visual and literary consumption activities; 

performing-arts production activities; and visual and literary production 

activities. Regression analysis was used to examine the effects of race and 

ethnicity on these scales, controlling for sociodemographic characteristics, 

parental guidance and lessons, and artistic taste and interest as reflected by 

the art-music and television-viewing scales. The results added further evidence that one cannot generalize about the effects of race or ethnicity on 

cultural participation per se. Hispanic-Americans attend fewer public arts 

consumption activities than whites (both performing and visually oriented), 

but this difference was almost entirely the result of the fact that white 

Americans had more years of education, higher incomes, and higher status 

occupations. Hispanic respondents participated in no fewer art-producing 

activities (either performing or visual) than white respondents and, with both 

sociodemographic factors and guidance/lessons controlled, they participated 

in these art-producing activities significantly more than did comparable 

whites. 

There is no statistically significant difference between African-Amerixiv 
Summary 

can and white respondents with respect to participating onstage or backstage 

in performing-arts events, but African-Americans scored significantly lower 

than whites on the other scales. Sociodemographic differences, however, 

accounted for approximately 80 percent of the significant difference between African-Americans and white Americans in the number of kinds of 

performing-arts events attended with jazz excluded, and all of the difference 

with jazz included. The remaining gaps were not statistically significant. 

Controlling for sociodemographic differences eliminated approximately 

40 percent of the differences between white and African-American respondents in the visual/literary consumption and production scales, although 

small, but statistically significant differences remained. The remaining significant difference in production was attributable to differences between 

African-Americans and whites in childhood socialization in the arts (both at 

home and through lessons and classes); whereas the differences in consumption remained significant even after including the full range of controls. 

Separate predictive models for African-Americans, Hispanics, and whites. 

Data on each group were separated in order to see if the factors predicting 

outcome measures were similar or different for the three groups. For the most 

part, artistic socialization, taste, and participation measures were predicted 

by the same variables for African-Americans and Hispanics as for whites. 

Two exceptions were notable, however. 

First, the effects of age on parental socialization, taste for art music and 

related genres, and arts television watching were greater for whites than for 

African-Americans. With parental education controlled, white parents of 

young respondents offered fewer arts socialization experiences than comparably educated white parents of older respondents, whereas African-American parents of younger respondents offered more than comparable 

African-American parents of older respondents, suggesting that a convergence is occurring. Similarly, controlling for other sociodemographic factors, tastes for art music and viewing arts programs on television increased 

with age for whites, but not for African-Americans and Hispanics. (These 

differences were significant except for white/Hispanic viewing of arts programs on television.) Although these results might mean that white Americans’ tastes change more with age than those of African-Americans or 

Hispanics, they may also indicate a convergence of all groups over time with 

respect to tastes for art music, and convergence between African-Americans 

and white Americans in watching arts programs on television. These findings are consistent with inspection of means by race and age: intergroup 

xv 
Race, Ethnicity, and Participation in the Arts 

differences in socialization and lessons, taste for art music, and arts television watching were smaller among younger respondents than for older 

respondents. 

Second, education had a significantly stronger effe, ct on viewing arts on 

television and on all of the participation scales except for performing-arts 

production activities for whites than for African-Americans, although in 

most cases education was a significantly positive predictor for both groups. 

Moreover, the effects of taking lessons or classes in the arts were less 

pronounced for African-Americans than for other groups, although these 

differences were not statistically significant. Watching the arts on television 

was also less strongly predictive of attendance for AfiScan-Americans, and 

the differences between African-Americans and Hisp~tnics were significant 

with respect to visual-arts consumption and production activities. In other 

words, the analyses provided tentative evidence that formal education, both 

general and arts-specific, was less strongly related to interest and participation in the arts for African-Americans than for other groups. 

Change over time. For most participation activities, gaps between white 

and minority populations were greater for older than for younger respondents. Most of the decline in intergroup differences appeared to be the result 

of changes in the sociodemographic profiles of African-American, Hispanic, 

and white Americans. Sharp increases in the educational attainment of 

African-Americans and Hispanics have narrowed the gap in participation in 

the arts by younger men and women. 

xvi 
Chapter 1 

RACE, ETHNICITY, AND 

PARTICIPATION IN THE ARTS 

Since the creation of the first modem museums and orchestras after the 

Civil War, many Americans have regarded the arts as a public good. 

Even during the Great Depression, a number of institutions, including 

the Camegie Corporation of New York and the Works Progress Administration of the federal government, supported the extension of the visual arts and 

"good" music to communities that had little access to them.~ After World 

War II, especially from the 1960s on, attention turned specifically to making 

the arts available to groups believed to have been culturally isolated. 

With the emergence of government and the large foundations as patrons 

of the arts, attention to minority participation became widespread. The shift 

of concern from the amount of artistic activity to the distribution of opportunity to participate in such activity stemmed from at least three separate 

factors. 

First, due largely to the civil rights movement, the 1960s witnessed 

increased attention to the problems of the least well-off Americans and to the 

equitable distribution of such public goods as educational opportunity. 

Second, the traditionally dominant role of individual patrons in financing the 

arts was complemented by support from large institutions, especially private 

foundations and federal and state government agencies, which were compelled by their charter purposes to take a broad view of the public good. 

Third, with the expansion in the number and activity of arts organizations 

nationally in the 1970s, inequality of access to the arts came to be perceived 

less as a matter of regional disparity (at least among metropolitan areas) than 

of differences among groups within regions. 

It is the purpose of this report to examine the participation of racial and 

ethnic minorities in certain arts activities, primarily as audience members 

and to a lesser degree as amateur producers of art. With the completion of 

the 1982 and 1985 Surveys of Public Participation in the Arts (SPPAs), more 

reliable data became available. Previous studies of attendance of racial and 

ethnic minorities in the arts were either narrow in scope or of dubious 
Race, Ethnicity, and Participation in the Arts 

technical quality. The SPPAs were undertaken by the U.S. Bureau of the 

Census as part of the National Crime Survey at the request of the National 

Endowment for the Arts. Responses from 17,254 persons in 1982 and 13,675 

in 1985 were weighted (by age, gender, and race) to be representative of all 

noninstitutionalized Americans 18 years of age or older. The advantages of 

the SPPA data over data from earlier surveys include its national scope and 

representativeness, careful question design and prete.sting, closely supervised survey administration (usually in person rather than over the telephone), the broad scope of the questions asked, and the large number of 

respondents. Consequently, the SPPAs permit researchers and policy makers 

to pose more interesting questions and to generalize more confidently than 

we have been able to do in the past.2 

The SPPA included eight kinds of questions about cultural participation. 

The first set of questions (core activities) asked respondents to report on 

whether or not they had engaged in each of 10 kinds of activities during the 

previous year and, if so, how often they had done so during the previous 

month.3 The second set of questions (barriers) asked ~respondents which of 

the core activities they would like to participate in more than they do now, 

and what factors prevent them from doing so. The third set of questions 

(socialization) asked respondents about the extent to which their parents 

encouraged certain kinds of participation in the arts and whether (and if so, 

when) they had taken several kinds of classes or lessons in the arts. The 

fourth set (not analyzed in this report) asked respondents about their participation in a range of non-arts activities. The fifth set (.location) asked those 

who responded affirmatively to one or more of the core questions where their 

participation had taken place. The sixth set of questions (musicalpreference) 

asked respondents whether or not they liked each of several genres of music, 

and which they liked best. The seventh (other participation) asked whether 

or not respondents had participated in several cultural activities that were not 

included among the core questions. The last set (media) asked respondents 

whether they had watched or listened to several kinds of arts presentations 

on television, radio, records, or tapes. All respondents in both years were 

asked the core-activities questions, whereas only a portion (approximately 

one third in 1982 and one sixth in 1985) were asked the others.4 

Defining Our Terms 

The task of this report is less straightforward than it may appear. To 

explore the extent to which members of racial and ethnic minority groups 

are underrepresented as participants in the arts, it is necessary to define such 

2 
Race, Ethnicity, and Participation in the Arts 

terms as "racial and ethnic minority," "underrepresentation," and "participation in the arts." 

Different definitions of the terms entail different definitions of the 

problem and, in some cases, different implicit values as to what is desirable. 

Different definitions may also yield different conclusions. In the sections 

that follow, we explain how and why we define our terms as we do, and 

speculate about the possible consequences of our choices. These explanations provide warnings that may help the reader interpret our results. 

Racial or ethnic minorities. The categories "race" and "ethnicity" are socially 

constructed, not scientifically given. The ways and the extent to which 

differences associated with racial or national origin are perceived as important bases for social cohesion, exclusion, and individual identity vary considerably among societies and across historical eras? In the United States, 

race is treated as a social fact, and most respondents to surveys have little 

trouble designating themselves as African-American (or Black), white, Asian 

or Pacific Islander, or American Indian (or Native American)? These distinctions are reflected in relatively low rates of intermarriage among members of different racial groups, so defined. Because the SPPA sample was 

designed to be nationally representative as to race, we began with the racial 

categories available to us in that survey: in 1982, White, African-American, 

and Other; and, in 1985, White, African-American, Asian, and Other? 

With respect to ethnicity, the situation is more complicated. The SPPA 

data provide a single ethnic code for each respondent, but many Americans 

are of mixed national origin. When asked to designate their ethnicity, they 

may have difficulty doing so, and if they are compelled to do so, their 

responses may be only partially accurate. Moreover, the SPPAs were not 

designed to be representative with respect to ethnicity, as they were with 

respect to race. Therefore, we do not know whether patterns of participation 

in the arts found among respondents to the SPPA surveys are typical of (or 

generalizable to) members of their ethnic groups. These considerations, and 

a comparison of SPPA responses with those on the 1980 decennial census, 

which allowed for multiple national origins, led us to conclude that the 

ethnicity data in the SPPA were generally not suitable for our analyses. 

At the same time, however, we concluded that the SPPA data would be 

useful for examining arts participation among Hispanic-Americans, including those respondents whose ethnicity was coded as Mexican, Puerto Rican, 

Cuban, Central or South American, or Other Spanish. The proportions of 

respondents who reported their ethnic origin as Mexican, Puerto Rican, or 

Cuban are comparable to those reported in the United States census, and few 

3 
 

Race, Ethnicity, and Participation in the Arts 

Table 1-1
 

Comparison of National Origin Estimates
 

from 1980 Census and 1982 and 1985 SPPAs
 

Origin SPPA82 SPPA85 Census Single Multiple 

German 8.9 8.0 26.1 36.5 63.5 

Italian 3.7 3.8 6.5 56.5 43.5 

Irish 5.0 4.6 21.3 25.7 74.3 

French 1.6 1.9 6.9 23.8 76.2 

Polish 1.9 1.8 4.5 46.3 53.7 

Russian 1.0 0.8 1.5 49.6 50.4 

English 5.5 5.4 26.3 47.9 52.1 

Scottish 0.9 0.9 5.3 11.7 88.3 

Welsh 0.3 0.2 0.9 18.5 81.5 

Mexican 3.5 4.4 4.1 90.9 9.1 

Puerto Rican 0.7 0.6 0.8 88.0 12.0 

Cuban 0.4 0.2 0.3 83.7 16.3 

Central/South 

American 0.5 0.8 NA NA NA 

Other Spanish 0.6 0.6 NA NA NA 

Afro-American 10.3 10.3 11.1 97.9 2.1 

Other 55.3 55.7 NA NA NA 

Note: Rightmosttwo columns report percentage of respondents to 1980 census in each national origin 

group who reported single and multiple national origins, respectively. Only those national origins coded 

in SPPA are included. Because respondents to the 1980 census could give multiple responses, the 

census columns sum to more than 100 percent. All percentages from SPPA are weighted by race, 

age, and gender, and missing data (1.95 percent for 1982, 2.55 percent for 1985) are omitted from 

base. Source for census data is Bureau of the Census, 1980 Census of Population, Ancestry of the 

Population by State: 1980. Supplementary Report PC80-$1-10, April, 1983 (Table 2). 

census respondents in these categories reported multiple ethnic origins. 

Given these findings, and the fact that Hispanic-Americans represent an 

important set of ethnic minority groups in the United States, we felt warranted in distinguishing between Americans of Hispanic descent and other 

Americans in our analyses.~ 

Almost all Hispanic respondents to the 1982 and 1985 SPPA (99 and 97 

percent, respectively) reported their race as white, and the absolute numbers 

of those who did not were far too small to permit separate analysis.9 

Therefore, we did not divide the Hispanic respondents by race. 

4 
Race, Ethnicity, and Participation in the Arts 

On the basis of these decisions, we concentrate in this report on comparing the responses to the SPPAs of four groups, three racial and one ethnic: 

White Americans (not of Hispanic descent), African-Americans (not of 

Hispanic descent), Asian-Americans (not of Hispanic descent), and Hispanic-Americans. (Data permitting the separation of responses from AsianAmericans were available for 1985 only.) Although the SPPA surveys were 

designed and weighted to be representative of the racial composition of the 

American population, no such representativeness is guaranteed for the Hispanic ethnic category. 

Finally, it should be recognized that although we focus on "HispanicAmericans," this category includes members of ethnic groups that differ 

from one another in many respects.~° Similarly, the African-American and 

white racial categories include members of diverse ethnic backgrounds. 

Indeed, it is possible that variations in behavior within these groups are 

greater than those between them. Our use of broad categories, despite the 

potential differences they may obscure, is based on the coding categories and 

numbers of respondents available to us in these data. We hope that in the 

future, surveys with a larger number of respondents will be conducted so that 

more refined ethnic categories can be employed, allowing researchers to 

discover differences and similarities in arts participation that cannot be 

identified using the categorization scheme currently available. 

Table 1-2
 

Comparison of Estimates for Race and Hispanic Origin Between
 

1982 and 1985 SPPAs and 1980 Census
 

SPPA82 SPPA85 1980 Census 

White 87.1 87.2 85.0 

Black 10.6 10.8 10.5 

American Indian NA 0.2 0.5 

Asian NA 1.6 1.5 

Other 2.3 0.1 2.5 

Hispanic Origin 5.6 6.7 5.5 

Note: Individuals 18 and over only. SPPA figures based on data weighted for race, age, and gender. 

Census figures from Bureau of the Census, 1980 Census of Population, General Population 

Characteristics: U.S. Summary, PC80-1-B1 (tables 43 and 44). Census figures for "Other" calculated 

by subtracting sum of other racial categories from 100 percent. 

5 
Race, Ethnicity, and Participation in the Arts 

Underrepresentation. The term "underrepresentation" is pejorative, indicating a state of affairs that is unjust. Because the term is value-laden and 

because it has several meanings, we shall avoid it in the narrative of this 

report. Nonetheless, because a concern with "underrepresentation" underlies 

the analyses we undertake, it is necessary to discuss the issue. 

In one sense, members of a racial or ethnic group can be described as 

underrepresented relative to some other group if they participate less frequently in some activity. We can assess the degree of underrepresentation, 

thus defined, by comparing the rates of participation by different groups. If 

24 percent of Group A reports attending arts and crafts fairs, for example, 

but just 12 percent of Group B, the members of Group B are underrepresented. We investigate underrepresentation by race and ethnicity in this 

sense in Chapter 2. If one is concerned with equality of result- i.e., if one 

feels that equalizing participation in the arts is itself a legitimate goal of 

public policy -- then such differences among groups are a concern in their 

own fight. 

By contrast, public policy in the United States has often been concerned 

not with equality of result but with equality of opportunity. From the 

perspective of equality of opportunity, it is less important that members of 

different groups all participate to the same degree than that persons are not 

disadvantaged, by virtue of their racial or ethnic origin, in attempting to 

share a public good. American society tolerates all sorts of inequality, so this 

argument goes, opposing as odious only inequality that results directly from 

statuses such as race or gender into which one is born. Thus what are 

important are not differences in rates of participation’by members of different groups, but rather differences in opportunities to participate that are a 

consequence of, rather than simply associated with, membership in a racial 

or ethnic minority group. 

In this view, the appropriate measure of underrepresentation is the 

existence of a negative effect of racial or ethnic group membership on rates 

of artistic participation, net the influence of people’s other characteristics. 

To return to our previous example, imagine that members of Group A attend 

arts and crafts fairs less than members of Group B not because they are 

excluded on the basis of race but because they have less of other characteristics (e.g., education or money) that are associated with participation. If 

we control for these other characteristics, we can estimate the net effect of 

racial or ethnic origin. This we do, using logistic regression analysis, in 

Chapter 3. 

There is another reason one might wish to look at the "net effect" of race 

or ethnicity on artistic participation rather than the simple association of the 
Race, Ethnicity, and Participation in the Arts 

two. Measures of association, like those in the tables presented in Chapter 2, 

tell us what degree of inequality exists, but they do not tell us why it exists. 

Inspecting the factors that account for such variation in participation, as we 

do in Chapter 3, enables us to assess what would have to change to reduce 

the inequality we see. For example, if differences in the artistic participation 

of different racial or ethnic groups were simply a result of differences in the 

length of time members of different groups stay in school, then equalizing 

educational opportunity would suffice to equalize artistic participation. If 

not, then other programs would be required. 

The factors that lead to participation in the arts may not be the same for 

all groups. If one is concerned with increasing racial or ethnic minority 

participation, then it is important to understand the factors that account for 

participation by members of these groups, and how these factors may differ 

from those predicting participation by members of the majority. In Chapter 

3, we present results of separate analyses for white, African-American, and 

Hispanic respondents to the SPPAs, to explore the possibility that participation in the arts stems from different origins in each group. 

The notion of "underrepresentation" implies that participation in the arts 

is a public good that, like education or political influence, almost anyone 

would find attractive. By contrast, most of us think of our artistic participation (or lack thereof) in individualistic, voluntaristic terms. Differences in 

artistic participation, either gross or net, may result from the exclusion of 

some groups from artistic opportunities (either through active discrimination, of the kind commonly exercised against African-Americans in the past, 

or through more subtle, perhaps unintended, social pressures that make 

members of minority groups feel unwelcome or uncomfortable at certain 

artistic events). Or they may simply reflect intergroup differences in taste or 

preferences. The SPPA data do not provide such clear accounts of the extent 

to which racial or ethnic differences in participation represent exclusion or 

differences in taste as they do of the extent to which such differences exist. 

But they do permit us to hazard some guesses, which we shall do in Chapter 

4. Note, however, that many arts advocates may not regard such evidence as 

relevant to public policy. In their view, participation in the arts is a good 

thing, and people who do not want more of it may simply have been deprived 

of opportunities that would have awakened them to its virtues. 

Finally, to the extent that underrepresentation (however defined) is a 

concern, it is important to know what subgroups are most underrepresented 

and whether underrepresentation is increasing or decreasing. In Chapter 5, 

we shall present the results of analyses comparing the extent of racial and 

ethnic differences in artistic participation among men and women and 

7 
Race, Ethnicity, and Participation in the Arts 

among Americans of different ages and educational levels. In that chapter, 

we shall also use a special subsample of the 1982 SPPA that enables us to 

explore the impact of childhood experiences and indices of musical taste and 

artistic interest on several kinds of participation, controlling for socioeconomic factors. 

In summary, "underrepresentation" may mean at least three different 

things: 1) differences in the extent to which members of different groups 

participate; 2) differences in the extent of participation of members of some 

groups compared with members of other groups who are in other respects 

similar to them; or 3) differences in the extent of participation by members 

of different groups attributable to differences in access rather than to 

differences in taste. Each definition entails a different view of art and of the 

nature of a just society, and assessing underrepresentafion according to each 

definition requires a different methodological approach. Rather than choose 

one, we address each definition, investigating the first two rather thoroughly 

and the third as much as limited data permit. 

Artistic participation. No two people define "art" in exactly the same way. 

Some emphasize the most prestigious expressions of "high culture," others 

include such modem forms as jazz or film and "folk arts" or "crafts," and 

still others admit the full range of "the popular arts" distributed by the 

commercial media. People also differ in their estimation of the kinds of 

participation that are most important: some believe that any exposure to art 

is desirable, others value personal encounters more highly than exposure to 

the arts through broadcast or reproduction, and still others maintain that the 

best measure of our cultural well-being is the extent to which people create 

and perform art themselves. 

We call attention to these issues because the extent to which we find 

intergroup differences in participation will depend on where we look, on the 

kinds of art forms and participation about which measures are available in 

our data. Fortunately the 1982 and 1985 SPPAs took a relatively inclusive 

view both of the arts and of participation. The core questions, for example, 

asked respondents about jazz, as well as classical music and opera; and asked 

respondents whether they played a musical instrument (in any kind of 

musical presentation) or acted, sang, or danced onstage, as well as whether 

they watched others do so. Respondents were asked whether they had taken 

classes in photography as well as in painting; and in crafts as well as fine arts 

and art or music appreciation. And one question asked respondents whether 

they enjoyed each of a wide range of musical genres, from country western 

to chamber music. Moreover, people were asked about the arts they watched 

8 
Race, Ethnicity, and Participation in the Arts 

on television or listened to on radio or recordings, as well as those they 

witnessed live. 

Nonetheless, the SPPA questions tend to reflect both its sponsorship by 

the National Endowment for the Arts, and what is probably a loose consensus among educated Americans as to what forms of artistic participation 

matter most. Thus the survey focuses predominantly upon the arts that are 

within the domain of the Arts Endowment. These include the kinds of 

performances or presentations that are sponsored by nonprofit cultural 

organizations or public television stations rather than those that are produced 

by commercial media conglomerates. They also focus on the kinds of 

performances that are more likely to take place on a public stage than in 

one’s living room or on the street. 

Notwithstanding the legitimacy of these emphases, the choice of activities and the way in which questions are worded may have influenced the 

patterns that emerged from the data. For one thing, the SPPA simply did not 

ask specifically about certain activities: e.g., break dancing, graffiti art, clog 

dancing, mariachi music, many kinds of ethnic dance and song, or televised 

soap operas. Consequently, we cannot know if racial and ethnic patterns of 

participation in such activities are different from patterns in the activities 

about which the respondents were asked. It follows that the data cannot yield 

grand generalizations about racial and ethnic differences in "artistic participation," in the broadest definition of that term. To the extent that the SPPA 

focuses upon activities that are favored by white college graduates, it 

probably overestimates the extent of the difference between the artistic 

participation of white Americans and of everyone else. 

On the other hand, certain questions were phrased so broadly that the 

absense of racial and ethnic differences in response would not permit us to 

infer that the practices of white, Hispanic-, Asian-, and African-Americans 

were the same. For example, the fact that similar proportions of two groups 

attend live plays does not mean that they are attending the same kinds of 

dramatic productions. It is important, therefore, to remember that our findings pertain to a circumscribed, although relatively broad, set of artistic 

practices. 
Chapter 2 

RATES OF PARTICIPATION BY 

RACE AND ETHNICITY 

I

n reporting the rates at which members of three racial and one ethnic group 

participate in several artistic activities, we shall compare responses to 

questions about different kinds of artistic activities to see if the pattern of 

intergroup differences can give us hints as to the sources of racial and ethnic 

variation. These comparisons allow us to document differences in participation, but not to explain them. Differences may result 

 ̄ from patterns of racial or ethnic exclusion, 

 ̄ from differences in taste that are associated with race or ethnicity, or 

 ̄ from factors such as educational attainment or occupational status 

that are associated with both race and participation in the arts. 

The Core Activities 

We begin by looking at responses to questions ab,~ut participation in 10 

core activities about which respondents were asked each month in which the 

surveys were administered. Responses to these questions, weighted by age, 

race, and gender, appear in Table 2-1. 

Respondents were asked whether they had participated in each activity 

during the previous year, and how many times they had participated during 

the previous month. Because participation rates during the previous month 

were low for all groups, we focus here on whether or not respondents 

reported engaging in each activity during the year before the survey was 

administered.1 The way in which this question was phrased means that we 

do not know whether members of different groups who answered affirmatively differed in their frequency of participation over the course of the year. 

The respondent who attended a single play during the previous year, for 

example, is treated no differently than one who attended 20. 

10 
Rates of Participation by Race and Ethnicity 

We report the percentage of the members of different groups who 

participate. This is very different from the percentage of visits or attendance 

for which members of each group account. Previous research indicates that 

a relatively few people account for a large proportion of visits to museums 

and attendance at performing-arts events because they go very frequently.2 

If one’s primary interest is in these high attenders, the data reviewed here are 

of limited value. On the other hand, earlier studies and SPPA evidence on 

participation during the previous month suggest that high attenders represent 

only a small minority of the American population. Thus the data are suitable 

for comparing rates of attendance of groups within that population. 

We can make several generalizations about responses to core questions 

for 1982 and 1985. First, the absolute differences between groups with 

respect to core activities are relatively small, with spreads of from one-tenth 

of 1 percent (Hispanic ballet attendance in 1982) to, at most, almost 24 

percent (Hispanic fiction reading in 1982) between minority groups and the 

white majority. For the most part, absolute percentage differences are low 

because relatively few members of any group participate in the core activities (aside from reading literature). For example, the largest percentage of 

any group that attended opera was the 4.58 percent of Asian-Americans in 

1985. The highest rate of visiting art galleries and museums was 26.02 

percent (again for Asian-Americans in 1985). Participation rates for other 

activities were intermediate. 

Taking just those groups for which data are available for both years 

(whites, African-Americans, and Hispanics), we see that participation rates 

were higher for whites in both years for all but attendance at jazz concerts. 

Taking not the absolute differences but rather the odds ratios, we see that for 

some activities these differences were sizable. For example, in both years, 

whites were more than twice as likely as African-Americans to report 

attending a classical music concert, an opera performance, a musical theater 

performance, a play, or a ballet. In 1985, they were more than twice as likely 

to report visiting an art gallery or museum. Non-Hispanic whites were also 

more than twice as likely as Americans of Hispanic origin to report attending 

a play (in both years) and in 1985 attending a classical music concert or an 

opera performance) Hispanic respondents reported rates of attendance comparable to those of whites at jazz concerts, operas, and ballet in 1982, 

although the gap widened slightly in 1985. 

Inspecting ratios of the probability of participation in many core activities for white respondents to the probability of participation for minority 

respondents makes the differences between groups look large. We can turn 

the measure around and look, instead, at the ratio of the probability that 
Race, Ethnicity, and Participation in the Arts 

Table 2-1 

Participation in Core Arts Activities 

by Race/Ethnicity 

Attend jazz 

concert 

Attend classical 

concert 

1982 1985 1982 1985 

White 9.13 

13,890 

9.48 

10,861 

14.42 

13,909 

14.31 

10,875 

AfricanAmerican 15.64 

1,654 

13.08 

1,384 

6.67 

1,656 

6,.39 

1,384 

Hispanic 8.27 

940 

6.55 

788 

7.87 

941 

6.77 

1789 

Asian -­

-­

7.81 

232 

-­

-­

16.50 

232 

Attend 

Ballet 

Visit Art 

Exhibit 

1982 1985 1982 1985 

White 4.64 

13,913 

4.72 

10,878 

23.94 

13,905 

24..14 

10,872 

AfricanAmerican 

1.78 

1,657 

2.14 

1,385 

12.47 

1,656 

10.71 

1,1385 

Hispanic 4.54 

941 

3.21 

790 

16.22 

941 

18.18 

’790 

Asian 6.22 

232 

-­

-­

26.02 

;232 

12
 
 

Rates of Participation by Race and Ethnicity 

Table 2-1 (Continued)
 

Participation in Core Arts Activities
 

by Race/Ethnicity
 

Attend opera 

performance 

Attend 

musical 

Attend 

play 

1982 1985 1982 1985 1982 1985 

White 3.33 

13,901 

2.97 

10,861 

20.67 

13,908 

18.60 

10,873 

13.44 

13,899 

13.10 

10,869 

AfricanAmerican 1.36 

1,654 

1.43 

1,384 

10.10 

1,656 

8.45 

1,384 

5.82 

1,655 

6.09 

1,383 

Hispanic 2.52 

940 

0.78 

788 

10.96 

940 

9.52 

789 

5.47 

941 

6.41 

788 

Asian -­

-­

4.58 

232 

-­

-­

13.89 

231 

-­

-­

8.87 

232 

Perform on Perform: 

musical act/sing/ Read 

instrument dance fiction 

1982 1985 1982 1985 1982 1985 

White 4.01 2.98 4.68 4.27 60.19 59.66 

13,916 10,879 13,916 10,879 13,868 10,852 

African- 3.35 1.72 4.87 3.49 42.41 43.34 

American 1,658 1,385 1,658 1,385 1,651 1,381 

Hispanic	 3.11 2.03 2.85 2.63 36.45 41.46 

941 790 941 790 938 788 

Asian	 -- 3.82 -- 4.00 -- 53.73 

-- 232 -- 232 -- 230 

Note: First line to right of racial ethnic category refers to weighted percentage of group engaging in 

activity at least once during 12 months preceding survey. Second line refers to unweighted number 

of respondents. In 1982, Asian-Americans were included in an "Other" racial category. 

13 
Race, Ethnicity, and Participation in the Arts 

minority respondents do not participate in an activity to the probability that 

whites do not participate. Viewed this way, the same !intergroup differences 

seem much smaller. For example, in 1982 whites were well over twice as 

likely as African-Americans (a big difference) to have attended an opera, but 

Afi’ican-Americans were only 2 percent more likely than whites (a tiny 

difference) to have abstained from opera attendance. Similarly, in 1985, 

white respondents were twice as likely as Hispanic respondents to have 

attended a classical music performance, but Hispanics were only 9 percent 

more likely than whites not to have attended. 

Responses of Asian-Americans (available only in 1985) resemble those 

of white Americans. (So few Asian respondents were included in the survey 

that we cannot be as confident that the percentages reflect actual population 

distributions.) Asian respondents were somewhat more likely than whites to 

attend classical music concerts, operas, and ballet performances, and to visit 

art galleries and museums. They were less likely than whites to attend jazz 

concerts, musical theater, and stage plays, but white rates of attendance were 

in all cases less than 50 percent greater than those of Asians. 

Rates of public performance were lower than those for attendance at arts 

events for members of all groups, and these rates varied less among the 

groups than those for attendance. African-Americans were more likely than 

others to report singing, acting, or dancing onstage in 11982 (but not in 1985), 

and Asian-Americans were more likely to report performing publicly on 

musical instruments than any other g~roup in 1985. His]panics were somewhat 

less likely than others to report performing onstage, but the absolute margin 

of difference is very small. 

We may infer from this that artistic participation is more equal among 

ethnic groups with respect to performing than with respect to watching other 

people perform. We would also note, however, that the wording of the 

performance questions was somewhat broader than that of the attendance 

questions, coveting any kind of public performance: in any musical, dramatic, or dance style. Respondents who answered the music performance 

question affirmatively were then asked if they performed classical music and 

if they performed jazz. One-fourth of the white musical performers and onefifth of the Hispanic reported that they had played classical music, compared 

to one in ten of the African-American musical performers in 1982. (In 1985, 

the comparable figures were 71 percent for Asians, 32; percent for whites, 24 

percent for Hispanics and 19 percent for African-Americans.) In 1982, more 

than one-fourth of the Hispanics and more than one-fifth of the whites who 

reported performing on an instrument in public said that they had played 

jazz, compared to just 16 percent of the African-American instrumentalists. 

14 
Rates of Participation by Race and Ethnicity 

(In 1985, the comparable proportions were 36 percent for Hispanics, 26 

percent for whites, 17 percent for African-Americans, with no Asian reporting a public performance of jazz.) 

Instrumentalists who performed in public but played neither classical 

music nor jazz presumably were playing either folk or ethnic music or some 

form of commercial popular music. Thus we can infer that in 1982, 77 

percent of African-American instrumentalists, compared to 63 percent of 

whites and 70 percent of Hispanics, played exclusively commercial popular 

or folk/ethnic music. (In 1985, the figures were 71 percent for AfricanAmericans, 55 percent for whites, 57 percent for Hispanics, and 29 percent 

for Asians.) Had the question been restricted to classical music and jazz, as 

were many questions in the SPPA, ratios of white to African-American 

participation rates would have been higher, and Hispanic participation rates 

would have exceeded those of African-Americans. These results serve well 

to illustrate how the size and direction of intergroup differences are influenced by the ways in which "the arts" are defined. 

Although the music performance question is unusual in permitting inference about participation in popular commercial art forms, other options do 

vary in the extent to which they focus upon conventionally prestigious "high 

culture" activities. Are racial and ethnic differences greater with respect to 

well-established forms of high culture and smaller for more contemporary 

or commercial forms? The gaps between whites and Asians, on the one hand, 

and Hispanics and African-Americans, on the other, are striking with respect 

to classical music and, to a lesser extent, opera and art exhibits. But the gap 

between whites, on one hand, and African-Americans and Hispanics on the 

other, is also sizable with respect to stage plays and musical theater presentations, often seen as more popular events; and differences between whites 

and Hispanics in ballet are relatively modest. Thus responses to the core 

questions defy generalization on this issue. 

Although African-Americans report the lowest participation levels with 

respect to most of the attendance activities, they report the highest rates of 

attendance at jazz concerts. Jazz is notable because it is the single art form 

included in the core questions that has emerged out of the African-American 

experience; and, although jazz attendance is a minority pursuit among 

African-Americans and jazz has established itself within American music 

more broadly, African-Americans artists are still especially prominent as 

composers and musicians. (The jazz audience is predominantly white, but 

only because there are so many more white Americans than African-Americans?) African-Americans were more than 60 percent more likely than 

whites to report attending a jazz concert in 1982, and more than 35 percent 
Race, Ethnicity, and Participation in the Arts 

more likely to do so in 1985. This anomalous finding is important, for it 

shows that the gap between African-Americans and whites with respect to 

other kinds of attendance does not reflect a generalized indisposition towards 

attendance at the performing arts within the African-American subsample. 

Differences in Core Participation Among Hispanic 

Ethnic Groups 

The Hispanic subgroups vary with respect to demographic attributes 

such as age and formal educational attainment. These subgroups also vary 

substantially in their participation in core activities of the SPPA. The 1982 

SPPA included data from 425 Mexican-Americans, but only 98 Puerto 

Ricans, 47 Cuban-Americans, and 143 Hispanics with other national backgrounds. Evidence from the 1985 survey is even more limited, with 382 

Mexican-American respondents, but just 62 Puerto Ricans, only 22 CubanAmericans, and 131 in the "other Hispanic" category. 

In both 1982 and 1985, respondents in the "other" category participated 

in most activities more than members of the named Hispanic ethnic groups, 

and, especially in 1985, their pattern of participation was similar to that of 

non-Hispanic whites. Puerto Rican and Mexican-American respondents 

tended to report lower levels of participation, although the former were 

relatively more active in 1985 than in 1982. (See Table 2-2.) 

These differences are both suggestive and consistent with what we know 

about differences in age and educational attainment among these segments 

of the heterogeneous Hispanic-American community. But without systematic sampling of larger numbers of Hispanic respondents, we can treat these 

findings only as bases for hypotheses to be explored in future research. 

Participation in Other Artistic Activities 

An additional set of questions was asked of approximately one-third of 

the respondents in 1982 and one-sixth in 1985. Several of these questions 

focused on visual and craft arts, and on activities that involved "making" art 

rather than "consuming" it. This set of questions also asked respondents if 

they had read or listened to poetry, visited historical or science museums or 

visited historical monuments. 

Weighted participation rates by race/ethnicity are reported in Table 2-3. 

16 
 

Rates of Participation by Race and Ethnicity 

Table 2-2
 

Participation in Core Activities by Hispanic-Origin
 

Ethnic Groups, 1982 and 1985
 

Mexican Puerto Rican Cuban Other 

1982 1985 1982 1985 1982 1985 1982 1985 

Jazz 6.40 6.45 2.02 11.04 5.74 4.41 8.78 8.27 

Classical 7.57 5.03 2.89 6.41 8.36 0.00 9.65 11.46 

Opera 1.44 0.24 2.40 2.03 8.86 3.85 5,95 0.91 

Musical 10.91 6.53 5,84 17.53 12.46 6.23 12.62 21.05 

Play 3.62 4,83 3.80 6.57 7.35 3.85 t 1.97 13.29 

Ballet 4.35 2.08 1.79 1.27 7.27 0,00 7.75 7.22 

A~ Ex. 13.44 15.43 16.84 18.35 18.40 12,07 19.82 29.49 

Perform: 

Music 

2.09 2.50 2.05 0.00 8.97 0,00 0.65 2.55 

Perform: 2.23 2.12 3.99 0.00 4.42 0.00 0.82 1.46 

Sing, e~. 

Read 29.22 37.70 34.72 39.63 29.31 42.65 48.93 57.42 

425 382 98 62 47 22 143 131 

Note: N for Mexican-Americans in 1982 is 424 for attending operas and musicals. N for MexicanAmericans in 1985 is 380 for jazz and opera, 381 for plays. N for Other in 1985 is 130 for plays. Ns 

are unweighted, percentages are weighted. 

Whites were substantially more likely to participate in the attendance activities and creative writing than Hispanics, who were somewhat more likely to 

do so than African-Americans. For visiting history or science museums and 

historical monuments, differences in African-American and white rates were 

substantial. In 1985, for example, 26 percent of white respondents, but just 

1 ! percent of African-Americans, attended a science or history museum. 

More than 40 percent of the white Americans, but just 18 percent of the 

African-Americans, visited a historical monument. 

White respondents were more likely than African-Americans or Hispanics to report attending arts or craft fairs in the previous year: 43 percent of 

whites in 1982 and 45 percent in 1985, compared to 27 and 26 percent for 

17 
Race, Ethnicity, and Participation in the Arts 

Table 2-3 

Participation in Other Arts Activities 

by Race/Ethnicity 

Visit nonart musem 

Visit hist. 

monument 

1982 1985 1982 1985 

White 24.06 

3,461 

26.08 

1,860 

40.19 

3,462 

40.09 

1,858 

AfricanAmerican 

13.20 

416 

11.23 

249 

21.68 

417 

17.50 

248 

Hispanic 21.09 

186 

16.26 

144 

26.99 

185 

23.95 

144 

Asian 16.57 

37 

3’1.06 

37 

Workwith 

pottery 

Weave, 

crochet 

1982 1985 1982 1985 

White 13.29 

3,463 

12.68 

1,857 

33.58 

3,463 

3O.67 

1,857 

AfricanAmerican 

6.93 

417 

5.42 

249 

22.97 

417 

15.58 

249 

Hispanic 8.82 

186 

8.95 

144 

22.20 

186 

16.48 

144 

Asian 4.14 

37 

38.74 

37 

18
 
 

 

Rates of Participation by Race and Ethnicity 

Table 2-3 (Continued)
 

Participation in Other Arts Activities
 

by Race/Ethnicity
 

Read/listen Arts/craft Take art 

poetry fair lessons 

1982 1985 1982 1985 1982 1985 

White 20.66 20.37 43.18 44.56 11.12 10.98 

3,461 1,854 3,462 1,857 3,462 1,859 

African­ 15.12 14.16 !7.14 15.41 8.08 7.03 

American 417 248 417 249 417 249 

Hispanic 16.83 14.83 26.50 26.03 10.60 6.92 

186 142 186 142 186 143 

Asian -­ 20.17 -­ 43.71 -­ 15.56 

37 -­ 37 -­ 37 

Creative Photography, Paint or 

writing film	 draw 

1982 1985 1982 1985 1982 1985 

White 6.70 6.73 11.05 10.67 10.34 9.54 

3,463 1,857 3,461 1,856 3,463 1,859 

African- 5.72 4.56 8.01 8.54 7.59 5.04 

American 416 249 417 248 417 249 

Hispanic 6.97 4.00 7.91 5.23 8.80 9.01 

186 144 185 144 186 143 

Asian	 -- 3.02 -- 7.71 -- 7.70 

-- 37 -- 37 -- 37 

Note: First line to right of racial/ethnic category refers to weighted percentage of group engaging in 

activity at least once during 12 months preceding survey. Second line refers to unweighted number 

of respondents. Asian-Americans who were included in an "Other" racial category are not included 

here for 1982. 

19 
Race, Ethnicity, and Participation in the Arts 

Hispanics and just 17 and 15 percent for African-Americans. By contrast, 

whites were only somewhat more likely to have read or listened to poetry. 

Data were available from only 37 Asian-Americans, too few for confident statistical inference, so participation rates for this; group are suggestive 

at best. Asian respondents attended art and craft fairs and read or listened to 

poetry at roughly the same rates as whites. Their attendance at science and 

history museums was comparable to that of Hispanics, whereas their rate of 

visiting historical monuments fell between the white and Hispanic levels. 

The percentages of the African-American, white, and Hispanic groups 

that attended science or history museums- and the differences in those 

rates -- were similar to patterns for attendance at art galleries and museums. 

This suggests that the latter differences have as much to do with museum 

visiting per se as with the content or exhibits of art m~aseums. 

Other activities covered in this section of the SPPA were creative 

pastimes that individuals could pursue in private: taking lessons in writing, 

music, arts, dance, or crafts; working with pottery, ceramics, jewelry, 

leather, or metal; practicing a needlecraft (weaving, sewing, or others); 

creative writing; photography, film, or video "as an artistic activity"; and 

painting, drawing, sculpting, or printmaking. (Respondents were also asked 

if they had worked backstage at musical or other kinds of performances, but 

so few had that we do not report the results here.) 

Most intergroup differences with respect to these creative activities were 

strikingly small. In 1985, for example, 11 percent of the white respondents, 

compared to 7 percent of both African-Americans and Hispanics, reported 

taking art lessons; 7 percent of the whites, 5 percent of the African-Americans, and 4 percent of the Hispanics engaged in creative writing; 10 percent 

of the whites, 5 percent of the African-Americans, and 9 percent of the 

Hispanics created in the visual and plastic arts. In 1982 Hispanics were 

somewhat more likely to report creative writing than whites. Whites were 

twice as likely as Hispanics to report art lessons, photography, and film 

making in 1985, but not in 1982. Asian-American responses were high to 

moderate compared to those of other groups. 

Differences were greater for creative activity in the craft arts, both 

needlecrafts and other crafts. Whites were 50 percent more likely than both 

African-Americans and Hispanics in 1982, and almost twice as likely in 

1985, to report sewing, weaving, or similar activities. They were almost 

twice as likely in 1982 and more than twice as likely in 1985 as AfricanAmericans, and about 50 percent more likely than Hispanics in both years to 

report working with pottery, ceramics, or comparable materials. This pattern 

suggests that with respect to making the visual arts, rates of minority 

2O 
Rates of Participation by Race and Ethnicity 

participation relative to those of the white majority are no higher, and in fact 

may be lower, for the craft arts than for more prestigious creative activities 

like drawing, photography, or painting. The data as a whole indicate that 

minority group members are less likely to attend cultural institutions, relative to whites, than to be found in the ranks of amateur creative artists. 

Nonetheless, the tendency of white Americans to participate at higher rates 

than others manifests itself in responses to most of these questions. 

Use of the Media for Exposure to the Arts 

A subset of respondents to the SPPAs (approximately one-fourth in 1982 

and approximately one-sixth in 1985) were asked if they had, during the past 

year, seen or heard a jazz performance, a classical music performance, an 

opera, a musical theater production, a stage play, a ballet performance, or a 

visual arts program on television and, where appropriate, radio or sound 

recording. These questions are of particular interest for two reasons. First, 

policy makers have viewed the media, especially television, as an important 

means of increasing exposure to art forms that have benefitted from public 

subsidy. To the extent that participation by minorities in consuming the arts 

via the media is greater relative to the non-Hispanic white majority than their 

attendance at live performances, many would regard such an apparent 

equalization of one kind of artistic opportunity as another benefit of programs that promote the arts on television and radio. 

Second, a comparison of differences in the use of media arts programs 

by different groups with those intergroup differences that emerge when we 

look at attendance at live events and exhibitions may provide clues as to the 

origins of the latter differences. Nearly all American families own television 

sets, and nearly all television sets receive one or more public television 

stations, which tend to broadcast fine arts programming. As such, consumption of the arts on television or radio is costless, except in time. Roughly 

speaking, if intergroup differences are simply a matter of taste, we should 

not expect them to be much reduced when we compare viewing a kind of art 

on television to attending the same activity in person. If they are reduced, 

this suggests that lower levels of live attendance may reflect not simply 

differences in taste, but differences in the resources necessary to attend or in 

the comfort felt in the places where live performances and exhibitions are 

held. 

The results (Table 2-4) are striking in two respects. First, more people 

encountered the arts about which the SPPA asked through the media than in 

21 
Race, Ethnicity, and Participation in the Arts 

Table 2-4 

Use of Media for Arts Consumption by Race/Ethnicity 

Watch jazz 

on TV 

Listen jazz 

on radio 

1982 1985 1982 1985 

White 

AfricanAmerican 

Hispanic 

16.91 

3,288 

27.95 

366 

16.06 

203 

14.97 

1,705 

37.94 

186 

15.05 

123 

15.78 

3,281 

36.01 

366 

17.45 

201 

15.47 

1,699 

32.42 

186 

19.43 

124 

Asian -­

-­

24.85 

37 

-­

-­

35.90 

36 

Classical 

records 

Opera 

on TV 

1982 1985 1982 1985 

White 

AfricanAmerican 

23.54 

3,264 

13.24 

362 

22.49 

1,698 

15.48 

186 

12.45 

3,288 

9.32 

366 

12.78 

1,710 

9.97 

187 

Hispanic 

Asian 

15.58 

2OO 

11.03 

123 

46.63 

36 

9.71 

203 

-­

-­

12.70 

123 

25.16 

37 

Musical 

theater 

on TV 

Musical 

theater 

on radio 

1982 1985 1982 1985 

White 

AfricanAmerican 

Hispanic 

Asian 

21.04 

3,279 

17.21 

366 

17.83 

203 

17.43 

1,707 

17.82 

186 

17.67 

124 

40.12 

37 

4.22 

3,275 

4.44 

366 

4.09 

201 

4.92 

1,700 

2.80 

186 

6.50 

124 

1.4.10 

37 

22 
Rates of Participation by Race and Ethnicity 

Table 2-4 (Continued)
 

Use of Media for Arts Consumption by Race/Ethnicity
 

Listen jazz 

records 

Classical 

music on TV 

Classical 

radio 

1982 1985 1982 1985 1982 1985 

White 

AfricanAmerican 

18.42 

3,260 

36.62 

361 

17.03 

1,695 

36.45 

186 

26.04 

3,287 

15.68 

366 

24.89 

1,709 

21.88 

187 

20.49 

3,276 

15.40 

364 

22.01 

1,703 

17.49 

187 

Hispanic 18.76 

201 

16.18 

124 

21.66 

203 

18.59 

124 

19.90 

201 

18.05 

124 

Asian -­19.71 

36 

-­

-­

41.86 

37 

-­

-­

38.51 

36 

Opera on 

radio 

Opera 

records 

1982 1985 1982 1985 

White 

AfricanAmerican 

7.35 

3,269 

5.32 

363 

7.03 

1,702 

4.36 

187 

8.23 

3,281 

3.94 

366 

8.19 

1,709 

4.31 

186 

Hispanic 5.26 

201 

6.17 

124 

3.18 

202 

3.03 

124 

Asian 11.04 

36 

14.10 

37 

Musical 

theater 

records 

Stage 

play 

on TV 

Stage 

play 

on radio 

1982 1985 1982 1985 1982 1985 

White 

AfricanAmerican 

9.53 

3,271 

1.89 

365 

8.24 

1,697 

5.07 

185 

27.86 

3,284 

18.21 

366 

22.91 

1,707 

18.60 

186 

3.90 

3,272 

2.67 

361 

3.93 

1,695 

3.90 

183 

Hispanic 3.40 

20O 

3.00 

124 

14.58 

203 

15.38 

124 

6.54 

199 

3.34 

123 

Asian 19.39 

37 

25.45 

37 

0.00 

37 

23
 
Race, Ethnicity, and Participation in the Arts 

Table 2-4 (Continued)
 

Use of Media for Arts Consumption by Race/Ethnicity
 

Ballet Art 

on TV on TV 

1982 1985 1982 1985 

White 16.98 15.00 23.74 26.75 

3,278 1,707 3,275 1,706 

African­ 10.34 15.66 19.48 23.62 

American 365 187 366 187 

Hispanic 15.09 16.58 16.37 18.40 

203 123 202 124 

Asian -­ 40.92 -­ 36.02 

-­ 37 -­ 37 

Note: First line to right of racial/ethnic category refers to weighted percentage of group engaging in 

activity at least once during 12 months preceding survey. Second line refers to unweighted number 

of respondents. In 1982, the "Other" category included Asian-Americans, whereas in 1985 it did not. 

For the media questions, which were asked only two months of 1985, only two respondents were in 

the "Other" category, too few to warrant reporting results. 

live settings. Persons in every racial or ethnic group in each year were more 

likely to see a jazz concert, a classical music performance, an opera, a stage 

play, or a ballet on television (and in the case of the first three, to hear such 

an event on radio or recording) than to attend a live event. This tendency was 

less pronounced for musical theater (which, in 1985, a slightly larger proportion of the white sample reported seeing live than on television) and for the 

visual arts. (For the visual arts, white and Hispanic, but not African-American, television viewing were roughly comparable to attendance at galleries 

or museums.) 

Second, the proportionate gap between white and minority attendance 

was smaller in consuming the arts through the media than in live attendance. 

The only exceptions were jazz, where African-Americans were even more 

likely than whites to report hearing jazz on television, radio, and record than 

in live performances; and the substantial gaps between Asians and all other 

groups in media-linked consumption of classical music, opera, musical 

theater, ballet, and the visual arts. (The evidence on Asian-Americans is 

intriguing, but inconclusive because the number of respondents [37] is so 

small.) In other words, although members of all groups were more likely to 

24 
Rates of Participation by Race and Ethnicity 

watch these art forms than to attend, this tendency was more pronounced for 

minority groups than for whites. 

Consider a few examples from 1985. That year, 24 percent of white 

respondents, compared to 6 percent of African-Americans and 7 percent of 

Hispanics, reported attending classical music concerts. By contrast, 25 

percent of the whites, compared to 22 percent of the African-Americans and 

19 percent of the Hispanics, reported watching classical music on television. 

In other words, in 1985 whites were twice as likely as Hispanics and more 

than twice as likely as African-Americans to attend a classical concert; but 

only 14 percent more apt than African-Americans and only 32 percent more 

likely than Hispanics to watch one on television. That same year, whites 

were more than twice as likely as African-Americans, and about 50 percent 

more likely than Hispanics to attend a ballet performance. By contrast, 

slightly larger proportions of the latter groups watched ballet on television 

than did whites. 

These findings are notable for two reasons. First, they tell us that the 

media, especially television, have done much to ensure that African-Americans and Hispanic-Americans are nearly as likely as whites to expose 

themselves to classical music, opera, musical theater, drama, ballet, and the 

visual arts. Second, they indicate that a substantial proportion of AfricanAmericans and Hispanics who do not attend such events in person are 

sufficiently interested to watch them on television. This finding suggests the 

potential for developing minority audiences, and leads one to ask why 

African-American and Hispanic-Americans who view the arts on television 

do not attend them live. Do intergroup differences in attendance reflect 

differences in opportunity as well as taste? 

The implications of these data are inconclusive for four reasons. First, 

attending a live event requires more commitment than watching a similar 

program on television. To do the former one must spend time in transit, 

usually pay some money, and face embarrassment if one wishes to leave. By 

contrast, one can view the arts on television free of charge and without 

preparation, and leave a performance by changing the channel. We do not 

know how many respondents who reported watching opera on television, for 

example, did so intently or repeatedly and how many simply spent a few 

minutes watching an opera in between action adventure shows. People who 

watch fine arts events on television but not in person may have less interest 

than those who see them live, albeit more interest than persons who neither 

watch nor attend such activities. 

Second, it is necessary to disentangle watching televised arts programs 

from television viewing generally. African-Americans and Hispanics, on 

25 
Race, Ethnicity, and Participation in the Arts 

average, watch more television than whites; however, analyses described in 

Chapter 5 (Appendix Tables 5-7 and 5-14) indicate that their relatively high 

consumption of televised arts programming does not simply reflect a greater 

propensity to watch television. For the full sample, overall television watching has a small, significant positive effect on the number of kinds of arts 

programs a respondents watched. But even with that measure controlled, 

Al~can-Americans and Hispanics watch as much arts programming as 

comparable whites. Separate analyses on African-American, Hispanic, and 

white subsamples indicate that within each group, general television watching has no significant impact on viewing arts television, with appropriate 

controls. 

Third, we do not know if the musical performances, plays, or dance 

presentations that people watch on television are similar to the ones they 

attend live. It may be that some African-Americans and Hispanics are more 

likely to watch arts events on television than to attend them because they 

prefer the specific programs on television to those available in their communities. 

Finally, these data tell us nothing about the quality of the televised arts 

experience. Many would argue that television simply cannot capture the 

sound of a symphony hall or the texture and color of a work of art. Others 

would contend that attending an arts event represents; a statement of social 

membership that solitary consumption cannot duplicate. We have no data 

that bear on these issues, which are matters of value ratlher than social science 

research. Nonetheless, if one holds to either of these views, a world in which 

Aflican-Americans and Hispanic-Americans disproportionately experience 

the arts via media and white Americans experience them disproportionately 

in person does not seem equitable. By contrast, if one l~elieves that it is good 

to have contact with the arts forms about which the media questions asked, 

and that they are as rewarding televised as live, or that watching such events 

on television will lead to attendance, these findings are encouraging.5 

We explored these issues further by comparing the percentage of respondents in each group who watched a given kind of arts program on TV and 

who also attended comparable live events to the percentage of those who did 

not see such events on television but did attend in person. For all groups, 

people who watched an arts program on television were more likely than 

others to attend comparable live events (see Appendix Tables 2-2 and 2-3). 

In some cases the tendency was slight: for example, in 1982, Hispanic 

respondents who watched jazz programs on television were only 6 percent 

more likely than those who did not to go to live events. By contrast, Hispanic 

respondents in 1982 who watched classical music programs were more than 

26 
Rates of Participation by Race and Ethnicity 

10 times as likely to attend live classical music performances than were those 

who did not. 

A tendency for arts viewing and attending to be more closely associated 

for African-Americans and Hispanics than for whites (with smaller intergroup differences for viewers than for nonviewers) was evident in both 1982 

and 1985 for Hispanic respondents with respect to classical music, musical 

theater, ballet, and art, and for African-American respondents with respect 

to opera and musical theater. These findings may indicate that for these art 

forms television has served to develop an appetite for live attendance among 

new minority audiences. On the other hand, they could mean that AfricanAmerican and Hispanic audiences of these events are more likely than whites 

to pursue their interest by watching them on television; or that watching 

these arts on television is more closely associated with other characteristics 

that lead to live attendance among African-Americans and Hispanics than 

among whites. Therefore, caution demands that these findings be regarded 

as no more than the basis for hypotheses to be pursued in future studies. 

Musical Preferences 

We have hypothesized that more specific definitions of art forms or 

genres vary more markedly with race and ethnicity than categories that are 

broadly defined. During certain months, the SPPA asked respondents if they 

liked to listen to any of a range of musical genres: classical music, opera, 

show tunes, jazz, soul/blues, big band, country western, bluegrass, rock, easy 

listening, folk, barbershop and hymns or gospel. The question did not 

include such genres as rap, salsa, mariachi, cajun, reggae, or polka, for which 

even greater racial or ethnic variation in taste might be expected. Although 

the question is not, strictly speaking, about participation, it provides an 

opportunity to investigate intergroup differences in taste for a wider range of 

musical genres than that about which the core or other participation questions ask. 

Responses are described in Table 2-5. Intergroup differences are summarized by the correlations at the bottom of that table. Correlations between 

groups for 1982 are below the diagonal, for 1985 above it. Correlations on 

the diagonal describe the relationship between each group’s own responses 

for 1982 and 1985. A correlation is a measure of association, in this case 

between the percentages of each group who reported liking each kind of 

music, that ranges from -1.0 to +1.0. If tastes were perfectly coincident, the 

correlation would be 1.0. If they were totally opposed, it would be -1.0. 

27 
 

Race, Ethnicity, and Participation in the Arts 

Table 2-5
 

Percentage Reporting That They Enjoy Specific
 

Musical Genres, by Race/Ethnicity, 1982 and 1985
 

Whites African-Americans Hispanics 

1982 1985 1982 1985 1982 1985 

Classical 29.45 27.13 15.74 12.61 25.68 31.32 

Opera 10.41 11.52 5.74 7.05 5.51 10.29 

Show tunes 25.60 26.77 12.25 12.32 15.51 23.23 

Jazz 24.52 30.19 43.23 57.82 26.67 41.57 

Soul/blues 23.07 28.87 61.14 72.45 28.74 34.80 

Big band 35.69 35.28 18.53 20.94 23.91 21.52 

Country 63.68 57.46 24.65 27.10 49.26 52.95 

Bluegrass 28.27 27.59 5.07 3.02 9.51 15.85 

Rock 36.71 43.17 29.59 32.29 37.49 51.01 

Easy listening 52.39 54.85 24.93 43.17 40.30 46.29 

Folk 28.00 27.43 8.72 13.66 18.01 19.93 

Barbershop 16.70 17.53 4.60 2.88 5.18 7.67 

Hymns/gospel 34.30 38.30 64.49 65.05 16.40 26.61 

4,518 1,758 532 156 277 113 

Correlations White African-American Hispanic 

White .97 .41 .84 

African-American .18 .97 .56 

Hispanic .86 .37 .96 

Note: Pearson correlations. 1985 above diagonal, 1982 below. Diagonal=correlation between 1982 

and 1985 for each group. Correlations subject to rounding error. Z-scores presented in Appendix 

Table 2-1. 

28 
Rates of Participation by Race and Ethnicity 

The diagonal correlations indicate that the musical tastes of each group 

were highly stable between 1982 and 1985. Correlations between the tastes 

of white and Hispanic respondents were also very high in both years. (Both 

whites and Hispanics favored country western music above any other genre, 

both liked easy listening music, and few in either group enjoyed opera.) 

In 1982, the correlation between African-American and white tastes was 

 ̄ 18, positive but nonetheless considerably weaker than any other association 

in the table. African-Americans were less likely than whites to report 

enjoying classical or chamber music, and whites were less likely than 

African-Americans to report enjoying jazz. The largest differences between 

the groups, however, were for soul/blues, country western, easy listening 

and hymns or gospel music. For example, more than 60 percent of AfricanAmerican respondents, but fewer than one in four of the whites, reported 

liking soul or blues music. Less than one-fourth of the African-Americans 

but almost two-thirds of the whites enjoyed country western. More than half 

the whites but fewer than one in four African-Americans liked easy listening 

music. About one-third of the white respondents, but almost two-thirds of 

the African-American respondents, enjoyed hymns or gospel music. Sizable 

minorities of white respondents, but very few African-American respondents, reported enjoying folk or bluegrass music. Although whites were 80 

percent more likely than African-Americans to report that they liked opera, 

the two groups were similar in that few respondents, African-American or 

white, reported enjoying this form. In 1985, the African-American/white 

correlation (based on a smaller sample than in 1982) rose substantially to .41. 

Most of the increase resulted from a marked rise in the proportion of 

African-American respondents who reported that they enjoyed easy listening music, although there was some slight convergence in taste for opera, big 

band, country western, folk, and hymns or gospel music as well. 

Correlations between Hispanic and African-American tastes were midway between those between African-Americans and white preference, .37 in 

1982 and .56 in 1985. Like whites, Hispanics tended to enjoy country 

western and easy listening music and were less likely than African-Americans to report enjoying soul music or blues. Like African-Americans, they 

were less likely than whites to like big band music or, in 1982, show tunes 

and bluegrass. Hispanic respondents reported liking hymns or gospel music 

less than either African-Americans or whites. 

These results indicate notable differences associated with race or ethnicity in a national musical culture dominated by commercially produced 

genres. On the one hand, African-Americans are particularly supportive of 

forms like jazz, soul or blues, and gospel, all of which have deep roots in the 

29 
Race, Ethnicity, and Participation in the Arts 

African-American experience; and relatively uninvolved in such forms as 

bluegrass, barbershop, or, relative to others, country western music, associated with white subcultures. But even genres associated with specific racial 

or ethnic communities appear to have permeated a national musical culture. 

Thus approximately one in four whites liked jazz and soul/blues, and an 

equal proportion of African-Americans enjoyed country western music. The 

findings lend support to images neither of racially segmented cultures nor of 

a homogeneous mass society where racial and ethnic differences have 

atrophied. Instead, we find differentiation without segmentation. 

African-Americans were less likely to report liking classical music than 

white or Hispanic respondents, and opera was enjoyed by only small minorities in any group. In 1985, Hispanics were more likely than whites to report 

enjoying classical music, ranking it sixth among the thirteen genres, higher 

than whites, who ranked it tenth, or African-Americans, for whom it ranked 

ninth. It is thus striking that in 1985 Hispanics were only one half as likely 

as whites to have reported attending classical music concerts. 

Childhood Experience in the Arts 

Advocates of arts education sometimes assert that appreciation of the arts 

must be cultivated from childhood if one is to understand and care about 

them as an adult. Sociologists sometimes refer to the familiarity with the fine 

arts with which educated parents endow their children~ as "cultural capital," 

analogous to bequests of financial capital as a means to ensure that one’s 

children get ahead in life.6 If this emphasis on early artistic experiences is 

justified, then it is possible that intergroup differences in participation reflect 

difl~erences in the way that children of these groups were socialized. 

Fortunately, the SPPAs asked a portion of the respondents (about onethird in 1982 and approximately one-sixth in 1985) about their childhood 

experiences with respect to a variety of art forms. Four questions concerned 

socialization by parents "when you were growing up." Respondents were 

asked if their parents "often, occasionally, or never" listened to classical 

music, took them to art museums or galleries, took them to plays, dance or 

classical music performances, or encouraged them to read books "which 

were not required for school or religious studies.’" Responses to these 

questions are presented in Table 2-6. 

People often have difficulty recalling events that happened in their 

distant past, and we all have some tendency to reconstruct our childhoods so 

as to make them consistent with our subsequent experience. We do not know 

30 
Rates of Participation by Race and Ethnicity 

Table 2-6
 

Cultural Socialization in Family by Race/Ethnicity
 

Parents listened Parents took Parents took Parents 

classical art museums/ plays/dance/ encouraged 

music galleries classical reading 

1982 1985 1982 1985 1982 1985 1982 1985 

White 32.64 34.19 35.33 36.64 33.05 33.59 40.36 39.08 

4,563 1,913 4,567 1,912 4,561 1,910 4,567 1,915 

African­ 18.84 22.17 26.86 26.07 26.31 29.13 32.82 37.91 

American 507 197 508 198 511 194 511 199 

Hispanic 16.56 25.05 22.76 27,09 20.36 23.16 22.26 20.06 

302 140 304 141 302 141 305 141 

Asian -­ 48.70 -­ 43.30 -­ 32.86 46,66 

-­ 39 -­ 39 -­ 39 39 

Note: First line to right of racial/ethnic category refers to weighted percentage of group reporting 

parents engaged in activity "occasionally or often" (for first three columns) or "often" (for "encouraged 

reading"). Second line refers to unweighted number of respondents. In 1982, Asian-Americans were 

in an "Other"category (not included). 

whether such distortions bias the responses affirmatively or negatively, or 

whether, by contrast, individual distortions more or less balance one another 

out. To the extent we are interested in comparisons between groups, we need 

be concerned less by absolute bias than by the possibility that responses from 

different racial or ethnic categories are flawed by different degrees (or 

directions) of biased recall. John Robinson and his colleagues have suggested that question ordering in the SPPA may have made childhood arts 

experiences more salient to respondents who had reported engaging in 

related arts activities. If this were the case, we would expect such tendencies 

to yield exaggerated differences between whites and members of other 

groups in the tables that follow.7 

White respondents were most likely to report that their parents at least 

occasionally listened to classical music. In 1982, 33 percent of whites 

compared to 19 percent of African-Americans and 17 percent of Hispanics 

31 
Race, Ethnicity, and Participation in the Arts 

answered in this way. (In 1985, the figures were 34 percent for whites, 22 

percent for African-Americans, 25 percent for Hispanics, and 49 percent for 

Asians. Regrettably, the small number of Asian-American respondents prevents us from placing much stock in the latter arresting figure,g) These 

differences are comparable to those for attending classical music concerts 

and greater than those for viewing or listening to classical music programs 

on television or radio.9 

In 1982, white respondents were 32 percent more likely than AfricanAmericans to report that their parents took them occasionally or often to art 

museums or galleries when they were young.~° (1985 results were similar.) 

In 1982, they were 55 percent more apt to report such experiences than were 

Hispanic respondents, whereas in 1985 Hispanics were more similar to 

African-American respondents. (More than 40 percent of the Asian respondents -- compared to 37 percent of the whites -- reported such early experience in 1985.) If we compare these results to reports of visits to art 

museums in the past year (Table 2-1 ), we see that the gap between white and 

African-American respondents is somewhat greater than we would expect 

on the basis of these early socialization experiences, whereas the difference 

between white and Hispanic respondents is approximately the same. By 

contrast, the difference in the proportion of whites and African-Americans 

who report watching visual arts programming on television is somewhat less 

than we would expect on the basis of parental socialization. 

Because the question about going to performing ~Lrts events with one’s 

parents was worded to include attendance at plays, dance, or classical music 

performances, it does not admit to straightforward comparison with any of 

the core participation questions. The responses are comparable to those for 

visits with parents to art museums and art galleries, with approximately onethird of the whites in both years, compared to 26 and 29 percent of the 

African-American respondents (1982 and 1985, respectively) and 20 and 23 

percent of the Hispanic group reporting that their parents at least occasionally took them to concerts and plays when they were young.~ 

In 1982, 40 percent of the white respondents, compared to 33 percent of 

the African-American respondents and 22 percent of the Hispanics reported 

that their parents often encouraged them to do reading that was not required 

as part of school or religious instruction. (In 1985, with smaller samples, the 

figures were 39 percent, 38 percent, and 20 percent. Of the few Asian 

respondents, 47 percent reported such parental encouragement.) If we compare these responses to those for the core question on whether respondents 

had read novels, short stories, poetry, or plays during the previous year, we 

see that the proportionate gaps between African-American and white respon32 
Rates of Participation by Race and Ethnicity 

dents are somewhat greater than one might expect on the basis of responses 

to the parental socialization question, whereas the differences between 

whites and Hispanics are somewhat less. 

The SPPAs also asked respondents if they had taken classes or lessons 

in voice or an instrument, art, acting, ballet, creative writing, craft arts, art 

appreciation, or music appreciation at various periods in their lives. Table 

2-7 reports the proportion that never took each kind of class, as well as the 

percentage of respondents who took their first class of each kind when they 

were under the age of 12, between the ages of 12 and 17, and older than 17. 

White respondents were more likely each year to report taking each kind 

of art class or lesson than were African-American or Hispanic respondents. 

Similarly, with just one exception, African-Americans were more apt to 

report having taken classes in each area in each year than Hispanics.~z As 

was the case for other questions asked in only one month of 1985, the 

number of Asian respondents was too small to yield conclusive results. 

Focusing upon 1982, for which the number of African-American and 

Hispanic respondents to these questions was substantially higher than in 

1985, the absolute gap between whites and African-Americans ranged from 

10 percent (50 percent of the whites compared with 40 percent of the 

African-Americans) for vocal or instrumental lessons, to less than 1 percent 

(22 percent of the whites and 21 percent of the African-Americans) for music 

appreciation courses. The ratio of white to African-American participation 

ranged from two to one (for ballet lessons, taken by 8 percent of the whites 

and just 4 percent of the African-Americans), to 1.03:1, for music appreciation courses. Among class types taken by substantial minorities of all 

respondents, whites were 38 percent more likely than African-Americans to 

report classes in the visual arts, 33 percent more apt to report taking creative 

writing classes, 40 percent more likely to report classes in the craft arts, and 

31 percent more likely to report art appreciation classes. 

The proportion of Hispanic-Americans who indicated that they had 

taken classes or lessons was comparable to, although slightly lower than, the 

African-American percentage for the visual arts, acting, and ballet classes. 

Hispanics were just 62 percent as likely as whites and 82 percent as apt as 

African-Americans to report taking creative writing courses. For craft art 

courses the comparable figures were 59 percent and 83 percent. For art 

appreciation courses, they were 53 and 70 percent, respectively. Hispanics 

were especially unlikely to have taken music lessons or music appreciation 

courses. Only 22 percent of the Hispanics, compared to 40 percent of the 

African-American and 50 percent of the white respondents, reported taking 

vocal or instrumental classes or lessons. And only 9 percent, as compared 

33 
Race, Ethnicity, and Participation in the Arts 

Table 2-7
 

Age at First Class or Lesson in Selected Arts Subjects by
 

Race/Ethnicity, 1982 and 1985
 

Age at Music Art Acting Ballet 

first class class class cllass class 

White Never 49.51 48.92 74.55 72.16 90.05 89.16 92.00 90.81 

<12 26.30 28.68 3.00 3.93 1.07 1.00 5.57 7.05 

12-17 19.93 18.61 11.41 12.16 6.03 6.73 0.92 0.89 

>17 4.27 3.78 11.04 11.75 2.84 2.56 1.51 1.25 

African- Never 59.55 62.96 81.60 82.77 93.08 91.53 96.17 97.04 

American <12 13.81 14.23 2.44 0.89 1.02 0.75 1.73 1.14 

12-17 21.23 17.31 11.14 11.98 3.80 6.85 1.04 1.40 

>17 5.41 5.51 4.82 4.36 2.09 0.88 1.05 0.43 

Hispanic Never 77.65 76.07 82.97 88.71 92.69 95.27 96.56 97.28 

<12 6.38 7.37 2.48 0.00 0.60 0.00 1.85 0.44 

12-17 14.20 11.24 9.97 7.74 4.60 3.79 0.00 1.41 

>17 1.77 5.32 4.59 3.55 2.11 0.94 1.60 0.87 

Asian Never -­ 59.88 -­ 70.88 -­ 88.04 -­ 94.59 

<12 -­ 15.04 -­ 6.44 -­ 0.00 -­ 0.00 

12-17 -­ 8.53 -­ 11.76 -­ 7.37 -­ 2.75 

>17 -­ 16.55 -­ 10.91 -­ 4.59 -­ 2.66 

with 21 percent of the African-American respondents and 22 percent of the 

whites, reported ever taking a course in music appreciation. 

The age at which persons first took classes or lessons varied by kind of 

lesson, with music and ballet lessons often taken during the elementary school 

years, and music and art appreciation often taken after the age of 17. Such 

patterns differed somewhat by race and ethnicity, however. For example, 26 

percent of the white respondents, but just 14 percent of the African-American 

respondents, reported taking voice or instrumental lessons before the age of 

12. By contrast, African-Americans were slightly more likely than whites to 

take such lessons during the high school years and after the age of 17. 

Similarly, African-Americans were somewhat more likely than whites to take 

music appreciation courses during the high school years, and somewhat less 

likely to take them before or after. This pattern of relatively equal AfricanAmerican/white participation during the high school years, and less equal 

participation before and/or after high school tended also to be the case for 

34 
Rates of Participation by Race and Ethnicity 

Table 2-7 (Continued)
 

Age at First Class or Lesson in Selected Arts Subjects by
 

Race/Ethnicity, 1982 and 1985
 

Creative Craft Art Music Num ber 

writing 

class 

art 

class 

appreciation 

class 

appreciation 

class 

of 

respondents 

1982 1985 1982 1985 1982 1985 1982 1985 1982 1985 

White 80,78 78.94 66.51 62.44 79.31 78.50 78.47 78.27 4,590 1,923 

0,75 1.07 3.47 4.25 0.81 0.76 2,32 1.95 

7.51 9.21 15.37 17.95 6.16 6.50 9.02 9.39 

10.96 10.78 14.66 15,36 13.71 14.24 10.18 10,39 

African­ 85.60 87.90 76.04 71.79 84.22 83.17 79.10 83.03 515 199 

American 1.05 0.78 3.57 0.93 0.68 0,30 1.73 1.11 

6.21 4.37 13.00 15.79 6.02 11.17 11.01 6.73 

7.14 6.96 7.38 11.49 9.08 5.36 8.16 9.13 

Hispanic 88.17 95.91 80.08 84.31 88.99 93.06 91.02 93.02 305 143 

0.98 0.00 2.14 2.22 1.09 0.00 1.07 0.44 

4.71 1.64 12,17 8.99 4.59 4.00 3.54 3.22 

6.14 2.45 5.61 4.49 5.32 2.94 4.37 3.32 

Asian 89.78 -­ 81.39 -­ 88.89 -­ 87.32 -­ 39 

0.00 -­ 0.00 -­ 0.00 -­ 4,56 

-­ 5.96 -­ 6,45 -­ 5.96 8,13 

4.26 -­ 12.15 -­ 5.15 -­ 0.00 

Note: Figures under class names refer to weighted percentage of group first engaging in activity at 

age indicated. Last two columns indicate unweighted number of respondents. (Ns for each group for 

each year were the same for all classes, except that N=4,589 for white respondents with respect to 

writing classes and craft art classes in 1982.) In 1982, Asian-Americans were coded in "Other" 

category (not included). 

other kinds of classes. Although the data are ambiguous because respondents 

were not asked where they took lessons or classes, the findings do suggest 

that U.S. secondary schools have tended to equalize access to arts training 

between white and African-American students. They do not seem to have 

done this for Hispanic-Americans, however. 13 

Whether such classes have had a long-term effect is another issue. If we 

assume that music appreciation courses focused on classical music, then the 

gaps between white and African-Americans in attending classical concerts 

and watching televised classical music programs are larger, and the differ35 
Race, Ethnicity, and Participation in the Arts 

ences between African-Americans and Hispanics smaller (or in the opposite 

direction), than what one would predict on the basis of these responses. This 

could be the case if African-American students took different kinds of 

courses than whites, or if whites and Hispanics had more opportunities to 

develop a taste for classical music without taking classes. African-Americans are less likely than whites to visit art museums or galleries but more 

likely to watch visual-arts programs on television than we would expect 

from the rate at which they have taken art appreciation courses, whereas the 

white/Hispanic gap in the rate of visiting art exhibits is lower than the 

art-appreciation data would lead one to predict. The difference between the 

percentage of whites, on the one hand, and both Alt’rican-Americans and 

Hispanics on the other, who report that they currently practice creative 

writing and painting or drawing is less than one would expect on the basis 

of differences in the proportion of these groups who have taken art or 

creative writing courses.14 

Summary 

The data reported above are too complex to summarize facilely, but one 

fact emerges clearly. African-Americans and Hispanics are statistically 

underrepresented, relative to whites, among those who attend fine-arts 

events, both performances and exhibitions. They also tend to be less likely 

than whites to participate in the fine arts by watching tlhem on television and 

by engaging in amateur practice, but the differences are proportionately 

smaller than for most kinds of live attendance. White Americans are also 

more likely than African-Americans and much more likely than Hispanics 

to report that they have been socialized into the fine arts (and reading) by 

parents and by classes or lessons. With respect to core participation, the only 

set of questions for which there were a sizable number of Asian respondents, 

Asian-Americans were notable for their rates of attendance at classical 

concerts, art exhibits, and ballet and opera performances, all of which 

exceeded the white rate. 

Despite their superficial similarity in comparison to those of whites, the 

response patterns of African-Americans and Hispanics are distinct. Fewer 

Hispanics than African-Americans reported benefiting from most of the 

socialization experiences about which respondents were asked. Yet their 

rates of participation through watching the arts on media were similar to 

those of African-Americans (but higher for classical music and ballet), as 

was their participation in creative practice (with somewhat higher rates for 

36 
Rates of Participation by Race and Ethnicity 

most visual arts or crafts activities). Hispanics were also more likely than 

African-Americans to visit art exhibits. 

These patterns point to relatively low participation of African-Americans as fine-arts attenders (except for jazz concerts) and art exhibition 

visitors that cannot be explained by artistic socialization alone. Moreover, 

the fact that African-Americans attend jazz concerts at higher rates than 

whites (or Hispanics or Asians) indicates that they are not uninterested in 

performing-arts events pet" se. It is likely that had the SPPA questions 

emphasized artistic genres with closer historical links to the African-American and Hispanic communities, artistic participation for these groups would 

have been as high or higher than that of whites. 

Nonetheless, we cannot assume that relatively low rates of AfricanAmerican and Hispanic participation among attenders of fine-arts events 

simply reflect lower interest in or liking for such activities. The fact that the 

proportionate gap between white respondents, on the one hand, and AfricanAmerican and (to a somewhat lesser extent) Hispanic respondents on the 

other, was greater for live attendance than for media participation indicates 

that there is interest in both the African-American and Hispanic populations 

in the fine arts that is not being manifested in attendance. Moreover, given 

the relatively small differences in the proportion of African-Americans and 

whites who take art and, especially, music appreciation courses, the low rates 

at which African-Americans attend classical music concerts, opera and ballet 

performances, and art exhibits are surprising. Add to this the greater statistical overrepresentation of African-Americans relative to whites for watching jazz on television and listening to it on radio and recordings than for 

attendance at live concerts, and it appears that some factors other than taste 

may inhibit the attendance of African-Americans at live performing-arts 

events and art exhibits. 

If one believes that the kinds of arts participation about which the SPPA 

asked are so important that intergroup differences, of whatever origin, are 

unacceptable, then these findings are of grave concern. If one believes that 

such intergroup differences are unacceptable only if they reflect differences 

in opportunity, rather than differences in preferences, then these patterns 

raise cause for concern, but do not demonstrate conclusively that such 

concern is warranted. 

The reader should be aware, however, that almost all of the activities 

about which respondents were asked (except for reading novels, short 

stories, poetry, or plays) are ones in which only a minority of all respondents 

participated during the year prior to the survey. With respect to many 

activities (for example, attending opera or ballet performances or performing 

37 
Race, Ethnicity, and Participation in the Arts 

onstage), these minorities were very small ones. If one believes that the goal 

of policy should be to increase the number of minority Americans engaging 

in these activities rather than to make participation rates equal, this could be 

accomplished more effectively for most activities by doubling the current 

rates of participation of all groups than by bringing African-American and 

Hispanic rates up to white levels. 

These findings tell us that whites, African-Americans, Hispanics, and 

Asian-Americans participate in a wide range of artistic activities at unequal 

rates, but they do not tell us why these differences exi,st. If one believes that 

racial or ethnic differences of the sort identified here are only problematic if 

thes, seem to be explained by race or ethnicity, as opposed to being just 

associated with race or ethnicity, then these findings are not sufficient. In 

Chapter 3, we investigate the net effects of African-American and Hispanic 

origin on SPPA core participation rates among otherwise similar respondents, and address certain questions this chapter has posed but not answered. 

38 
Chapter 3 

NET EFFECTS OF RACE AND 

ETHNICITY ON PARTICIPATION IN 

SPPA CORE ACTIVITIES 

I

n Chapter 2, we observed persistent differences between the rates of 

participation of African-Americans, Hispanics, Asian-Americans, and 

whites in the artistic activities about which the SPPAs asked. Comparison 

of patterns of responses to different questions suggested that, with certain 

exceptions, differences by race were stronger for live attendance than for arts 

consumption through the media, stronger for live attendance than for artproducing activities, and stronger for performing "high culture" music than 

jazz or popular music. 

It is one thing to establish that racial or ethnic groups vary in the rates at 

which they participate in certain cultural activities. It is quite another to 

demonstrate that these differences result from race or ethnicity, rather than 

being by-products of other differences between such groups. The major goal 

of this chapter is to determine the extent to which differences among whites, 

African-Americans, and Hispanics stem from group membership itself, or 

originate in sociodemographic differences among these groups.1 In other 

words, we shall ask whether members of these groups would participate at 

different rates were they identical with respect to sociodemographic position 

as measured by the SPPA. 

These analyses are both of intrinsic interest and of interest for their 

relevance to public policy towards the arts. If one believes that racial or 

ethnic differences in participation are objectionable only if they flow directly 

from race or ethnicity, the results of this chapter will permit one to see to 

what extent this is the case. If one regards intergroup differences as lamentable whatever their origin, the analyses in this chapter will provide clues as 

to how they might be modified. 

We cannot assume, however, that the factors that lead people to participate in the arts are the same for members of different racial or ethnic groups. 

39 
Race, Ethnicity, and Participation in the Arts 

After exploring the net effects of race and ethnicity on participation, we 

analyze the sociodemographic determinants of participation in the "core" 

activities separately for each group. These separate analyses permit us to 

judge the extent to which the same factors account for variation within each 

group. The results, should they differ, may suggest that different kinds of 

programs are necessary to extend opportunities for participation to members 

of different groups. 

We restrict our analyses to the core participation q~aestions because these 

activities are of particular interest and because they were asked throughout 

the survey periods, thus yielding large African-American and Hispanic 

subsamples.2 Because these questions cover only a limited range of activities, the findings should not be generalized to other forms of participation in 

the arts. 

Explaining Racial and Ethnic Differences 

In this section, we predict participation in each of the core activities as a 

function of race, ethnicity, and sociodemographic characteristics.3 For each 

core activity, we executed two predictive models: one including only racial 

or ethnic origin, and one including racial/ethnic origin and sociodemographic measures. By comparing the size of coefficients estimating the 

influence of racial or ethnic group membership on participation with and 

without controls, we can estimate the percentage of intergroup differences 

for which sociodemographic differences account. 

Because the dependent variables- the participation measures- are 

binary, taking the value of "1" if the respondent did participate and "0" if he 

or she did not, we use a method designed for such variables, called logit or 

logistic regression analysis.4 Race and ethnicity are included in the models 

as a series of dichotomous or "dummy" variables, taking the value of "1" 

when the respondent is a member of the group in question and "0" when he 

or she is not. To use dummy variables in this way, it i:~ necessary to exclude 

a category. In these analyses, whites are the excluded ,category. Coefficients 

for other groups represent the impact of group membership on the probability of participation (net the effects of other independent variables in the 

model) compared to the participation rates of comparable white respondents. 

For the 1982 data, we included "African-American," "Hispanic," and 

"Other" as racial/ethnic categories. (Because we do not know who is in the 

"Other" category, we do not report results for this group.) In models for 

1985, we excluded the very few "Other" respondents from the analyses and 

4O 
Net Effects of Race and Ethnicity 

included "African-American," "Hispanic," and "Asian" as racial/ethnic variables. 

In interpreting these results, we focus upon the coefficients comparing 

the net participation of each racial or ethnic group in the activity in question. 

By way of illustration, consider the section of Table 3-1 reporting the effect 

of being African-American on attending classical music concerts in 1982. 

(These results are reported under 1982 to the fight of the rows labeled "A" 

under the column headed "attends classical concerts.") Column 1 reports the 

results of the model including only the racial/ethnic dummy variables. 

Column 2 reports the results of the model including the racial/ethnic dummy 

variables with sociodemographic controls. Under each column, the row 

labeled "b" reports the logistic regression coefficient indicating the net 

influence of being African-American on attending classical music concerts. 

The coefficient in column 1, for example, is -.845. Because there are no 

controls in the model reported in column 1, this figure is comparable to the 

descriptive percentage results reported in Table 2-1. (Its negative sign means 

that African-Americans are less likely to attend than the omitted group, i.e., 

whites.) Column 2 reports the effect of being African-American on attending 

classical music concerts, controlling for a wide range of sociodemographic 

differences between the white and African-American respondents. Because 

the coefficient is less than that in column 1 but nonetheless remains negative, 

it indicates that part, but not all, of the difference between African-Americans and whites is attributable to sociodemographic differences between the 

two groups. By dividing the coefficient in column 2 (-.566) by the coefficient in column 1 and subtracting the result from unity, we can conclude that 

roughly 33 percent of the difference in rates of participation between African-Americans and whites resulted from measured sociodemographic differences between the two groups, whereas the remainder stems from other 

SOUrCes. 

We shall not discuss the standard error (the figure immediately under the 

logistic regression coefficient), which is of interest only to statistically 

sophisticated readers. Of more general interest is the alphabetical notation 

below that (in the row labeled "sig"). Probability theory tells us that when 

one uses a sample from a larger population, one gets some positive or 

negative coefficients simply by chance. The letters in the significance rows 

of Table 3-1 (keyed to an explanation at the end of the table) tell us how 

likely it is that a coefficient of a given magnitude would occur by chance. 

The letter "c" in the significance row of column 2 under classical music (for 

African-Americans in 1982) tells us that such an effect (-.566) would be 

estimated by chance fewer than 5 times out of 100,000. This is a very high 

41 
Race, Ethnicity, and Participation in the Arts 

Table 3-1
 

Coefficients Representing Effects of African-American (A) and
 

Hispanic (H) on Core Participation Items (1) with Race/Ethnicity
 

Only and (2) with Demographic Controls
 

Jazz Classical 

1982 

A b .631 .683 -.845 -.566 

se .071 .084 .097 .110 

sig c c c c 

H b -.090 .075 -.667 -.071 

se .121 ,133 .123 .137 

sig NS NS c NS 

1985 

A b .381 .453 -.868 -.557 

se .084 ,101 ,111 .128 

sig c c c d 

H b -.382 -.272 -.805 -,261 

se .140 .156 .137 .153 

sig a NS c NS 

Ballet 

1982 

A b -.967 -.781 -.774 -.617 

se .182 .202 .074 .086 

sig c b c c 

14 b -.000 .511 -.486 -.039 

se ,161 ,179 ,090 .104 

sig NS a c NS 

1985 

A b -,799 -.536 -.948 -.790 

se .187 .205 ,088 .102 

sig c a c c 

H b -,384 ,094 -,332 .101 

se .196 .211 .090 .105 

sig a NS b NS 

42 
 

Net Effects of Race and Ethnicity 

Table 3-1 (Continued) 

Coefficients Representing Effects of African-American (A) and 

Hispanic (H) on Core Participation Items (1) with Race/Ethnicity 

Only and (2) with Demographic Controls
 

Opera Musical Play 

1982 1 2 1 2 1 2 

A b -.900 -.582 -.825 -.567 -.903 -.674 

se .208 .240 .081 .093 .103 .118 

sig c a c c c c 

H b -.275 .356 -.734 -.314 -.970 -.505 

se .212 .233 .106 .119 .145 .160 

sig NS NS c a c a 

1985 1 2 1 2 1 2 

A b -.715 -.306 -.884 -.562 -.815 -.603 

se .228 .249 .098 .111 .113 .133 

sig a NS c c c c 

H b -1.334 -.832 -.753 -.339 -.761 -.359 

se .388 .428 .117 .131 .140 .159 

sig b NS c a c a 

Instrument Act, sing Read 

1982 1 2 1 2 1 

A b -.194 -.191 .040 .042 -.701 -.501 

se .137 .147 .116 .127 .051 .062 

sig NS NS NS NS c c 

H b -.271 -.352 -.518 -.466 -.951 -.579 

se .191 .217 .199 .212 .070 .084 

sig NS NS a a c c 

1985 1 2 1 2 1 2 

A b -.547 -.317 -.195 -.043 -.629 -.456 

se .209 .221 .151 .169 .056 .069 

sig a NS NS NS c c 

H b -.381 -.103 -.489 -.293 -.705 -.284 

se .245 .254 .215 .228 .071 .086 

sig NS NS a NS c b 

Note: b is the logistic regression coefficient; se is the standard error; sig refers to the level of statistical significance, where a=probability less than .05, b=probability less than .001, c=probability less 

than .00005, and NS=not significant. 

43 
Race, Ethnicity, and Participation in the Arts 

level of statistical significance and enables us to conclude that AfricanAmericans really were less likely to attend classical, music concerts than 

whites, as the negative regression coefficient indicates. 

Racial/Ethnic Effects Net of Sociodemographic
 

Differences
 

In chapter 2 we raised the possibility that differences in participation 

between whites, on the one hand, and African-Americans and HispanicAmericans, on the other, might result simply from the fact that whites as a 

group are economically better-off. Because educational attainment and occupational status are associated with patterns of leisure activity and interest 

in the arts, it seemed reasonable to expect that at least some of the differences 

we observed stemmed from sociodemographic differences between whites 

and members of other groups. 

We explored this possibility by including race/ethnicity in a predictive 

model that controlled for a wide range of socioeconomic and demographic 

characteristics. These characteristics included: gender, three categories of 

residence (central city, other SMSA, and outside an SMSA), age, education, 

income, seven broad categories of occupation (1982: ]professional and technical; managerial and administrative; sales and clerical; craft, operative, 

service, farm, transport, laborers, private household, and armed forces; 

unknown; unemployed and retired; keeping house; and student; 1985: executive, administrative, managerial; professional; technical, sales, and administrative support; craft, operative, service, farm, armed forces; unknown; 

unemployed and retired; keeping house; and student); and five categories of 

marital status (married, widowed, divorced, separated, and single)? 

To what extent are differences in participation in the core activities 

attributable to differences among groups in the sociod:emographic controls? 

No single generalization applies to African-American~, Hispanic, and Asian 

respondents. 

Variation between African-Americans and whites. Differences in participation between African-Americans and whites were partially attributable to 

sociodemographic differences between these two groups; but significant 

differences tended to persist even in the presence of sociodemographic 

controls. In both 1982 and 1985, African-Americans were significantly less 

likely than whites, even after controlling for sociodemographic factors, to 

44 
Net Effects of Race and Ethnicity 

attend classical music concerts, musical theater performances, plays, ballet 

performances, and art exhibitions, and significantly less likely to report 

reading novels, plays, poems, or short stories. In 1982, but not 1985, 

significant differences in opera attendance between African-Americans and 

whites remained after controls, as well. For reading and for attendance at 

classical music concerts, musical theater performances, plays, and art exhibits, the differences, net sociodemographic factors, were highly significant. 

For these activities, there are small but persistent differences between African-Americans and whites that cannot be attributed to the different sociodemographic characteristics of these two groups. 

Nonetheless, introducing sociodemographic controls did diminish the 

differences in both 1982 and 1985 with respect to each of the activities 

mentioned above. In 1982, between 20 percent (for ballet) and 36 percent 

(for opera) of the African-American/white differences were attributable to 

sociodemographic variation between African-Americans and whites. In 

1985, similar proportions of the African-American/white differential were 

attributable to sociodemographic variation (from 18 percent for art exhibitions to 37 percent for musical theater), with the exception that 57 percent of 

the variation in opera attendance was of sociodemographic origin. In other 

words, except for opera attendance, less than one-half, and in most cases 

closer to one-fourth, of the differences between African-American and white 

probabilities of participation in these activities stem from differences in the 

sociodemographic characteristics of these groups. 

It is instructive to consider the core activities -- jazz concert attendance, 

public performance on a musical instrument, and acting, singing, or dancing 

in public--to which this generalization does not apply. In both years, 

African-Americans were significantly more likely than whites to report 

attending live jazz concerts, and controlling for sociodemographic characteristics merely increased their advantage, although modestly. In both years, 

whites were slightly more likely to report performing on a musical instrument in public. In 1982, adding sociodemographic controls yielded only a 

trivial reduction in the small and statistically insignificant difference. In 

1985, the gross difference was modestly significant; whereas, with sociodemographic controls, it was not significant at all. For acting, singing, and 

dancing, neither the gross nor net difference between African-Americans 

and whites was significant in either year. 

The pattern that emerges is one of significant differences between 

African-American and white participation in the consumption of most highcultural arts activities, both in gross terms and with sociodemographic 

characteristics controlled. With respect to these activities, a substantial 

45 
Race, Ethnicity, and Participation in the Arts 

portion, but (with one exception) less than hall of the .difference results from 

variation between African-American and white Americans in sociodemographic factors. By contrast, the greater propensity of African-Americans to 

attend jazz concerts- the one activity with historical ties to the AfricanAmerican community- is actually accentuated when sociodemographic 

differences are controlled. Gross differences between African-Americans 

and whites with respect to acting or singing (including popular or commercial as well as fine-arts forms) are slight; in the one case in which such a 

difference is modestly significant, it becomes insignificant when sociodemographic factors are taken into account. 

This pattern reinforces our conviction that one cannot generalize about 

racial differences in artistic participation, per se. We suspect that if more art 

forms with origins in the African-American experience had been included 

among the core activities, the results would reveal, as; was the case for jazz, 

statistical underrepresentation of white Americans. 

It is with respect to attendance at live, noncommercial, high-cultural 

events, as well as attendance at musical theater and reading imaginative 

literature, that whites participate at significantly higher rates than AfricanAmericans, even controlling for demographic differences between the two 

groups. In other words, African-Americans are less likely than whites of 

similar socioeconomic standing to engage in the public consumption of 

Euro-American "high culture" and related genres. 

Although these interracial differences are persistent and appear with 

respect to most of the forms of participation examined here, they are not 

large in magnitude relative to differences associated with other determinants 

of participation.6 With respect to all of the activities for which being African-American significantly lessens participation (relative to whites), the 

direct effect of race is dwarfed by the impact of educational attainment and 

(e×cept for reading in 1982) exceeded by the effect of family income. 

Similarly, once other sociodemographic factors are taken into account, 

participation rates of African-Americans and whites are more similar than 

are rates for men and women for all such activities but visiting art exhibitions. They are also more similar than rates for inner-city dwellers and 

persons living outside of SMSAs for all such activities but attending classical 

music performances and reading imaginative literature. Thus race is a far less 

important net predictor of participation in all activities in which AfricanAmericans participate significantly less than whites t]han educational attainment. In most cases, race is also a weaker predictor than income, gender, or 

urban residence. Note, however, that African-Americans earn less money 

and have historically received fewer years of formal education than compa46 
Net Effects of Race and Ethnicity 

rable whites.7 Therefore, in addition to its direct negative effect, being 

African-American exerts a small indirect negative effect on probability of 

participation in the core activities because African-Americans have, on 

average, lower incomes and fewer years of formal education than whites. 

Variation between whites and Hispanics. The results for Americans of 

Hispanic origin lend themselves less easily to generalization. For one thing, 

no single pattern characterized Hispanic participation in the core consumption activities. For another, the influence of Hispanic origin on participation 

in specific activities varied from year to year. Although the latter differences 

were not statistically significant, the relatively small size of the Hispanic 

subsamples and, more important, the fact that the survey was not designed 

to represent statistically the Hispanic population, make the differences 

between the 1982 and 1985 results difficult to interpret. 

In 1982, Hispanics were significantly less likely than whites to report 

reading novels and other imaginative works, attending classical music concerts, art exhibits, plays, musical theater performances; or acting, singing, or 

dancing on stage. In 1985, they were significantly less likely than whites to 

report every activity but performing on an instrument in public. 

For most of these activities, however, large portions of the Hispanic/ 

white difference stem from differences in the sociodemographic composition of the two groups. Entering sociodemographic controls into the 1982 

models, for example, eliminates 89 percent of the differential between 

whites and Hispanics in classical music attendance, 91 percent of the variation in attending art exhibits, 57 percent in attending musical theater 

performances, 48 percent in attending stage plays and 39 percent in reading 

imaginative literature. Indeed, after controlling for these characteristics, 

rates of Hispanic participation are significantly lower than those of whites 

for no activities but attending musical theater performances and plays, and 

reading imaginative literature (in both years); performing on stage (in 1982); 

and attending opera (in 1985). In other words, these analyses demonstrate 

that Americans of Hispanic origin are about as likely as white Americans 

with similar sociodemographic characteristics to attend ballet, classical 

music, and jazz performances, to visit art exhibitions, and to perform on a 

musical instrument. Indeed, in 1982, Hispanic respondents were significantly more likely to attend ballet performances than sociodemographically 

comparable whites. 

Two differences are notable between patterns for Hispanic and AfricanAmerican respondents. First, although participation rates are roughly comparable for these two groups for most activities, larger proportions of the 

47 
Race, Ethnicity, and Participation in the Arts 

differences between Hispanics and whites than between African-Americans 

and whites stem from intergroup differences in sociodemographic attributes. 

By contrast, more of the differences between African-.Americans and whites 

reflect differences between the races in tastes, access., or unmeasured characteristics not associated with the sociodemographic controls. What this 

means is that public policies or historical processes that made Hispanics 

more similar to whites with respect to such resources; as educational attainment, occupation, or earnings would, as a by-product, minimize many 

differences in artistic participation as well. So would policies that increased 

the artistic participation of people with fewer educational, occupational, and 

financial resources, even if those policies were not directed specifically at 

Hispanic Americans. By contrast, even if African-Americans became more 

similar to white Americans in their sociodemographic characteristics and 

even if the link between such characteristics and participation were lessened, 

African-Americans could still be expected to participate slightly but significantly less than whites in several of the core activitie.,s. 

Hispanics and African-Americans also differ wit]h respect to the activities for which these generalizations do not hold. As we have seen, the 

statistical overrepresentation of whites relative to African-Americans applies only to predominantly Euro-American consumption activities and not 

to jazz or public performance. By contrast, Hispanic Americans participated 

at lower rates than whites in both years, net sociodemographic differences, 

only in reading and in attendance at musical and dramatic theatrical performances. Note that these three activities are the only ce, re activities for which 

command of the English language is ordinarily essential. Whereas almost all 

African-Americans and white Americans are native English speakers, a 

substantial proportion of Hispanic Americans are not. Thus we surmise 

(although, lacking data on language we cannot be sure) that lower net rates 

of Hispanic participation in activities involving the printed and spoken word 

reflect the linguistic characteristics of the Hispanic population and the 

relatively low availability of performances and imaginative literature in 

Spanish. Were the availability of such materials increased, we would expect 

to see Hispanics participate in them at rates comparable to those of whites 

with similar sociodemographic attributes. 

Variation between Asian and white Americans. The 1985 SPPA (unlike its 

1982 counterpart) made it possible to distinguish between Asian-American 

and other respondents. Nonetheless, because there were so few Asian respondents (well under 2 percent of the total sample), we cannot report their 

behavior with much statistical confidence. In models with only race and 

48 
Net Effects of Race and Ethnicity 

ethnicity included, Asians were more likely than whites to participate in all 

the activities that do not rely on the spoken or printed word except attending 

jazz concerts, and less likely than whites to participate in those that do. 

Nonetheless, these differences were small and never statistically significant. 

Because Asian-Americans tend on average to have sociodemographic 

characteristics that are associated with participation in the core activities, 

entering sociodemographic controls actually decreased net Asian participation relative to white participation. Thus Asian-Americans were significantly less likely than whites in similar sociodemographic circumstances to 

attend musical or dramatic stage presentations. Differences with respect to 

other core activities remained statistically insignificant. 

Differences in Predictors of Participation by 

Race/Ethnicity 

Built into the preceding analyses is the assumption that the same sociodemographic factors influence the participation of African-Americans, Hispanics, and whites in the same ways and to the same extent. This is a useful 

simplifying assumption because it enables us to estimate net differences in 

participation. But if we are interested in understanding the factors that lead 

members of racial and ethnic minorities to participate in the arts activities 

about which the surveys asked, we must consider the possibility that different groups arrive at participation by different routes. After much analysis, 

we conclude that the sociodemographic predictors of artistic participation 

(as defined by the core variables) are not systematically different for African-Americans, Hispanics, and whites.~ 

Differences in predictors of participation for whites and African-Americans. 

For both African-Americans and whites, educational attainment tended to be 

the variable that most effectively distinguished participants from nonparticipants for most of the core participation measures. Each of the other independent variables was significant, although less so than education, in 

predicting most of the participation measures for whites. For African-Americans, SMSA residence, income, and, in 1982, occupation, were also significantly related to many core variables. Although they were less likely to be 

significant for African-Americans than for whites (in part because significance is a function of the number of cases and there were many more whites 

than African-Americans among the respondents to the survey), most predic49 
Race, Ethnicity, and Participation in the Arts 

Table 3-2
 

Significant Differences in Models Predicting
 

Responses to Core Participation Questions for African-American,
 

Hispanic, and White Subsamples
 

ACTIVITY PREDICTOR 

Jazz WOMEN 

MARITAL 

EDUCATION 

Classical music EDUCATION 

OCCUPATION 

Opera SMSA 

OCCUPATION 

Musical theater WOMEN 

EDUCATION 

Plays WOMEN 

SMSA 

Ballet SMSA 

Significantly negative for African-Americans (1982 and 

1985). Not significant for whites in 1982 and significantly positive in 1985. 

Significantly positive for whites but not for AfricanAmericans or Hispanics in 1982. 

Significantly positive for whites but not for Hispanics in 

1982. 

More significantly positive for whites than for Hispanics 

in 1982. 

Significantly positive for whites but not for Hispanics in 

1985. 

Extremely positive for Afric, an-Americans and Hispanics
 

but not for whites in 1985.
 

Extremely positive for Hispanics but not for African-


Americans or whites in 1985.
 

Significantly positive for whites but not for AfricanAmericans in 1982. 

More significantly positive for Hispanics than for whites
 

in 1985.
 

Significantly positive for whites but not for AfricanAmericans or Hispanics in 1982. 

More significantly positive for African-Americans than 

for whites in 1982. 

Extremely significantly positive for Hispanics but less so 

for whites and not significant for African-Americans in 

1982. Extremely significant (positive) for AfricanAmericans but not for whites or Hispanics in 1985. 

50 
Net Effects of Race and Ethnicity 

Table 3-2 (Continued)
 Significant Differences in Models Predicting Responses
 

to Core Participation Questions for African-American,
 

Hispanic, and White Subsamples
 

ACTIVITY PREDICTOR 

Art WOMEN Significantly positive for whites but not for Africanmuseums Americans in 1982. 

SMSA Significantly positive for African-Americans but less so 

for whites and not significant for Hispanics in 1982. 

EDUCATION More significantly positive for whites than for Hispanics 

in 1985. 

Perform: 

instrument 

SMSA Extremely significantly positive for Hispanics but not for 

African-Americans or whites in 1982, 

Perform: 

act, sing, 

SMSA Extremely significantly positive for Hispanics but not for 

African-Americans or whites in 1982 and 1985. (Signifidance cantly negative for whites in 1985.) 

EDUCATION Significantly positive for whites but not for Hispanics in 

1982. 

Literature WOMEN More significantly positive for whites than for Africanreading Americans and Hispanics in 1982 and African-Americans in 1985. 

SMSA More significantly positive for African-Americans than 

for whites in 1985. 

AGE Significantly negative for African-Americans but not for 

whites in 1982. 

EDUCATION More significantly positive for whites than for AfricanAmericans in 1982. 

OCCUPATION More significantly positive for African-Americans than 

for whites in 1982. 

Note: Descriptive statements provided only for differences that are statistically significant, Similar 

differences that do not reach statistical significance are not noted in this table. 

51
 
Race, Ethnicity, and Participation in the Arts 

tors took the same sign and, in many cases, were of the same order of 

magnitude for African-Americans and whites. 

In only a few cases were there significant differences in models predicting core participation activities for the two races. In 1982, most such 

differences reflected an apparently stronger sexual diivision of labor in the 

consumption of the arts among whites than among Afi’ican-Americans. That 

year, white women were significantly more likely than white men to report 

having participated in all of the core activities except playing a musical 

instrument in public and attending jazz concerts? iBy contrast, AfricanAmerican women were significantly more likely than African-American 

men only to read works of imaginative literature and attend ballet performances. Differences between African-Americans and whites in the impact of 

gender were statistically significant in 1982 with respect to attending jazz 

concerts, attending musicals, attending plays, visiting art museums and art 

galleries, and reading literature. In each of the first four cases, white women 

were more likely to engage in the activity than white men, but AfricanAmerican men were more likely to do so than African-American women. 

Women of both races were more likely to read literature than men, but the 

differences were significantly greater for whites. 

For 1982, these differences were notable and persistent across different 

kinds of artistic participation. But in 1985, the effects of gender varied less 

markedly by race, except for attending jazz concerts and reading literature, 

for which the gap widened. With respect to attending musicals and plays and 

visiting art exhibitions, however, African-American women joined white 

women in being more likely than men to participate, and the effects of gender 

became similar for the two groups. In summary, the pattern for the two years 

indicates that there may be more marked gender differences in artistic 

participation among whites than among African-Americans; but, except for 

reading literature and attending jazz concerts, the differences are not large or 

persistent. Nonetheless, the interaction of gender and race deserves further 

investigation. 

For some activities in each year, the positive impact of living in an 

SMSA was greater for African-Americans than for whites. In 1982, although 

both African-Americans and whites were significantly more likely to attend 

plays and visit art galleries and museums if they lived in SMSAs, the 

advantage of SMSA dwellers was significantly greater for African-Americans. In 1985, the same was true for reading literature. Also in 1985, SMSA 

residence was not significantly related to attending operas or ballet performances for whites, but was overwhelmingly so for African-Americans. That 

year, all 20 African-Americans who reported going to opera performances, 

52 
Net Effects of Race and Ethnicity 

and 32 of 33 who attended ballet performances, lived in SMSAs. These 

differences between African-Americans and whites are notable, but because 

they were discernible for no activity in both 1982 and 1985, they must be 

regarded with caution. 

In 1982, although single and divorced whites and African-Americans 

were more likely to attend jazz performances than others, the advantage of 

single and divorced people was significantly greater for whites than for 

African-Americans. Although the pattern held in 1985, the difference was 

not significant. 

In 1982, although education and occupation were both very significantly 

associated with reading works of imaginative literature among both AfricanAmericans and whites, the effects of education were significantly greater for 

whites and the effects of occupation were stronger for African-Americans. 

Moreover, whereas age was positively, but not quite significantly, associated 

with reading for whites, it was negatively and significantly related to reading 

for African-Americans. In 1985, these patterns held but none of the differences were significant, although the difference for age was nearly so. The 

pattern suggests, but does not confirm, the hypothesis that there may be 

increasing interest in reading literature among younger cohorts of AfricanAmericans that cannot be explained solely by reference to increases in 

African-American educational attainment. 

Taken together, the separate models for African-Americans and whites 

suggest that the same sociodemographic characteristics are related to most 

of the core participation measures in approximately the same way for 

members of each group. There is a greater tendency for white women to 

outparticipate white men than for African-American women to outparticipate African-American men, and a stronger tendency for residence outside 

an SMSA to depress African-American attendance at arts events more than 

it depresses white attendance. Few specific differences, however, were 

significant in both 1982 and 1985, leading us to offer these observations as 

hypotheses for further study rather than as conclusions. 

Differences in predictors of participation for whites and Hispanics. As was 

the case for African-Americans and whites, education was by far the strongest predictor of participation in most of the core activities for Hispanics in 

both 1982 and 1985. As was the case for African-Americans, most of the 

predictors took the same sign and many were of roughly the same magnitude 

for Hispanics as for whites, but, because of the far smaller number of 

Hispanic than of non-Hispanic white respondents, fewer were statistically 

significant. Given these relatively few, relatively weak, and very inconsistent 

53 
Race, Ethnicity, and Participation in the Arts 

results, we can only conclude that the factors accounting for participation in 

the core activities were similar for whites and Hispanics. 

Differences in predictors of participation for African-Americans and Hispanics. There were no statistically significant differences in the models 

predicting participation in the core activities for African-Americans and 

Hispanics. 

Differences in predictors of participation for each group between 1982 and 

1985. Perhaps unsurprisingly, given the brief time between the two surveys, 

no statistically significant differences in predictors for African-Americans 

and Hispanics were observed. For whites, residence in an SMSA had a 

significantly stronger positive impact on visiting art galleries and museums, 

and a significantly stronger negative impact on playing an instrument in 

public in 1985 than in 1982. The positive impact of educational attainment 

on reading imaginative literature was slightly, but significantly, weaker in 

1985 than in 1982. Given the large size of the white subsample and the large 

number of coefficients, we place little stock in these differences. 

Summary. It was important to test whether the mode, Is for African-Americans, Hispanics, and whites indicated that the factors influencing participation for these groups differed. If they had, such evidence might have 

suggested, first, that the social meaning of participation differed, on average, 

for members of these groups and, second, that public policies or sociodemographic change would influence African-American, Hispanic, and white 

participation in systematically different ways. Moreover, if the differences 

were substantial, they might lead us to question our’ interpretations of the 

aggregated models described in the first part of this chapter. 

The findings of these analyses provide no compelling evidence of systematic differences in factors leading African-Americans, Hispanics, and 

whites to participate in the core activities about which the SPPA asked. 

Significant differences were few, usually small in magnitude, and rarely 

persisted from one year to the other. It is possible that more differences 

would have been found had the selection of activities about which respondents were asked been broader. Note, however, that the variation present 

among the different core activities was sufficient to permit us to note 

systematic patterns of racial differences in rates of pa~rticipation, whereas no 

such systematic differences were observed with respect to the predictors of 

participation. It is also possible that a different set of predictor variables 

might have revealed significant differences not noted here. It is not obvious 

54 
Net Effects of Race and Ethnicity 

to us, however, what such additional predictors might be. Finally, were the 

African-American and Hispanic sample sizes larger, it is likely that more 

differences would have emerged as statistically significant. We believe there 

are important reasons to include more African-American and Hispanic (and 

Asian and Native American) respondents in the SPPA. But we regard the 

African-American and Hispanic sample sizes as adequate for detecting 

substantively meaningful differences in models predicting core participation 

items. In short, these analyses convince us that the sociodemographic characteristics accounting for most kinds of artistic participation are basically 

similar for African-American, Hispanic, and white Americans. In Chapter 5, 

we construct more detailed models predicting several additional dimensions 

of artistic participation. 

55
 
Chapter 4 

RACIAL/ETHNIC DIFFERENCES IN 

UNSATED DEMAND FOR 

PARTICIPATION 

I
n chapter 2, we noted persistent differences in rates at which Asian,
 

African-American, Hispanics, and white Americans; participate in the core
 

activities about which the SPPAs asked all respondents. In chapter 3, we 

asked to what extent these differences could be accounted for by sociodemographic attributes with respect to which Asians, African-Americans, Hispanics, and whites also differ. In this chapter, we focus on the extent to which 

such differences reflect intergroup differences in &;mand for the arts as 

opposed to differential exposure to barriers to participation. We consider this 

question with respect to the seven core activities that involve attendance at 

arts events.~ 

Approximately one-fourth of the 1982 respondents and one-sixth of the 

1985 respondents were shown a card listing the activities and told: 

"Few people can do everything they would like to do. But if you 

could do any of the things listed on this card as often as you wanted, 

which ones would you do more often than you have during the last 

12 months?" 

Those respondents who said they would like to have done a given 

activity more than they had in the past year were then asked to indicate which 

of several reasons were responsible for the fact that they had not participated 

more. 

Demand for Greater Participation 

Members of a group may participate in a given activity at a lower rate 

than members of another group for either of two reasons. They may do so 

because they enjoy or otherwise value the activity less. Or they may want to 

56 
Racial/Ethnic Differences in Unsated Demand 

engage in the activity as much as do members of the other group, but face 

obstacles to participation that the others do not. 

These two explanations have very different implications for public 

policy. If low participation results not from low demand but from barriers to 

participation, policy might equalize participation by eliminating the barriers. 

If low participation results not from barriers but from low demand, policies 

aimed at eliminating inequality must serve to increase demand and not 

simply to level barriers. 

We hesitate to interpret people’s responses to questions about their 

desire for increased participation, for we are not sure what people mean 

when they say they "want" to attend arts events more than they do. Some 

people may deeply desire to attend more, but be unable to do so for well 

defined reasons. Others may wish to attend more, but lack the willingness 

to pay the cost in foregone opportunities to do things they value even more 

highly. Still others may mean that they wish they were the kind of person 

who liked the arts more than they do. We do not believe that everyone who 

reported wanting to participate in an activity more cared passionately about 

doing so. As long as the different meanings of "want" were not distributed 

by race and ethnicity in dramatically different ways, however, responses to 

this question may provide clues as to the extent that intergroup variation in 

attendance represents differences in demand or differences in opportunity. 

Nonetheless, without knowing more than we do about the subjective meaning of these responses, we are reluctant to regard them as any more than 

clues. 

Responses to the "want more" question are reported in Table 4-1 for each 

activity and for African-Americans, Hispanics, whites, and (in 1985) AsianAmericans. We assume that "wanting to do more" means something different for a person who already participates than it does for someone who does 

not. Consequently, we report results separately for attenders (respondents 

who engaged in the activity at least once during the previous 12 months) and 

nonattenders. Consistent with our focus on rates of participation (rather than 

levels of participation), we look more closely at the latter. 

Findings. It has been suggested that the arts are addictive. That is, whereas 

demand for most goods precedes and is sated by consumption, consumption 

of the arts is said to beget demand for more.2 If this is the case, it explains 

what John Robinson, in a report on the 1982 SPPA, has called the "moremore principle": the more activities in which respondents participate, the 

more likely they are to participate in still others.3 

Our findings on unsated demand for the core attendance activities are 

57 
Race, Ethnicity, and Participation in the Arts 

Table 4-1
 

Percentage of Attenders and Nonattenders Wanting to Do
 

Each Activity More Than They Had in the Previous 12 Months,
 

by Race/Ethnicity
 

Jazz Classical Opera Musical 

Attenders 1982 1985 1982 1985 1982 1985 1982 1985 

Whites 53.77 59.89 53.15 46.56 44.50 40.41 69.77 64.69 

394 168 568 279 111 48 882 380 

African­ 67.74 50.12 42.79 41.62 26.95 25.18 50.03 56.85 

Americans 80 42 31 17 4 9 44 30 

Hispanics 51.41 42.23 61.89 44.99 24.87 NA 68.91 45.24 

28 10 17 8 4 0 34 11 

Asian- NA 42.41 0.00 30.61 

Americans 0 4 2 4 

Nonattenders 1982 1985 1982 1985 1982 1985 1982 1985 

Whites 13.34 14.60 14.28 13.36 7.17 8.50 27.33 24.82 

3,995 1,643 3,824 1,534 4,278 1,762 3,510 1,430 

African­ 24.08 22.30 10.34 7.82 4.88 3.42 16.35 14.87 

Americans 457 245 506 269 531 278 493 256 

Hispanics 14.13 19.28 12.65 5.61 4.82 4.80 16.24 10.29 

273 138 284 140 297 148 267 137 

Asian­ 6.77 5.29 1.98 14.01 

Americans 47 43 45 42 

consistent with Robinson’s "more-more" dictum and with the addiction 

model of arts consumption. With only four exceptions (all cases in which 

only two or fewer respondents participated in the given activity), for every 

activity and every racial/ethnic group, attenders were more than twice as 

likely (and in most cases three or four times as likely), to want to participate 

more than were nonattenders. For example, in 1982, 54 percent of white jazz 

attenders, but just 13 percent of white nonattenders, reported wanting to 

attend jazz concerts more. That year, 43 percent of African-Americans who 

attended classical music concerts wanted to attend more, compared with just 

58 
Racial/Ethnic Differences in Unsated Demand 

TABLE 4-1 (Continued)
 

Percentage of Attenders and Nonattenders Wanting to Do
 

Each Activity More Than They Had in the Previous 12 Months,
 

by Race/Ethnicity
 

Plays Ballet Art 

Attenders 1982 1985 1982 1985 1982 1985 

Whites 62.42 59.95 54.29 55.09 57.18 57.91 

575 245 182 80 1,057 475 

African­ 55.38 48.06 31.83 44.33 50.48 57.26 

Americans 27 23 5 11 49 33 

Hispanics 57.45 20.44 57.92 65.01 78.86 63.59 

18 4 9 3 52 28 

Asian- NA 0.00 43.23 

Americans 0 2 6 

Nonattenders 1982 1985 1982 1985 1982 1985 

Whites 22.48 22.10 11.01 11.42 24.40 24.07 

3,816 1,565 4,211 1,733 3,334 1,337 

African­ 9.45 8.31 6.20 5.74 17.80 20.20 

Americans 510 263 532 276 488 254 

Hispanics 9.54 8.43 7.26 10.75 19.25 17.66 

283 144 292 145 249 120 

Asian­ 6.43 6.04 11.60 

Americans 47 45 41 

Note: Percentages are weighted. Ns are unweighted. 

10 percent of African-American nonattenders. Almost 80 percent of Hispanics who visited art museums or galleries, but less than 20 percent of those 

who did not, wanted to go more often. 

The "more-more principle" also applied at the group level among nonattenders. That is, for each activity, except for Asian-Americans, nonattending members of the racial or ethnic group that attended most were also more 

likely than members of other groups to want to attend. For example, more 

59 
Race, Ethnicity, and Participation in the Arts 

than 20 percent of African-Americans who did not attend jazz concerts 

wanted to do so in both survey years. By contrast, fewer than 15 percent of 

nonattending whites wished to attend. With respect to the other activities, 

which whites were more likely to attend, white nonattenders were more 

likely than other nonattenders to report wanting to participate. 

For some activities, the differences were small. For example, in 1982, 14 

percent of whites who had not attended classical mu~sic concerts wanted to 

do so, compared with 10 percent of such African-Americans and 13 percent 

of Hispanic nonattenders. In other cases, the differences were more sizable. 

In 1982, 22 percent of nonattending whites, but fewer than 10 percent of 

nonattending African-Americans and Hispanics wished to go to stage plays 

or "the theater." 

Asian-Americans were the exception to the more-more principle. Although they participated in most activities at rates either higher or only 

slightly lower than those of white Americans, the percentages reporting a 

desire to attend each activity more were lower than those for all or most other 

groups. Whatever the reason, the gap between self-reported aspiration and 

actual participation was smaller for Asian-American respondents than for 

members of other groups. 

The tendency of nonattenders from groups with relatively high rates of 

attendance to want to attend more than those from groups with lower 

attendance rates can be interpreted in either of two ways. To the extent that 

members of these groups tend to socialize dispropc, rtionately with others 

from those groups, nonattenders in groups with high attendance rates may 

come into more frequent contact with attenders than do members of other 

groups. On the one hand, this contact may engender a greater desire to try 

the activity in question. On the other, it may engender guilt about nonparticipation, and consequently inflate what survey analysts refer to as "socialdesirability bias" in their responses. The latter possibility is one more reason 

to interpret these data with caution. 

How would rates of participation change if everyone did what he or she 

wanted? Let us take the responses at face value and t~reat them as indicators 

of genuine unsated demand for the activities about which respondents were 

asked. If each nonattender who said that he or she wanted to participate were 

to do so, how would differences in participation by race and ethnicity be 

affected? 

The answers are presented in Table 4-2. For each activity, each survey 

year, and each racial/ethnic group, data are presented on the percentage 

reporting participation in the prior year; the percentage who did not partici6O 
Racial/Ethnic Differences in Unsated Demand 

Table 4-2 

Real Attendance Rates, Potential Increments, and Total Potential 

Attendance by Race and Ethnicity
 

1982 Jazz 1985 

W A H W A H S 

Base 9,13 15,64 6,27 9.48 13,08 6,55 7,81 

Increment 12,30 20,31 12,13 13,22 19,38 18,02 6,24 

Potential 21,43 35,95 20.40 22.70 32.46 24,57 14.05 

1982 Classical 1985 

W A H W A H S 

Base 14.42 6.67 7.87 14.31 6.39 6.77 16.50 

Increment 12.22 9.65 11.65 11.45 7.32 5.23 4.42 

Potential 26.64 16.32 19.52 25.76 13.71 12.00 20.92 

1982 Opera 1985 

W A H W A H S 

Base 3.33 1,36 2,52 2.97 1.43 0.78 4,58 

Increment 6.93 4.81 4.70 8.25 3,37 4,76 1,89 

Potential 10.26 6,17 7.22 11.22 4,80 5.54 5,47 

1982 Musical 1985 

W A H W A H S 

Base 20.67 10.10 10.96 18.60 8.45 9.52 13.89 

Increment 21,68 14.70 14.46 20.20 13.61 9.31 12.06 

Potential 42.35 24.80 25.42 38.80 22.06 18.53 25.95 

1982 Plays 1985 

W A H W A H S 

Base 13.44 5,82 5.47 13.10 6.09 6.41 8.87 

Increment 19,46 8,90 9,02 19,20 7,80 7,89 5,86 

Potential 32.90 14,72 14,49 32.30 13,89 14.30 14.73 

1982 Ballet 1985 

W A H W A H S 

Base 4,64 1.78 4.54 4.72 2.14 3.21 6.22 

Increment 10.50 6.09 6.93 10.88 5.62 10.40 5.66 

Potential 15.14 7.87 11.47 15.60 7.76 13.61 11.88 

1982 Art 1985 

W A H W A H S 

Base 23.94 12.47 16.22 24.14 10.71 18.18 26.02 

Increment 18.56 15.58 16.12 18.26 18.04 14.45 8.58 

Potential 42.50 28.05 32.34 42.40 28.75 32.63 34.60 

Note: Base rates from Table 2-1. Increment=percentage of nonattenders who reported waning to 

participate times complement of base. A=African-American; S=Asian-American; H=Hispanic-American. 

61 
Race, Ethnicity, and Participation in the Arts 

pate but reported they wanted to; and the total "potentiial audience" comprising both groups. 

Potential participation rates, defined in this way, are much greater than 

the actual participation rates for all groups but Asian-Americans. Indeed, 

except for white attendance (in 1982 and 1985) and Hispanic attendance (in 

1985) at classical music concerts and white and ]Hispanic visits to art 

museums and galleries (in both years), potential rate~,; are at least twice the 

actual rates of attendance. In many cases, the differences are much greater 

than that. In other words, fewer people participated in these activities than 

did not but said they would like to do so. 

Because nonattending members of groups with high participation rates 

are more likely to report wanting to attend than are nonattending members 

of other groups, the first effect of everyone doing what he or she reports 

wanting to would be to widen the absolute intergroup percentage difference 

in participation rates. In the case of jazz, the absolute difference between 

African-American participation rates and those of whites and Hispanics 

would double. In the case of the other six activities, t]he absolute difference 

between white rates and those of African-Americans and Hispanics would 

increase. (Again, Asian-Americans are the exception to the rule. Although 

their real participation rates in classical music concert!~, opera, ballet, and art 

exhibits were higher than those for other groups, their potential participation 

rates were actually lower than those of whites for all of these and of 

Hispanics for opera attendance.) In other words, if all respondents did what 

they said they wanted to do, the absolute gap in participation rates between 

whites and everyone else would become wider. (The .exceptional activity is 

jazz, for which the gap between African-Americans and everyone else would 

widen.) 

In chapter 2, we focused not on absolute differences in rates but on the 

ratio of the white rate to rates for other groups. In other words, we asked how 

much more likely whites were than African-Americans or Hispanics to 

participate in these activities. When we put the question this way, our results 

are mixed. For most activities- and in 1982 for all activities but jazz and 

ballet -- the ratios of white to other potential attendance rates are lower than 

the ratios of white to other real attendance rates. For example, whites were 

more than twice as likely as African-Americans to attend musicals in 1982. 

If everyone who wanted had attended, they would have been only 1.71 times 

as likely. Similarly, whites were nearly 50 percent more likely to visit art 

galleries or museums than Hispanic-Americans in 1982. If everyone who 

wanted had attended, their advantage would have declined to approximately 

30 percent. 

62 
Racial/Ethnic Differences in Unsated Demand 

With respect to several activities, however, ratios between white and 

other groups’ potential participation rates are even higher than for real 

participation rates. This is true of the white/African-American ratios for 

opera attendance and theater-going in 1985 and of white/Hispanic ratios for 

opera and ballet attendance in 1982 and for classical music, musical theater, 

and straight theater attendance in 1985. For example, in 1985 white Americans were 2.04 times as likely as Hispanic-Americans to report theater 

attendance, whereas they were 2.26 times as likely to appear in the potential 

audience for stage plays. 

These results indicate that differences in participation in core activities 

do not result from barriers that disproportionately affect the ability of 

members of different groups from satisfying perceived demand. Instead they 

seem to reflect differences in the extent to which members of different racial 

and ethnic groups believe that they want to attend such arts events. For each 

of the seven activities about which they were asked (and with the notable 

exception of Asian-Americans), nonattenders of the groups whose members 

already participated at the highest rates were more likely than others to want 

to become participants. 

If African-American and Hispanic nonattenders had wanted to participate 

more than white nonattenders, this would have constituted strong evidence 

that intergroup differences reflected barriers to minority attendance and not 

differences in demand. Clearly these data do not point in that direction. It 

would be simplistic, however, to take these results as strong evidence that 

intergroup differences do not reflect differences in opportunity. 

First, the most effective barriers to participation may be those that 

influence demand, not those that influence the ability of persons to satisfy 

demand they already have. If, as the addiction theory mentioned at the 

beginning of this section suggests, taste for the arts is acquired through 

participation in the arts, then any barriers that prevent persons from participating in the arts are likely to be reflected in lower demand from the persons 

excluded.4 

Second, respondents to the SPPA "want-more" questions may have 

answered on the basis of pre-conscious understandings about the costs 

associated with getting more of what they wanted. If there are perceived 

higher costs to participation for minorities than for whites, differences in 

demand may reflect these costs. 

Third, it is possible, for the reasons discussed above, that social-desirability bias inflated the "want-more" responses of whites relative to those of 

African-Americans and Hispanics for those activities in which white Americans have the highest rates of participation. 
Race, Ethnicity, and Participation in the Arts 

These are all hypotheses that should lead us to avoid hasty conclusions 

on the basis of these findings, but should not lead us to dismiss them either. 

The results of these analyses indicate that it would be simple-minded to think 

about intergroup differences in arts attendance in the, same way we think 

about intergroup differences in education. In the case .of education, we have 

much evidence that demand is similar among racial and ethnic groups, with 

everyone viewing education as a good thing that helps people get ahead? In 

the case of the arts, the evidence presented here indicates that attendance at 

the live events about which people were asked is not desired equally by 

members of all groups. The evidence indicates that demand varies by group 

and that if there are barriers, they work in large part by influencing demand 

for live attendance. 

Why People Don’t Attend More 

Respondents who said they wanted to attend one of the seven core 

activities were given a list of possible reasons for not attending more than 

they did and were asked to check all those that applied. The reasons among 

which respondents could choose included: Tickets sold out, Cost, Not 

available, Feel uncomfortable, Don’t have anyone to go with, Babysitter 

problems/Must care for children, Problem related to a handicap, Problem 

related to age/health, Too far to go, Transportation[Traffic/Parking problems, Crime or fear of crime, Poor quality/Not very good, Prefer to watch 

TV, Don’t have time, Procrastination/Lack of motivation, and Other? To 

simplify the analyses we coded together "Problem related to a handicap" and 

"Problem related to age/health." Similarly, we coded together "Procrastination/Lack of motivation" and "Prefer to watch TV" because we regarded 

each of these as indicating exceptionally low levels of’ demand, so low as to 

suggest some inconsistency with the respondent’s professed desire to attend 

more. 

We present the results in two forms. Appendix Tables 4-1 through 4-7 

list, for African-Americans, Hispanics, and whites for 1982 and 1985, the 

weighted percentage of"want-more" attenders and "want-more" nonattenders in each group in each year giving each reason, along with the unweighted 

numbers of respondents upon which results for each group are based.7 Table 

4-3 summarizes the information for nonattenders who reported wanting to 

attend -- the group of most immediate interest here --- by listing for whites, 

African-Americans, and Hispanics in each year the three reasons given by 

the largest numbers of respondents and the percentages (of the nonattenders 

64 
Racial/Ethnic Differences in Unsated Demand 

who wished to attend) giving each response. (In the two cases in which more 

than 20 percent of such respondents marked a fourth reason, that one is 

reported as well.) 

These findings are suggestive at best. The results for African-Americans 

and Hispanic-Americans are based on very small numbers of respondents 

because these questions were asked during only some of the survey months 

and because relatively few nonattenders wished to become attenders,s Moreover, we find responses to these questions difficult to interpret. We can be 

reasonably certain that some of the reasons provided were hastily selected 

excuses offered under duress by respondents who may have expressed a 

casual wish to do something they had not done. We are certain that others 

reflect real barriers to attendance. There is no obvious way to tell the two 

apart. For example, some people who said they did not attend stage plays 

because they were given at sites too far away may have made no effort to 

find out whether plays were presented nearby. Others may have been 

suburbanites who think nothing of going downtown to visit a museum, but 

value stage plays less than other forms of recreation. Still others may live in 

rural areas of prairie states where the nearest theater is three hours away. 

Some respondents who gave "cost" or "don’t have enough time" as reasons 

may be destitute or work 70-hour weeks to support large families: that is, 

they may be people with little or no discretionary money or time. Others may 

have more discretionary income or time, but choose to spend it on other 

things. For the latter, "cost" or "time" responses tell us not just about barriers 

but about the value that respondents place on the arts relative to other uses 

of their time and money. Without either direct or plausible indirect measures 

of value that respondents place on attendance at the core activities, responses 

to the barrier questions are virtually uninterpretable. 

Nonetheless, if we assume that the underlying valuation of arts attendance is the same for all three groups and if we remember to treat the data 

as merely suggestive, the results are interesting2 For members of all groups, 

cost and lack of time were the most important reasons given for nonparticipation. With respect to most activities, white respondents were more likely 

to give time as a reason than cost, and Hispanic respondents were more likely 

to cite cost than time. In 1982, African-American respondents were somewhat more likely to mention cost than time for most activities, whereas in 

1985 they were somewhat more likely to cite time than cost. Lack of 

availability was frequently cited by whites, and a similar reason, that events 

were too far away, was often mentioned by Hispanics. African-American 

respondents frequently mentioned these and also cited transportation problems as impediments to attendance more than whites and, for most activities, 
Race, Ethnicity, and Participation in the Arts 

Table 4-3
 

Leading Reasons Given for Nonattendance
 

by Nonattenders Who Wished to Attend
 

Jazz, 1982 

W 

A 

H 

Jazz, 1985 

W 

A 

H 

Time (41), Cost (26), Not available (22!)
 

Cost (45), Time (24), Transportation (1!4)
 

Cost (40), Time (37), Not available (14)
 

Time (45), Cost (29), Not available (221)
 

Time (41), Cost (39), Not available (121)
 

Cost (55), Lack motivation (31), Time (,31), Child care (21)
 

Classical, 1982 

W Time (39), Cost (28), Not available (221) 

A Cost (44), Time (35), Transportation (;!1) 

H Cost (48), Time (33), Too far to go (20) 

Classical, 1985 

W Time (35), Cost (30), Too far to go (25), Not available (24) 

A Time (48), Cost (24), Transportation (~17) 

H Insufficient number of respondents 

Opera, 1982 

W Cost (35), Time (30), Not available (26)
 

A Cost (39), Time (30), Too far to go (12)
 

H Cost (68), Too far to go (36), Time (15)
 

Opera, 1985 

W Cost (37), Time (33), Too far to go (26;)
 

A Time (61), Transportation (30), Too far to go (14)
 

H Insufficient number of respondents
 

Musical theater, 1982 

W Time (37), Cost (31), Not available (211)
 

A Cost (47), Time (29), Lack motivation (12)
 

H Cost (37), Time (33), Too far to go (29)
 

Musical theater, 1985 

W Time (34), Cost (32), Too far to go (19)
 

A Cost (43), Time (26), Too far to go (15)
 

H Cost (53), Time (37), Child care (17)
 

66 
Racial/Ethnic Differences in Unsated Demand 

Table 4-3 (Continued)
 

Leading Reasons Given for Nonattendance
 

by Nonattenders Who Wished to Attend
 

Plays, 1982 

W Time (39), Cost (31), Too far to go (15) 

A Cost (24), Not available (20), Time (15) 

H Cost (44), Time (41), Lack motivation (12) 

Plays, 1985 

W Time (39), Cost (25), Not available (21)
 

A Time (39), Cost (38), Transportation (14)
 

H Cost (60), Time (51), Lack motivation (25)
 

Ballet, 1982 

W Time (32), Cost (29), Not available (27) 

A Cost (43), Time (33), Not available (14) 

H Cost (46), Time (26), Too far to go (20) 

Ballet, 1985 

W Time (35), Cost (33), Too far to go (22) 

A Time (51), Cost (37), Fear of crime (12) 

H Cost (44), Time (28), Too far to go (16) 

Art museums and galleries, 1982 

W Time (40), Not available (25), Too far to go (20)
 

A Time (31), Cost (23), Lack motivation (18)
 

H Time (47), Child care (15), Transportation (13)
 

Art museums and galleries, 1985 

W Time (39), Not available (24), Too far to go (21)
 

A Time (53), Transportation (19), Cost (17)
 

H Time (74), Lack motivation (34), Cost (30)
 

Note: Figures in parentheses are weighted percentages of those nonattending respondents who 

wanted to attend who reported a given reason for not attending. Data summarized from Appendix 

Tables 4-1 through 4-7. 

67
 
Race, Ethnicity, and Participation in the Arts 

more than Hispanics. For most activities, Hispanics were more likely than 

Afi’ican-Americans or whites to cite child care problems as reasons for not 

attending. Fear of crime, handicap or health problems, poor quality, publicity, work related reasons, or performance time did not loom large as reasons 

for many respondents in any group. 

In other words, whites tended to cite reasons indicative of an inadequate 

supply of activities more than members of other groups. By contrast, African-Americans and Hispanics were more likely than whites to mention 

problems like cost, transportation, and child care that are associated with 

insufficient financial resources. It follows from this that programs aimed at 

improving geographical access to the arts may disproportionately aid white 

Americans, whereas programs focused on financial access may be more 

likely to assist African-Americans and Hispanics. 

At the same time, however, most of these differences were either relatively weak or somewhat inconsistent from activity to activity or year to 

year. Overall, the reasons given by African-Americans, Hispanics, and 

whites who did not attend the core activities but would like to do so, were 

rather similar, and focused on cost, time, and availability. 

Conclusions 

Demand for participation in the seven core attend~mce activities appears 

to be cultivated by attendance. People who already attend are much more 

likely to want to attend more than are people who do not. Thus, although 

there is much apparent unsated demand for these activities, most of it comes 

from attenders rather than nonattenders. Because, with the exception of jazz 

performances, whites are more likely to attend than are African-Americans 

or Hispanics, unsated demand appears to be greater among whites than 

among members of these other two groups. 

If we look only at nonattenders, members of groups with higher attendance rates (African-Americans for jazz performance, whites for the other 

attendance activities) are more likely than others to say they want to attend. 

If we take professed desire for attendance at face value, then if all barriers to 

attendance were removed, the absolute differences in. percentage participation rates between the groups that participate most and those that participate 

least would increase. Because intergroup differences in desired participation 

among nonattenders are less, in most but not all case, s, than are intergroup 

differences in actual participation, the ratios of white .attendance to AfricanAmerican and Hispanic attendance, respectively, would decline somewhat 
Racial/Ethnic Differences in Unsated Demand 

for most, but not all, activities if everyone did what he or she said they 

wanted to do. 

Data on people’s reasons for not attending are difficult to interpret and 

the numbers of African-American and Hispanic respondents are small. This 

weak evidence suggests that white, African-American, and Hispanic wouldbe attenders are all deterred most frequently by cost, lack of time, and limited 

availability. At the same time, whites are somewhat more likely to mention 

reasons related to limited availability than are members of other groups, 

whereas African-American and Hispanic respondents are more likely to 

mention reasons related to cost. Because, except for jazz, white nonattenders 

were more likely to report wanting to attend the events about which they 

were asked than were African-Americans or Hispanic nonattenders, and 

because most intergroup differences were relatively small or inconsistent, 

the evidence does not indicate that eliminating income-related barriers 

would quickly or markedly erode intergroup differences in participation. 

These findings may seem inconsistent with some of the results presented 

in earlier chapters. For example, we noted earlier that the differences in rates 

of participation between whites, on the one hand, and Hispanics and African-Americans, on the other, were less for watching the arts on television 

than for live attendance. This led us to suggest that African-Americans and 

Hispanics might be deterred from live attendance at the core activities (other 

than jazz) by something other than taste. Yet the "want-more" questions 

failed to uncover greater unsated demand for live attendance (except for 

jazz) among these groups than among white Americans. 

One reason for this may be that live attendance at an arts event requires 

a greater degree of commitment than watching a similar event on television. 

A second reason may be that demand for live attendance is influenced more 

by attributes of the attendance experience than by attributes of a program 

itself. A third reason is that people may consciously or unconsciously take 

account of barriers that raise their cost of attendance in responding to 

questions about unsated demand. The SPPA data do not permit us to 

determine which, if any, of these explanations is correct. 

Our results may also seem at odds with the logistic regression analyses 

that showed that the difference in participation rates between HispanicAmericans and (non-Hispanic) white Americans was reduced to insignificance when differences among groups in sociodemographic factors were 

taken into account. If this were the case, would we not expect to see high 

levels of unsated demand, explained by economic barriers, among Hispanic 

Americans? 

Not necessarily. Our regression analyses indicated only that Hispanic­
Race, Ethnicity, and Participation in the Arts 

Americans were similar in their participation in the core activities to white 

Americans with similar sociodemographic characteristics. It seems likely, on 

the basis of the data we have analyzed, that sociodemographic barriers work 

not just by making it more difficult for people who want to participate to do 

so, but also by influencing the extent to which people want to participate. 

Our conclusions in this chapter have been general and laced with qualifications. We have relatively little confidence in the usefulness of the SPPA 

questions on the extent of and reasons for unsated demand for understanding 

intergroup differences in participation. Some of our reservations have to do 

with the small number of African-American, Hispanic, and Asian-American 

respondents upon which our analyses, especially of reasons for nonattendance, are based. We hope that future SPPAs will oversample AfricanAmerican, Hispanic, Asian, and Native American respondents so that more 

detailed analysis will be possible. 

Most of our reservations, however, have to do with the questions themselves, which seem to us to embody an unsophisticated view of human 

motivation. Although responses to these questions may be applicable to 

short-term marketing issues, we suspect that they tell us little about the 

complex processes that culminate in demand for attendance at arts events or 

about the long-term potential for increases in participation. 

7O
 
Chapter 5 

EVIDENCE ON RACIAL AND 

ETHNIC DIFFERENCES IN 

PARTICIPATION FROM THE 

NOVEMBER/DECEMBER 1982 

SUBSAMPLE 

Most of the analyses reported in Chapters 2 and 3 drew on data from 

all respondents to the 1982 and 1985 SPPAs. Because there were 

so many respondents, these analyses were statistically powerful, 

and permitted confident generalization. 

At the same time, because most of the SPPA questions were asked only 

in certain months, reliance on these prevented us from exploring relationships among answers to the full range of questions the surveys included. In 

this chapter, we take advantage of the survey’s breadth by using data 

collected in November and December 1982. In these months alone, respondents were asked all of the questions that appeared on the SPPA survey. 

There are two advantages to focusing on this subsample. First, we can 

go beyond the core items to examine participation in a broader range of 

artistic activities. We have already noted that intergroup differences vary for 

different kinds of arts participation. In this chapter we investigate such 

differences more thoroughly. 

Second, the November/December 1982 subsample permits us to explore 

the combined effects on participation of a broader range of explanatory 

variables by including them in the same models. In addition to the sociodemographic factors investigated in Chapter 3, in this chapter we consider the 

influence on participation of childhood experience (including both parental 

guidance and classes or lessons), musical taste, and viewing arts programs 

on television. 

These advantages bear a cost: the decline of statistical power associated 

71
 
Race, Ethnicity, and Participation in the Arts 

with the number of respondents being reduced from more than 15,000 to 

2,255. In particular, some of the following results are based on small 

numbers of African-American or Hispanic respondents. Thus, the effects of 

race or ethnicity must be larger than in analyses reported in earlier chapters 

if they are to reach statistical significance. Nonetheless, the sample size is 

sufficient to reveal intergroup differences that are substantively important. 

The November/December sample contained data on 2,255 respondents, 

of whom 1,908 were white, 230 were African-American, and 117 were of 

Hispanic origin,l (Respondents classified as "Other’" were not included in 

these analyses.) Table 5-1 compares probabilities of participation by race for 

November and December in the l0 core activities to those for the year as a 

whole. The Hispanic-Americans included in the November/December sample were much less likely to report attending classical music concerts, much 

more likely to report acting, singing, or dancing on stage, and somewhat 

more likely to report reading imaginative literature than the Hispanic sample 

for the year as a whole. African-American respondents for November/December were somewhat less likely to report having visited art exhibits or 

having read imaginative literature than their counterparts during the rest of 

the year. Attendance rates at classical music concerts, opera performances, 

plays, ballet performances, and art exhibits were lc, wer for all groups in 

November/December than in all of 1982. For the most part, however, 

differences in participation between African-Americ, ans, whites, and Hispanics are similar for the full and for the November/December samples. 

Measures 

The SPPA gathered many measures of artistic socialization and current 

participation. In Chapter 3, we focused exclusively on the core participation 

items. Because this chapter explores the full range of data available, economy of presentation dictates that we use scales -- omnibus measures comprising several similar items in a single variable. 

As we have seen, different kinds of participation are associated with race 

and ethnicity in different ways. To develop scales of arts participation, we 

applied a statistical method called factor analysis to the core participation 

and other participation variables described in Chapter 2. 

Factor analysis permits one to identify families of variables that are 

strongly associated with one another. In the case of the participation measures, it revealed the existence of four such clusters. (See Appendix Table 

5-1 .) 

72 
 

Evidence on Racial and Ethnic Differences 

Table 5-1
 

Percentage Participating in Core and Other Arts Activities by
 

Race/Ethnicity, November/December and Full 1982 Samples
 

Attend jazz Attend Attend opera Attend Attend 

concert classical concert performance musical play 

Full N/D Full N/D Full N/D Full N/D Full N/D 

White 9.1 8.8 14.4 11.7 3.3 1.5 20.7 19.7 13.4 11.6 

Afr.-Am. 15.6 16.9 6.7 5.0 1.4 0.5 10.1 8.6 5.8 4.9 

Hispanic 8.2 9.0 7.9 2.2 2.5 0.8 11.0 11.8 5.5 3.9 

Attend Visit art Perform on Perform: Read 

ballet exhibit musical act/sing/ fiction 

instrument dance 

Full N/D Full N/D Full N/D Full N/D Full N/D 

White 4.6 3.8 23.9 23.3 4.0 3.8 4.7 4.2 60.2 60.1 

Afr.-Am. 1.8 0.7 12.5 9.8 3.4 3.7 4.9 4.4 42.4 38.4 

Hispanic 4.5 2.8 16.2 15.9 3.1 4.6 2.9 7.8 36.5 42.5 

Note: Weighted percentage of group engaging in activity at least once during 12 months preceding 

survey. 

* Performing-Arts Attendance: The first six core participation measures, all involving attendance at performing-arts presentations, 

loaded together on a single factor. These included (in descending 

order of the strength of the relationship of each to the others) attending 

plays, attending ballet, attending musical theater, attending classical 

music performances, attending opera, and attending jazz performances. The resulting variable is an additive scale of the activities, 

ranging from 0 to 6. 

 ̄	 Exhibit Visiting: The core activity, visiting an art gallery or museum, 

combined with items on the "other participation" list, forms a second 

factor. The first four activities in this scale -- in descending order, 

visiting historic monuments, visiting art or craft fairs, visiting science 

or history museums, and visiting art exhibits -- all involved attendance at exhibitions. The fifth and sixth items, reading novels and 

other imaginative literature and doing needlecrafts, were anomalous, 

73 
Race, Ethnicity, and Participation in the Arts 

having in common only that they do not involve the performing arts. 

This additive scale ranges from 0 to 6. 

Performing-Arts Activities: A third factor consists of four activities, 

two from the core list and two from the "other participation" items, 

each of which involves producing, rather than consuming, performing-arts events. In descending order these activities, summed to an 

additive scale ranging from 0 to 4, are acting, singing or dancing on 

stage, playing a musical instrument in public or on stage, working on 

a theatrical set, and working on a musical set. 

Non-Performance Activities: A fourth factor comprises six activities 

involving the visual or literary arts, each oriented towards production 

rather than consumption. In descending order, these are painting or 

drawing; creative writing; taking art, writing, or music lessons; 

photography; crafts (other than needlecrafts); and reading or listening 

to poetry. The additive scale ranges from 0 to 6. 

These four scales represent four kinds of cultural participation, varying 

along two dimensions: performing arts versus visuall[y oriented arts (visual 

and plastic arts, historical exhibits, literature), and arts consumption versus 

arts production. 

The first scale includes jazz, which African-Americans attended more 

frequently than whites, along with five other activities that white respondents are more likely to attend than African-Americans. Because race thus 

affects different parts of the scale in different ways, cancelling one another 

out to a degree, we created a fifth scale by eliminating jazz from the 

performing-arts attendance activities. Results for the, attendance scales including and excluding jazz, respectively, are reported separately throughout. 

A focus of this chapter is on how participation in the arts during 

childhood (i.e., before age 18) may affect participation in the arts as an adult. 

We subjected the measures of parental guidance and childhood classes (see 

Chapter 2 for a description of these variables) to factor analysis (Appendix 

Table 5-2), from which emerged two scales: 

 ̄ Parental Guidance: A scale ranging from 0 to 4, consisting of the 

following items, in descending order: parents took child to plays or 

concerts; parents listened to classical music; parents took child to art 

museums; and parents encouraged child to read. 

 ̄ Childhood Lessons: A scale ranging from 0 to 8, consisting of items 

reporting lessons or classes before age 18 in the following areas, in 

descending order: visual-art production, art appreciation, writing, 

74 
Evidence on Racial and Ethnic Differences 

Table 5-2
 

Means for Artistic Socialization, Musical Taste, TV Art Viewing,
 

and Artistic Participation Scales by Race
 

N Parental Lessons Art music TV arts 

White 1,908 1.134 1.240 1.509 1.404 

Afr.-Arn. 230 0.860 0.864 0.720 1.082 

Hispanic 117 0.800 0.667 1.084 1.027 

N Attend Attend* Exhibits Perform Do other 

White 1,908 0.571 0.483 2.288 0.116 0.762 

Afr.-Am. 230 0.365 0.197 1.203 0.094 0.449 

Hispanic 117 0.305 0.214 1.597 0.166 0.708 

*Excluding attendance at jazz performances. Means are weighted, Ns are unweighted. 

music appreciation, crafts, acting, playing an instrument or singing, 

and ballet. 

Throughout this report, we have speculated about the extent to which 

differences in participation reflect, on the one hand, barriers to participation 

and, on the other, differences in taste. In this chapter, we use two rough 

proxies for taste or interest in "high culture." The first is based on the 

question that asked respondents which of the following kinds of music they 

like to listen to: classical/chamber, opera, operetta/Broadway/musical/show 

tunes, jazz, soul/blues/rhythm and blues, big band, country western, bluegrass, rock, mood/easy listening, folk, barbershop, and hymns/gospel. Factor 

analysis (Appendix Table 5-3) yielded three factors, of which classical/ 

chamber, operetta/show tunes, and opera were associated strongly with the 

first, along with (at lower levels) big band and mood/easy listening music. 

(Jazz appeared on a distinct factor with soul/blues and rock; and a third factor 

included bluegrass, country western, folk, barbershop, and hymns/gospel 

music.) From the components of the first factor, we constructed an additive 

scale, ranging in value from 0 to 5, which we call art music. 

A final additive scale is TV arts, ranging from 0 to 7, with 1 point for 

75 
Race, Ethnicity, and Participation in the Arts 

Table 5-3: Regression Analyses Predicting Scores on Parental
 

Guidance Scale
 

I.V. la lb 2a 2b 3a 

African-American -.073 

b 

-.092 

d 

-.073 

b 

-.099 

d 

.044 

a 

Hispanic -.071 

b 

-.078 

c 

-.076 

b 

-.085 

d 

.044 

a 

Female .119 

d 

.099 

d 

.116 

d 

Age -.114 

d 

-.156 

d 

.131 

d 

Father’s education .336 

d 

Mother’s education .276 

d 

d.f. 

R Squared 

1,750 

.008 

2,254 

.012 

1,750 

.033 

2,254 

.044 

1,750 

.271 

Note: Additive scale of number of kinds of family-based childhood artistic socialization activities respondents reported. Models labeled "a" are based on only those respondents for whom data on 

mother’s and father’s education were available. I.V.=lndependent variable. 

each kind of arts programming the respondent reported watching on television. Because such programs are available to most Americans free of charge, 

we regard this as a rough measure of interest in the arts, unaffected by 

barriers that may reduce attendance at live events or exhibitions. 

In addition to the measures described above, we use the same control 

variables introduced in Chapter 3, as well as three new ones. The latter 

include father’s educational attainment in years; mother’s educational attainment; and the number of hours the respondent reported watching television 

on an average day (Hours TV). Because data on father’s or mother’s 

education are missing for many cases, these variables are used only for 

analyses based on a special subsample. Hours of television is included as a 

control variable for analysis with TV arts. 

76 
Evidence on Racial and Ethnic Differences 

Intergroup Differences in Socialization, Taste, and 

Participation Scales 

Let us begin by considering intergroup differences in mean scores on the 

scales described above. (See Table 5-2.) Not surprisingly, the patterns mirror 

those noted in Chapter 2 with respect to the items of which these scales 

consist. White respondents reported more parental guidance experiences 

(1.13 compared to .86 and .80) than African-American or Hispanic respondents, respectively, as well as more kinds of classes or lessons (1.24) than 

African-Americans (.86) or, especially, Hispanic-Americans (.67). Whites 

reported liking more of the musical genres on the art music scale (1.51) than 

Hispanic (1.08) or, especially, African-American (.72) respondents. They 

also reported watching more kinds of televised arts programs (1.40) than 

African-American or Hispanic respondents (1.0g and 1.02). 

Whites also had higher scores than African-Americans and Hispanics on 

all the participation measures but performance activities. The differences 

were greatest with respect to the visually oriented consumption scale, for 

which the average for white respondents was 2.29, compared to 1.60 for 

Hispanic and 1.20 for African-Americans. Intergroup differences in other 

areas were more modest. Indeed, Hispanics participated in slightly more 

performance activities and almost as many nonperformance activities as 

whites. 

Although differences among groups are notable, especially with respect 

to consuming, rather than producing, art, even more striking is the modest 

degree of participation evident among any of these groups. Fewer than half 

the respondents from any group, for example, attended a performing-arts 

activity other than jazz, or participated in a performance, either onstage or 

backstage. Variation by race or ethnicity is limited, then, because whites, 

African-Americans, and Hispanic-Americans all reported low rates of participation. 

Race, Ethnicity, and Parental Guidance 

African-Americans and Hispanic-Americans report fewer parental-guidance experiences than do white Americans. Do these differences reflect 

differences in the degree to which African-American, Hispanic, and white 

parents value the arts? Or do they, instead, stem from differences in socioeconomic opportunity related to race or ethnicity? 

77 
Race, Ethnicity, and Participation in the Arts 

To answer this question, we used multiple regression analysis, a method 

that lets one estimate net effects of race and ethnicity while holding other 

potential causal factors constant. In other words, the resulting coefficients 

describe differences between African-Americans and whites and between 

Hispanics and whites who are similar with respect to the variables for which 

we have controlled. Table 5-3 reports results of analyses predicting scores 

on the parental guidance scale, and Table 5-4 reports results of the analyses 

for lessons taken during childhood. Independent variables are arrayed vertically to the left of the page. Their statistical effects appear on the fight, 

expressed as standardized coefficients, enabling us to compare the impacts 

of different predictors in a common metric. 

Each table reports results of three separate analyses or models, each 

containing different sets of variables. The pair of columns labelled 1 a and 1 b 

reports the influence of being African-American or Hispanic (as compared 

to white, the omitted category), without controlling for any other factors. As 

such, they are comparable to Table 5-2. The second pair of columns, 2a and 

2b, reports results of models that included controls for gender and age. The 

column labelled 3 is based on a model that included controls for parental 

education. 

The first two models (1 and 2) are reported in two columns because the 

analyses were executed twice: once on the full November/December sample 

and once on a partial subsample, consisting of 1,751 cases from November 

and December that contained data on mother’s and father’s education. The 

latter data are somewhat biased because respondents who could not report 

their parents’ educational level were disproportionately lower in socioeconomic status than the sample as a whole. On the other hand, the subsampie includes information that is vital for understanding family influences.2 

Columns 1 a and 1 b for tables 5-3 and 5-4 confirm that African-American 

and Hispanic respondents received significantly less childhood experience 

in the arts than their white counterparts. Columns 2a and 2b indicate that this 

difference remains constant (for parental guidance) or grows (for lessons and 

classes) after controlling for differences in gender composition and age 

among the three groups. 

The models reviewed thus far fail to take into account the fact that 

parents of African-Americans and Hispanic-Americans, on average, received considerably less formal education than parents of white Americans. 

When we control for mother’s and father’s education in model 3, two things 

become clear. First, parental education explains much more variation in 

parental guidance than does race or ethnicity. Second, African-American 

and Hispanic respondents received no less parental guidance than did white 

78 
 

 

Evidence on Racial and Ethnic Differences 

Table 5-4
 

Regression Analyses Predicting Scores
 

on Childhood Lessons Scale
 

I,V, la lb 2a 2b 3a 

African-American -.069 -.085 -.074 -.100 -.011 

b d c d 

Hispanic -.080 -.091 -.102 -.111 -.038 

c d d d 

Female .057 .051 .056 

a b b 

Age -.341 -.37! -.209 

d d d 

Father’s education .168 

d 

Mother’s education .159 

d 

d.f. 1,750 2,254 1,750 2,254 1,750 

R Squared .009 .013 .125 .151 .192 

Note: Additive scale of number of kinds of lessons or classes respondent reported taking before the 

age of 18. Models labeled "a" are based on only those respondents for whom data on mother’s and 

father’s education were available. 

Americans of equivalent age with similarly educated parents. Indeed, both 

African-American and Hispanic respondents reported that their parents gave 

them slightly, but significantly, more kinds of exposure or encouragement 

than did parents of whites. Parental education had less influence on classes 

or lessons, which include those for which the schools as well as those for 

which the family are responsible. Nonetheless, once one controls for mother’s and father’s years of schooling, the effects of race and ethnicity on 

lessons are no longer significant. 

79 
Race, Ethnicity, and Participation in the Arts 

Race, Ethnicity, Musical Taste, 

and Television Arts Viewing 

We have seen that Hispanic and, especially, African-American respondents reported liking fewer of the genres on the art-music scale than whites 

and viewed somewhat fewer kinds of televised arts programs. Do race and 

ethnicity exert an independent influence on taste for art music or interest in 

the watching of arts programs on television? Or do differences stem entirely 

from intergroup variation in characteristics like socioeconomic status or 

artistic socialization that are related to artistic tastes or interests? 

With respect to scores on the art-music scale (which includes big bands 

and easy listening as well as classical music, opera, and musical theater), 

being African-American, but not being Hispanic, makes a differences (see 

Table 5-5). Without controls, both African-Americans and Hispanics report 

liking significantly fewer of these musical styles than whites. Controlling for 

sociodemographic factors eliminates the difference between whites and 

Hispanics, and accounts for almost half the difference between AfricanAmericans and whites. Nonetheless, the remaining e, ffect of race indicates 

that African-American and white musical tastes are :significantly different. 

Controlling for childhood experience reduces the remaining African-American/white margin by only 14 percent, and the difference remains statistically 

significant. 

Race is not a major factor, however, compared to other significant 

predictors of differences in art-music scores. The effect of age, for example, 

is almost four times that of race, the influence of educational attainment 

almost three times as great, and the effects of parental guidance and childhood lessons twice as substantial. (See Appendix Table 5-5.) 

The small but significant tendency for African-Americans and Hispanics 

to report viewing fewer kinds of televised arts programs than whites is 

entirely the result of sociodemographic differences among these groups. In 

other words, if we take such viewing as a measure of interest in the arts, 

African-Americans and Hispanic-Americans display just as much interest as 

do whites who are similar in educational attainment, occupational status, 

income, and related characteristics.3 

Race, Ethnicity, and Artistic Participation 

In this section we consider effects of race and ethnicity on five scales of 

participation: attending performing-arts events (jazz included); attendance at 

performing-arts events (jazz excluded); visiting museums, fairs, or exhibits, 

80 
 

 

Evidence on Racial and Ethnic Differences 

Table 5-5
 

Effects of Race and Ethnicity on Art-Music Scale and Number of
 

Kinds of Televised Arts Programs Viewed
 

A~ music TVarts 

Model 2 3 1 2 3 

African­ -.179 -.093 -.080 -.057 .017 .028 

American d d d b 

Hispanic -.067 .001 .019 -.047 .009 .030 

b a 

Note: Standardized beta coefficients, a=p less than .05; b=p less than .01; c=p less than .001; d=p 

less than .0001. Model 1 includes no control variables. Model 2 includes controls for gender, age, 

educational attainment, occupation (white-collar v. other), family income, marital status (single or 

divorced v. other), and residence in SMSA. Model 3 includes same controls as model 2 as well as 

controls for parental guidance and childhood lessons. Based on 2,255-person sample from November/December 1982. 

reading literature and related activities; performing on stage or working 

backstage at performances; and producing visual, craft, or literary arts. 

Throughout this report we have emphasized that artistic participation is 

multi-dimensional. Because the participation scales used in this chapter vary 

along two dimensions (consuming/producing, performing arts/other arts), 

we can use them to pursue this point. The reader should remember, however, 

that even the broad array of activities included in the participation scales 

does not begin to exhaust the diversity of artistic activities in the contemporary United States. In particular, except for jazz, the SPPA did not ask people 

about art forms or activities with special links to African-American, Hispanic, or other American racial or ethnic minority communities. 

Absent controls for other variables (Table 5-6, model 1 under each 

participation heading), African-Americans reported participating in fewer 

items than white Americans on each scale except performance activities. 

Hispanic respondents reported fewer consumption activities than non-Hispanic whites, but not fewer production activities. None of the zero-order 

differences is very large, although the differences between African-Ameri81 
 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Table 5-6
 

Effects of Race and Ethnicity on Arts Participation Scales
 

Attend performances A~endpedormancesModel: 1 2 3 4 4 

African­ -.067 .015 .026 .031 -.107 -.022 -.013 -.006 

American b d 

Hispanic -.061 -.002 .012 .001 -.070 -.008 .004 -.007 

b c 

Visual consumption Performance activities 

Model: 4 

African- -.199 -.115 -.101 -.094 -.016 -.004 .003 .007 

American D d d d 

Hispanic -.088 -.024 -.004 -.016 .025 .038 .049 .045 

d a a 

Other activities 

Model: 1 2 3 4 

African- -.091 -.056 -.035 -.032 

American d b 

Hispanic -.011 .016 .043 .034 

a 

tSecond attendance scale does not include jazz. Note: Standardized beta coefficients, a=p less thar= 

.05; b=p less than .01 ;c=p less than .001 ;d=p less than .0001. Model 1 includes no control variables. 

Model 2 includes controls for gender, age, educational attainment, occupation (white-collar v. other), 

family income, marital status (single or divorced v. other), and residence in SMSA. Model 3 include,,; 

same controls as model 2 as well as controls for parental guidance and childhood lessons. Model 4 

includes same controls as model 3 as well as controls for art-music scale, TV arts viewing, and hour,,; 

spent watching all kinds of television on average day. Based on 2,255-person sample from November/December 1982. 

82 
Evidence on Racial and Ethnic Differences 

cans and whites with respect to visually oriented consumption activities and, 

to a lesser extent, attending performances (excluding jazz) are moderate. 

When sociodemographic controls are entered into the predictive equations (model 2), the negative coefficients of being African-American on 

performance attendance disappear (with jazz included) or become insignificant (with jazz excluded). Controlling for such factors as educational attainment, family income, having a white-collar occupation, and marital status 

eliminates all of the differences between African-Americans and whites on 

the performance-attendance scale that includes jazz, and almost 80 percent 

of the difference on the scale excluding jazz. Sociodemographic controls 

also reduce the effect of race on visually oriented consumption activities by 

more than 40 percent, and on visual-art, craft, and literary activities by 

almost as much, but the differences between whites and African-Americans 

remain statistically significant in these areas. 

Sociodemographic differences account for almost all of the difference 

between whites and Hispanics in performance attendance and more than 70 

percent of the gap in the exhibit-visiting scale. When these characteristics 

are taken into account, being Hispanic has no significant influence on any 

form of participation. 

The third model adds controls for childhood experience (both parental 

guidance and lessons and classes) to the sociodemographic measures. These 

additional controls reduce the remaining effect of being African-American 

on visiting exhibits by only 12 percent, leaving a small but statistically 

significant difference between otherwise similar African-Americans and 

whites. They reduce the African-American coefficient for nonperformance 

creative activities by almost 40 percent, to nonsignificance. 

Although the impact of being African-American on visiting exhibits is 

statistically significant, it is small relative to the influence of other predictors. For example, it is less than half the size of the effects of educational 

attainment, gender, and parental socialization, and well below the influence 

of lessons and classes during youth? 

We have already seen that whenever Hispanics had significantly lower 

scores on participation scales than whites, these differences were almost 

entirely the consequence of intergroup sociodemographic differences. With 

respect to the consumption scales- performance attendance and visually 

oriented activities -- controlling for childhood experience makes no notable 

difference. With respect to the art-producing activities, both performance 

and nonperformance, when one controls for childhood experience in the arts, 

Hispanic Americans are involved in slightly, but significantly, more activities than are whites. In other words, Hispanic respondents reported partici83 
Race, Ethnicity, and Participation in the Arts 

pating in more artistic production activities than did white or African-American respondents of similar socioeconomic status and with comparable socialization into the arts. 

With respect to nonperformance activities, the positive effect of being 

Hispanic is small relative to that of other predictors: about one-eighth as large 

as childhood lessons, less than one-third the effect of home socialization, less 

than half the size of educational attainment, and smaller than the effect of age, 

income, marital status, having a white-collar occupation, and living in an 

SMSA. By contrast, the coefficient for Hispanic origint, although small, is one 

of only four significant predictors of onstage or offstage performance activities, and the largest demographic predictor other than income. 

The fourth model we investigated added three new control variables: the 

art-music scale, the TV arts viewing scale, and a measure of hours watched 

per day of all kinds of television. These additional controls did not materially 

alter the results of the earlier models, except insofar as they reduced the 

coefficient for being Hispanic as a predictor of participation in nonperformance production activities to insignificance. What this means is that more 

than one-fifth of the advantage associated with being Hispanic in nonperformance production ("other activities") results from Hispanic respondents 

having musical tastes and viewing habits associated with this kind of participation. 

Summary of Findings Thus Far 

The analyses reported above clarify certain issues raised in earlier chapters. In Chapter 2, we saw that African-American and Hispanic respondents 

received fewer forms of parental guidance in reading and the fine arts and 

took fewer arts-related classes or lessons at an early age than did whites. In 

this chapter, we have seen that these differences are entirely a result of the 

fact that African-American and Hispanic respondents had parents who had 

received fewer years of formal education than had the parents of white 

respondents. Controlling for parental education, African-American and His-. 

panic parents gave their children significantly more parental guidance expe-. 

riences than did comparable white parents. To the extent that the way one 

socializes one’s children reflects the value one places on the arts, then 

African-American and Hispanic families appear to value the arts (and read-. 

ing) as much as comparable white families. 

In Chapters 2 and 3 we raised the question of whether differences in. 

participation between whites on the one hand, and African-Americans and 

84 
Evidence on Racial and Ethnic Differences 

Hispanics on the other, resulted from differences in opportunity or from 

differences in taste. In this chapter we have looked at two proxy indicators 

of taste for the fine arts. The first, a scale of the number of kinds of art music 

and related genres respondents said they enjoyed, is a fairly direct indicator 

of a narrow spectrum of taste. The second, a scale of the number of kinds of 

arts programs respondents reported viewing on television, is a more indirect 

indicator of interest in a broader range of the arts. 

If we treat television viewing of the arts as an indicator of interest in the 

arts, then we see that African-American and Hispanic-Americans are no less 

interested in the arts than are white Americans of similar socioeconomic 

status. The same is true of taste for classical and related forms of music for 

Hispanic-Americans. By contrast, African-Americans do report liking fewer 

kinds of art music (but recall that this scale includes big band, Broadway, 

and easy listening music, as well as classical) than whites, and only about 

half of the difference is explained by sociodemographic characteristics. 

However, the results reported in Table 5-6 for model 4 indicate that this 

small difference in taste cannot explain interracial differences in any of the 

arts participation scales. 

Whereas most of the core questions examined in Chapter 3 concerned 

attendance at live, high-culture, performing arts events, use of the "other 

participation" items in constructing the participation scales permitted us to 

distinguish among the determinants of different kinds of participation. The 

analyses further confirmed that one cannot generalize about the effects of 

race or ethnicity on cultural participation per se. Hispanic Americans attended fewer public arts activities than whites, but this difference is almost 

entirely the result of the fact that white Americans have more formal 

education, higher incomes, and higher status occupations. When these factors are controlled, Hispanic-Americans participate in active art-making 

activities significantly more than do white Americans. 

African-American/white differences in participation also vary for different kinds of activities. There is no statistically significant difference between 

African-American and white respondents with respect to participating onstage or backstage in performing-arts events. And the significant difference 

between African-Americans and white Americans in the number of kinds of 

performing-arts events attended stems almost entirely from differences between African-Americans and whites in sociodemographic characteristics 

other than race? Significant, although relatively small, differences between 

white and African-American respondents who are similar in sociodemographic profile did appear with respect to the scales measuring visually 

oriented consumption activities and in the nonperformance creative activity 

85 
Race, Ethnicity, and Participation in the Arts 

scale. The latter difference was attributable to differences between AfricanAmericans and whites in childhood experience, whereas the former persisted 

even after controls for childhood experience, musical taste, and televised arts 

viewing were entered into the model. 

One advantage of multiple regression analysis over logistic regression 

analysis (the method used in Chapter 3) is that it enables one to compare the 

relative influence of different predictive factors using a common metric. The 

analyses reported above indicate that even in those relatively few cases in 

which race or ethnicity affect artistic outcomes after controlling for intergroup sociodemographic differences, those effects are usually dwarfed by 

those of childhood experience and educational attainment, and exceeded by 

other measures of socioeconomic status. 

In other words, at least for the range of participation measures about 

which the SPPA surveys asked, most differences ~Lmong white, AfricanAmerican, and Hispanic respondents result from differences in the sociodemographic attributes of members of these groups. Where differences in 

participation other than those for which such factors account are found, they 

vary among kinds of participation. African-Americans report receiving more 

kinds of parental guidance into the arts, like art music and related genres less 

(but like jazz more), visit fewer kinds of public exhibitions, and engage in 

fewer arts, crafts, and literary creative activities than ’whites who are comparable with respect to sociodemographic characteristics. Hispanic-Americans 

report benefitting from more kinds of parental guidance and participate in 

more active art-producing activities (both performance and nonperformance) than white Americans who are comparable sociodemographically and 

with respect to childhood experience. Such net differences, where they are 

present, are in most cases small relative to other predictors. 

Differences in Models Predicting Artistic
 

Socialization, Taste, and Participation by Race
 

Do the same factors predict outcomes for African.-Americans, Hispanics,. 

and whites, or do members of these groups follow separate paths to artistic: 

participation? Differences in the predictors of participation are relevant both 

to understanding intergroup differences in the extent of participation and to 

evaluating the likely effects of programs and policies aimed at reducing such 

differences. 

In this section we investigate differences in the predictors of socializa-­

tion, taste, and participation by applying the same predictive models 

described in the previous section (excluding the dichotomous African-­

86 
Evidence on Racial and Ethnic Differences 

American and Hispanic variables, of course) separately to respondents from 

each group. For the childhood experience variables (parental guidance and 

childhood lessons) these analyses employ the subsample with data on 

mother’s and father’s educational attainment and also include gender and 

age. For art music and TV arts viewing, the full November/December 

subsample is used for two separate models: with sociodemographic predictors, and with both sociodemographic and socialization variables included. 

For the participation scales (attending performances with and without jazz, 

visiting exhibits, performance activities, and nonperformance activities), 

three models are run using the full November/December subsample: with 

sociodemographic predictors only; with sociodemographic and childhood 

experience independent variables; and with sociodemographic, childhood 

socialization, and taste proxy measures all included. 

Table 5-7 reports all instances where predictors for two or more groups 

are significantly different across comparable models. (The full models are 

reported in Appendix Tables 5-13 through 5-20.) Most significant differences are between whites and African-Americans or between whites and 

Hispanics. In part, this is an artifact of sample size. Because the number of 

white respondents is much greater than the number of African-American or 

Hispanic respondents, differences between whites and other groups are more 

likely to be statistically significant than gaps between Hispanics and African-Americans. 

Childhood experience. There were no significant intergroup differences in 

the predictors of childhood classes and lessons. By contrast, once parental 

education was controlled, age was a significantly positive predictor of 

parental guidance for whites but a significantly negative predictor for African-Americans. What this means is that whereas white parents of equivalent 

educational levels have been providing fewer kinds of parental guidance over 

the lifetimes of our respondents, comparable African-American parents have 

been providing more kinds of guidance over that same time span. This trend, 

along with increases in educational attainment among African-Americans, 

might be expected to moderate or eliminate African-American/white differences in family guidance. 

Taste/interest proxies. Older white respondents watched significantly more 

kinds of televised arts programs and reported liking significantly more kinds 

of art music, other things equal, than younger whites. By contrast, older 

African-American and Hispanic respondents were no more likely than otherwise comparable younger ones to have high scores on these scales. Significant 

87 
Race, Ethnicity, and Participation in the Arts 

Table 5-7
 

Significant Differences in Models Predicting Scores on Artistic
 

Socialization, Taste, and Participation Scales for African-


American, Hispanic, and White Subsamples
 

SCALE PREDICTOR 

Parental AGE Significantly positive for whites, negative for Africanguidance Americans, controlling for gender and parental 

education 

Childhood None 

lessons 

TV arts viewing AGE Significantly positive for whites, only slightly positive for 

African-Americans with sociodemographic controls 

EDUCATION Significantly positive for both whites and AfricanAmericans, but effect for whites significantly stronger, 

with sociodemographic controls 

Art music AGE Significantly positive effect for whites, insignificant 

weak effects for African-Americans and Hispanics, both 

with sociodemographic controls only and with sociodemographic and socialization controls. 

EDUCATION With sociodemographic controls, strongly significant for 

whites, significant but less so for African-Americans; 

with socialization controls, still strongly significant for 

whites, insignificant for African-Americans 

Performance EDUCATION More strongly significant for whites than for Africanattendance Americans with sociodemographic control only; insignifiinc, jazz cant for Hispanics with sociodemographic controls and 

negative for Hispanics with additional controls 

Performance EDUCATION More strongly significant for whites than for Africanattendance Americans with sociodemographic and socialization 

exc, jazz controls; insignificant for Hispanics with sociodemographic controls and negative with other controls 

SMSA Significantly positive for whites, negative for AfricanAmericans with sociodemographic controls; negative 

and significant for African-Americans, insignificant for 

whites with sociodemographic and socialization controls 

88 
Evidence on Racial and Ethnic Differences 

Table 5-7 (Continued)
 

Significant Differences in Models Predicting Scores on Artistic
 

Socialization, Taste, and Participation Scales for African-


Americans, Hispanic, and White Subsamples
 

SCALE PREDICTOR 

Exhibition EDUCATION 

visiting 

OCCUPATION 

(white collar) 

GENDER (female) 

PARENTAL 

TV ARTS 

Performance INCOME 

activity 

Nonperformance AGE 

activity 

EDUCATION 

OCCUPATION 

(white collar) 

PARENTAL 

SOCIALIZATION 

TV ARTS 

VIEWING 

Strongly significant for whites, all models; for AfricanAmericans, more weakly significant with sociodemographic controls, insignificant with other controls 

More significantly positive for African-Americans than 

for whites with sociodemographic controls; significantly 

positive for Hispanics, insignificant for whites, with sociodemographic, socialization, and taste controls 

Significantly positive for whites, insignificant for Hispanics, all models 

More significantly positive for African-Americans than 

for whites, all models 

More significantly positive for Hispanics than for whites 

Significantly negative for whites, all models; significantly positive for Hispanics with sociodemographic 

and with sociodemographic and socialization controls, 

and positive but insignificant with all controls 

Significantly negative for whites, positive for AfricanAmericans, with all controls 

More significantly positive for whites than for AfricanAmericans with sociodemographic controls 

Significantly positive for African-Americans, all models; 

significantly but less positive for whites, models with sociodemographic and with sociodemographic and socialization controls, insignificant in model with all controls 

Significantly positive for Hispanics but not for AfricanAmericans, model with socialization controls 

Significantly positive for Hispanics, less significantly 

positive for whites, not significant for African-Americans 

Note: For full models, see Appendix Tables 5-11 through 5-17, 

89 
Race, Ethnicity, and Participation in the Arts 

differences in the effects of age for whites as compared, to African-Americans 

(for art music and TV arts viewing) and Hispanics (for art music) suggest the 

possibility of a convergence in musical taste and interest in the arts. Although 

these differences may simply represent an absence of aging effects in the 

minority subpopulations, they may instead reflect cohort change in the 

African-American and Hispanic communities. One other intergroup difference was evident. Educational attainment was more strongly and positively 

predictive of TV arts viewing and liking for art music and related genres for 

white than for African-American respondents. 

Participation Scales. The most notable intergroup difference was that educational attainment was more strongly related for whites than for AfricanAmericans to performing-arts attendance (both including and excluding 

jazz), exhibition attendance and related activities, and nonperformance creative activities. In most cases, the effect of education was significant for 

African-Americans as well as for whites, but smaller in magnitude. A similar 

paltem appeared in the difference between white and Hispanic respondents 

in effects of education on attending the performing arts (both including and 

excluding jazz), but not on the other participation scales. 

In other words, to use the language of economics, returns to investments 

in education in the form of increased participation in a range of artistic 

activities are larger for whites than for African-Americans or Hispanics. One 

possible explanation for such a finding is that African-American respondents 

may have received different kinds of education than white respondents. If, 

for example, African-Americans were more likely to go to high schools 

where the arts were not stressed, to take vocational rather than college 

preparatory courses, to attend community colleges rather than liberal arts 

colleges, or to major in technical or business subjects rather than in the 

humanities, any of these factors might account for the differences in the 

effects of education. 

By contrast, the effects of having a white-collar occupation on nonperformance consumption and production activities were larger for AfricanAmericans than for whites, as they were on visiting exhibitions and related 

activities for Hispanics. In other words, there is some, evidence that, at least 

with respect to nonperformance items, occupation plays a more important 

role in determining the participation of African-Americans and Hispanics 

than of whites, whereas education is more important in determining participation levels of whites than of African-Americans and Hispanics. 

Other intergroup differences in the effects of sociodemographic factors 

were each restricted to just one form of participation in the arts. Living in an 

9O 
Evidence on Racial and Ethnic Differences 

SMSA had a positive effect on performing-arts attendance (excluding jazz) 

for white respondents, but a negative influence on attendance for AfricanAmericans. Other things being equal, white women were more likely to visit 

museums and exhibits than white men, but no such gender differences 

appeared for Hispanics. Family income was positively related to onstage and 

backstage performance activities for Hispanic respondents, but negatively 

related to such activities for whites. Consistent with findings described in 

Chapter 3, the gap in participation between women and men was greater 

among whites than among African-Americans for all the scales, but unlike 

those analyses, the differences never reached statistical significance. 

In general, the effects of childhood socialization on participation scores 

were weaker, although still significant, for whites than for members of other 

groups. The only difference between groups that was significant, however, 

was for visually oriented consumption activities, where parental guidance 

exerted a significantly stronger impact on participation by African-Americans respondents than on that of whites. 

In Chapter 2, we noted that differences between African-Americans and 

whites with respect to taking classes or lessons in the arts were relatively 

small, compared to differences in participation in the core activities, and 

speculated about the efficacy of the schools in increasing equality of opportunity for participation in the arts. Except for the performance attendance 

scale that included jazz, the effects of lessons or classes in the arts were 

smaller for African-Americans than for whites or Hispanics. This finding is 

consistent with the weaker effects of educational attainment on participation 

for African-Americans than for whites, and may indicate either that AfricanAmericans took different kinds of classes or lessons than members of other 

groups or that, for some other reason, classes or lessons were less effective 

in stimulating adult activity among African-Americans than among other 

respondents. On the other hand, these differences, although pervasive, never 

reached statistical significance, so, at most, they suggest hypotheses for 

further research. 

In Chapter 2, we also noted the smaller differences in patterns of 

watching the arts on television than in patterns of live attendance between 

white Americans, on the one hand, and African-Americans and HispanicAmericans, on the other, and speculated as to whether television might be a 

force for increasing minority participation in the arts. For Hispanic respondents, this hypothesis seems to be a credible one: watching televised arts 

programs is significantly related to each of the participation scales, even after 

controlling for sociodemographic factors, childhood experience measures, 

taste for art music, and amount of television viewing of all kinds. For each 

91 
Race, Ethnicity, and Participation in the Arts 

scale, the impact of viewing the arts on television is greater for Hispanics 

than for any other group, and for the nonperformance scales, both visually 

oriented consumption and nonperformance production activities, the relationship is significantly stronger for Hispanic respondents than for AfricanAmericans. By contrast, for African-Americans, viewing the arts on 

television has a weaker effect on each of the participation scales than for 

whites or for Hispanics, and is a significant predictor only of the performance attendance scales. The effects of TV arts viewing on participation for 

whites is intermediate between that for Hispanics and African-Americans for 

each kind of participation. 

What can we make of these differences? One possibility is that televised 

arts programs boost arts participation among Hispanic-Americans more than 

among African-Americans or whites. A plausible alternative explanation is 

that participating in the arts as consumers or producers makes Hispanics 

want to watch arts programs on television more than it does African-Americans or whites. Or, viewing arts programs may simply be a better proxy 

measure of interest in the arts for Hispanics than for members of other 

groups. These possibilities can at best serve as hypotheses for further 

research, especially given the fact that only two of the intergroup differences 

are statistically significant. 

Taken together, however, the findings suggest an intriguing and potentially important hypothesis: the links between childhood classes and lessons 

(but not parental guidance), formal education, televised arts viewing, and 

artistic participation may be weaker among African-Americans than for the 

Hispanic or white subpopulations. Whether this conclusion would survive 

replication, given the statistical insignificance of many of the results, is 

uncertain. If the hypotheses are confirmed, it remains to be seen whether 

the differences result from differences in the kinds of education AfricanAmericans and other Americans receive, the kinds of classes they take, and 

the kinds of arts programs they watch; or from aspects of the African-American experience that blunt the impact of education on artistic interests and 

behavior. 

Do Intergroup Differences Vary by Gender, 

Educational Attainment, or Age? 

Table 5-8 displays means by race for subsamples based on differences 

among respondents in educational attainment, gender, and age. The educational attainment categories are less than high school, high school graduation 

92 
Evidence on Racial and Ethnic Differences 

Table 5-8 

Means and Standard Deviations for Regression Variables 

by Race by Education, Gender, Age m Including 

Respondents without Data or Parental Education 

Art Attend 

Lessons Home music Attend Visit no jazz Perform Oovis TV arts 

EDUCATION 

11 & Less 

White 447 0.528 0.550 0.894 0.148 1.065 0.129 0.079 0.276 0.660 

1.054 0.674 1.195 0.482 1.203 0.447 0.346 0.692 1.333 

AfricanAmerican 106 0.318 

0.752 

0.516 

0.659 

0.316 

0.927 

0.115 

0.319 

0.467 

0,812 

0.058 

0.233 

0.023 

0.149 

0.143 

0.452 

0.668 

1.386 

Hispanic 54 0.290 

0.810 

0.626 

0.919 

0.886 

1.272 

0.161 

0.368 

0,966 

1.331 

0.088 

0.284 

0.152 

0.496 

0.494 

0.927 

0.806 

1.681 

12 Years 

White 801 1.187 

1.312 

1,027 

0.870 

1.368 

1.287 

0.387 

0.785 

2.275 

1.630 

0.323 

0.696 

0.082 

0.341 

0.694 

1.025 

1,260 

1.689 

AfricanAmerican 

80 1.272 

1.557 

0.990 

0.824 

0.872 

1.168 

0.304 

0,549 

1.400 

1.586 

0.084 

0.337 

0.181 

0.502 

0.469 

0.874 

1.200 

1.498 

Hispanic 38 1.093 

1.297 

0.804 

0.650 

1.239 

1.062 

0.332 

0.738 

1,959 

1.653 

0.264 

0.553 

0.244 

0.642 

0.781 

1.317 

0.955 

1.455 

13-15 Years 

White 342 1.758 

1.580 

1.558 

0.963 

1.833 

1.490 

0.837 

1.169 

2.779 

1.674 

0.700 

1.023 

0.166 

0.536 

1.044 

1.297 

1.676 

1.847 

AfricanAmerican 28 1.082 

1.206 

1.285 

0.855 

1.088 

1.384 

0.673 

0.906 

1.993 

1.688 

0.432 

0.735 

0.111 

0.400 

0.910 

1.102 

1.299 

1.528 

Hispanic 20 0.714 

0.760 

1.209 

0.589 

1.344 

1.202 

0.605 

1.209 

2.347 

1.316 

0,460 

0,896 

0.101 

0.301 

1.069 

1.412 

1.687 

1.732 

16 & Over 

White 318 1.781 

1.510 

1.738 

1.025 

2.339 

1.427 

1.308 

1.345 

3.457 

1.596 

1.120 

1.196 

0.194 

0.618 

1.286 

1.305 

2.471 

2.103 

African

American 

- 16 1.649 

1.566 

1,438 

0.940 

1.625 

1.371 

1.474 

1.534 

3.001 

1.575 

1.046 

1.137 

0.067 

0.249 

1.242 

1,119 

2.471 

2.286 

Hispanic 1,292 

1.179 

0.987 

0.458 

1.022 

1.602 

0.432 

0.823 

2.602 

2.220 

0,216 

0.411 

0.000 

0.000 

1.008 

1.256 

1.271 

1.993 

93
 
 

Race, Ethnicity, and Participation in the Arts 

Table 5-8 (Continued) 

Means and Standard Deviations for Regression Variables 

by Race by Education, Gender, Age-- Including 

Respondents without Data or Parental Education 

N Lessons Home 

Art 

music Attend Visit 

Atten,:l 

no jazz Perform Dovis TV arts 

GENDER 

Male 

White 860 1.177 

1.344 

1.033 

0.896 

1.357 

1.349 

0.475 

0.906 

1.839 

1.594 

0.389 

0.787 

0.094 

0.399 

0.688 

1.075 

1.319 

1.770 

AfricanAmerican 

92 0.921 

1.450 

0.783 

0.823 

0.652 

1.217 

0.361 

0.754 

0.890 

1.249 

0.1613 

0.511 

0.090 

0.341 

0.450 

0.855 

1.055 

1.621 

Hispanic 56 0.631 

1.020 

0.817 

0.722 

0.994 

1.069 

0.241 

0.692 

1.473 

1.351 

0.161 

0.496 

0.134 

0.469 

0.742 

1.223 

1.085 

1.593 

Female 

White 48 1.296 

1.494 

1.225 

1.029 

1.645 

1.459 

0.657 

1.096 

2.690 

1.756 

0.567 

0.974 

0.135 

0.477 

0.828 

1.162 

1.480 

1.864 

AfricanAmerican 138 0.818 

1.199 

0.922 

0.847 

0.776 

1.171 

0.369 

0.780 

1.457 

1.684 

0220 

0.60:3 

0.097 

0.375 

0.447 

0.864 

1.104 

1.599 

Hispanic 61 0.703 

1.120 

0.783 

0.870 

1.175 

1.368 

0.368 

0.778 

1.723 

1.824 

0.2613 

0.590 

0.197 

0.556 

0.675 

1.156 

0.968 

1.738 

AGE 

18-30 

White 605 1.915 

1,653 

1,288 

0.921 

1.023 

1.113 

0.528 

0.982 

2.511 

1.712 

0,401 

0.811 

0.136 

0.467 

1.142 

1.349 

1.134 

1.535 

AfricanAmerican 80 1.454 

1.515 

1,018 

0.799 

0.680 

1.099 

0,544 

0.809 

1.606 

1.609 

0.197 

0.555 

0.140 

0.465 

0,600 

0.969 

1,310 

1.661 

Hispanic 44 1.058 

1.268 

0.917 

0.589 

1.229 

1.145 

0.282 

0.765 

1.874 

1.621 

0.196 

0.549 

0.248 

0.629 

t.167 

1.469 

1.177 

1.630 

31-51 

White 647 1,192 

1,303 

1.129 

0.965 

1.751 

1.468 

0.693 

1.082 

2.517 

1.696 

0.595 

0.962 

0,148 

0.519 

0.789 

1,082 

1,547 

1,877 

AfricanAmerican 74 0.737 

1.238 

0,950 

0.909 

0.964 

1.340 

0,312 

0.769 

1,244 

1.611 

0,223 

0.589 

0.078 

0.267 

0.506 

0.913 

1.044 

1.517 

Hispanic 47 0.481 

0.811 

0.794 

0,806 

1.019 

1.251 

0.386 

0.817 

1.701 

1.709 

0.287 

0.629 

0.062 

0.318 

0.494 

0.955 

0.989 

1.645 

94 
 

Evidence on Racial and Ethnic Differences 

Table 5-8 (Continued) 

Means and Standard Deviations for Regression Variables 

by Race by Education, Gender, Age m Including 

Respondents without Data or Parental Education 

N Lessons Home 

Art 

music Attend Visit no j

Attend 

azz Perform Dovis TV arts 

Over 51 

White 656 0,660 

0.979 

0.996 

1,007 

1.717 

1.498 

0.488 

0,961 

1.852 

1.710 

0.446 

0.888 

0.065 

0.313 

0,382 

0.746 

1.511 

1.978 

AfricanAmerican 78 0.208 

0.543 

0.535 

0.706 

0.484 

1.069 

0.184 

0.648 

0.604 

1.062 

0.165 

0.544 

0.050 

0.276 

0.172 

0.492 

0.815 

1.599 

Hispanic 26 0,309 

0.872 

0.603 

1.037 

0.945 

1.309 

0.197 

0.475 

0.914 

1.135 

0.115 

0.319 

0.209 

0.548 

0.283 

0.618 

0.828 

1.752 

but no further education, some college, and at least college graduation. Age 

categories were derived by dividing the population into three groups of 

similar size: 18 to 30, 31 to 51, and older than 51 years of age. 

The educational means must be interpreted with caution, because only 

16 African-American respondents and only 5 Hispanic respondents in the 

November/December sample had 16 or more years of formal education, and 

only 28 African-Americans and 20 Hispanics had attended college for 1 to 

3 years. Differences in means between African-American and white respondents were smaller (expressed as ratios) among college graduates than 

among other groups with respect to taste for art music, performing-arts 

attendance, museum and exhibition visiting, and nonperformance creative 

activities. By contrast, the gaps between Hispanics and whites in participation (again, expressed in ratios) tended to be greater among the more highly 

educated. For example, Hispanics without high-school degrees had higher 

means than their non-Hispanic white counterparts on performing-arts attendance (including jazz), watching arts television, and participating in performance and nonperformance production activities. 

Comparisons of intergroup differences by age are also complicated by 

small subsample sizes. Nonetheless, the results are striking (see Table 5-9). 

Comparing mean scores of respondents 52 years of age or over, 31 to 51 

years old, and 18 to 30 years of age, we see that the ratio of white to 

African-American participation rises monotonically with age for lessons and 

classes, art music, televised arts viewing, performing-arts attendance (in95 
Race, Ethnicity, and Participation in the Arts 

Table 5-9
 

Ratio of White to African-American and of White to Hispanic
 

Weighted Means for Socialization, Taste, and Participation
 

Scales, by Age of Respondent (Nov./Dec. 1982 Subsample)
 

Ratios, white means: African-American means 

TV arts 

Attend 

(w/jazz) 

0.87 

1.48 

1.85 

0.97 

2.23 

2.65 

Other 

creative 

1.90 

1.56 

2.22 

TV arts 

Attend 

(w/jazz) 

0.96 

1.56 

1.82 

1.87 

1.80 

2.48 

Other 

creative 

0.98 

1.60 

1.35 

Parental 

Age guidance 

18-30 1.27 

31-51 1.19 

52+ 1.86 

Attend 

(no jazz) 

18-30 2.04 

31-51 2.67 

52+ 2.70 

Ratios, white means: Hispanic means 

Parental 

Age guidance 

18-30 1.40 

31-51 1.48 

52+ 1.65 

Attend 

(no jazz) 

18-30 2.05 

31-51 2.07 

52+ 3.88 

Number of respondents 

Age White 

18-30 605
 

31-51 647
 

52+ 656
 

96 

Lessons 

1.32 

1.62 

3.17 

Exhibits 

1.56 

2.02 

3.07 

Lessons 

1.81 

2.48 

2.14 

Exhibits 

1.34 

1.48 

2.03 

Art music 

1.50 

1.82 

3.55 

Perform 

0.97 

1.90 

1.30 

Art music 

0.83 

1.72 

1.82 

Perform 

0.55 

2.39 

0.31 

African-American Hispanic 

80 44 

74 47 

76 26 
Evidence on Racial and Ethnic Differences 

cluding and excluding jazz), and visually oriented activities. Indeed, a 

convergence of African-American and white participation is visible for all 

but performance and nonperformance activities. Among the youngest cohort, African-American means were higher than those of whites for viewing 

art programs on television, attending performances (including jazz), and 

participating onstage and backstage in performances. 

Reduction among age groups of the white/Hispanic ratios are less 

marked than those for whites and African-Americans (perhaps due to higher 

levels of Hispanic immigration), but a monotonic trend appears with respect 

to parental guidance activities, art music, televised arts viewing, performingarts attendance (excluding jazz), and visiting exhibits, museums and related 

activities. Among the youngest cohort, Hispanic means are higher than white 

means for taste for art music, television arts viewing, and both performance 

and other creative activities. 

Do these declining differences reflect changes in the net effects of race 

and ethnicity, or changes in the sociodemographic profiles of AfricanAmericans and Hispanic-Americans over the past decades? There is good 

reason to believe the latter is the case, especially changes in levels of formal 

education attained by Hispanics and African-Americans. Among the over51 subsample, the average white respondent had 11.25 years of education, 

the average African-American respondent, 7.43, and the average Hispanic, 

6.52. Among the subsample aged 18 to 30, the white average was 12.82, 

while the African-American average had risen to 12.33, and the Hispanic 

average had increased to 11.87. Given the powerful role of education in 

stimulating participation in the arts, we would expect that such relative 

advances for African-Americans and Hispanic-Americans should make 

these groups more similar to whites in patterns of taste and artistic participation.6 

Summary 

White respondents had higher mean scores on all the childhood experience, taste, and participation scales than African-Americans and, with the 

exception of performance activities, Hispanic respondents. Intergroup differences were modest because scores for all groups were low, and differences were greater for arts consumption than for arts production. 

Because their parents had less formal education than white parents, 

African-American and Hispanic respondents reported receiving fewer kinds 

of parental guidance experiences and taking fewer kinds of arts lessons or 

97 
Race, Ethnicity, and Participation in the Arts 

classes as children and adolescents than white respondents. African-Americans and Hispanics reported about the same number ,of classes and lessons 

and significantly more parental guidance experiences than whites of comparable age and family background. 

Hispanics liked art music as much and watched as many kinds of 

televised arts programs as whites with comparable sociodemographic characteristics, and the television arts viewing habits of African-Americans were 

similar to those of sociodemographically comparable whites. By contrast, 

sociodemographic differences account for only half ,3f the significant tendency for African-Americans to report enjoying fewer kinds of art music and 

related genres than whites, and differences in socialization explained little of 

the remaining gap. Thus, small but significant differences in musical taste 

are directly related to race. 

The effects of being African-American or Hispanic on participation 

varied depending on whether the activities entailed[ the consumption or 

production of art and whether the activities involved the performing arts or 

the visual and literary arts. Both Hispanics and African-Americans, on 

average, participate in fewer activities than whites on ~tll three arts consumption scales. By contrast, there is no significant difference between Hispanic 

and white respondents on either production scale, or between AfricanAmericans and whites with respect to onstage or backstage performance 

activities. The gap between African-Americans and whites is wider for the 

visual and literary arts than for the performing arts. 

Despite the gross differences, Hispanic-Americans participate in about 

as many arts-consumption activities as sociodemographically comparable 

non-Hispanic whites. Hispanic-Americans report being involved in more 

production activities (of both kinds) than sociodemographically similar 

white Americans with similar amounts of childhood experience in the arts. 

Significant differences between African-Americans and whites in performing-arts attendance are also fully accounted for by sociodemographic 

differences between the two groups. By contrast, sociodemographic factors 

explain only about two-fifths of the African-American/white difference in 

visually oriented consumption and production activities. Controlling for 

childhood experience eliminates the significant gap between AfricanAmericans and whites with respect to visual-art and literary production, but 

has little effect on African-American/white differences in exhibit attendance, literature reading, and related activities. The latter difference remains 

significant even after controls for artistic taste and interest are added. 

Taken together, these findings indicate that intergroup differences vary 

98 
Evidence on Racial and Ethnic Differences 

across different kinds of participation, that such differences are largely the 

result of sociodemographic variation between whites, African-Americans, 

and Hispanics, and that such effects of race or ethnicity as remain once 

sociodemographic factors are controlled are small relative to the impact of 

such variables as educational attainment and parental guidance. 

For the most part, childhood experience, taste, and participation measures were predicted by the same variables for African-Americans and 

Hispanics as for whites. Two exceptions were notable, however. The first of 

these had to do with the effects of age on parental socialization, musical taste, 

and television arts watching. With parental education controlled, it appears 

that white parents offer fewer guidance experiences than they used to, while 

African-American parents offer more, suggesting that a convergence is 

occurring. Similarly, controlling for other sociodemographic factors, tastes 

for art music and viewing arts programs on TV increased with age for whites, 

but not for African-Americans or Hispanics. (Differences were significant 

except for white/Hispanic TV arts program viewing.) Although these results 

could mean that white Americans’ tastes change more with aging than those 

of African-Americans or Hispanic-Americans, it seems more likely to indicate a convergence of all groups with respect to tastes for art music and 

convergence between African-American and white Americans in artistic 

interests as expressed through watching arts programs on television. These 

findings are consistent with inspection of means by race and age: among 

younger respondents, intergroup differences in parental guidance, taste for 

art music, and television viewing of the arts are smaller than for older 

respondents. 

Second, education had a stronger effect on television viewing of the arts 

and on all of the participation scales except for performance production 

activities for whites than for African-Americans, although in most cases it 

was a significant predictor for both groups. Although the differences were 

not significant, the effects on the participation scales of taking lessons or 

classes in the arts were also weaker for African-Americans than for other 

groups. The same was true of television viewing of the arts, and the differences between African-Americans and Hispanics were significant with respect to nonperformance consumption and production activities. In other 

words, there is some evidence that formal education, both general and 

specific to the arts, is more weakly related to adult interest and participation 

in the arts for African-Americans than for other groups. 

For most participation activities, gaps between white and minority subpopulations were greater for older than for younger respondents. The declin99 
Race, Ethnicity, and Participation in the Arts 

ing intergroup differences appear to be the result of changes in the sociodemographic profiles of African-Americans, Hispanics, and white Americans, 

especially rapid increases in the educational attainment of the two former 

groups, rather than of changes in the effects of race on the participation of 

otherwise similar men and women. 

100 
Chapter 6 

CONCLUSIONS
 

I

n Chapter l, we called attention to three distinct ways of thinking about
 

"underrepresentation" of groups as participants in artistic activities. The
 

first focuses on gross differences in rates of participation. In this view,
 

any statistical underrepresentation is a matter of public concern. The second 

emphasizes differences in net rates of participation between people who are 

similar in terms of socioeconomic and demographic characteristics other than 

race or ethnicity. In this view, differing rates of participation are of concern 

only if they stem directly from racial or ethnic identity. The third perspective 

asks whether differences in participation, gross or net, result from differences 

in taste or demand between groups or from differences in the degree to which 

groups face different obstacles to participation. In this view, varying participation is a concern only if it results from inequality of opportunity to 

participate rather than from differences in taste. 

Which of these perspectives one favors will depend on one’s more 

general attitudes towards inequality. It will also depend on one’s beliefs 

about artistic participation. If one believes that participation in the arts is 

absolutely essential to an acceptable quality of life, one is more likely to 

believe that gross differences in participation are important. If one believes 

that participation in the arts is essential, but not so important as education, 

income, or a good job, one might be more likely to focus upon net differences 

in participation. If one is not certain whether participation in the arts is 

important for people, one is more likely to focus on equality of opportunity 

and to see no virtue in stimulating demand. 

In this section, we summarize the results of our analyses of the SPPA 

data on participation in selected artistic activities by African-Americans, 

Hispanics, and white Americans.~ We organize our conclusions along the 

lines of the questions raised by the three perspectives noted above: gross 

differences in participation, net differences in participation, and evidence 

bearing on the relative roles of variation in tastes and varying exposure to 

barriers in accounting for the differences observed. 

101 
Race, Ethnicity, and Participation in the Arts 

Because patterns of differences among groups var.y for different kinds of 

artistic activities and because the SPPA did not ask people about many kinds 

of artistic activities, we can draw no general conclusions about differences 

in artistic participation per se. Thus, we shall call attention to the kinds of 

activities to which specific conclusions do and do not apply. 

The Surveys of Public Participation in the Arts represent the best resource available for investigating the question with which this report is 

concerned. But no survey, especially one designed to address a great many 

different issues, can tell us everything we wish to know. In the final section, 

we set out an agenda of questions that remain, along with some suggestions 

about how such questions might be answered. 

Do Rates of Participation Vary? 

The answer to this question is unambiguous. Rates of participation in 

most of the activities about which the SPPAs asked vary among white, 

At~can-American, and Hispanic respondents. White Americans participate 

at higher rates than African-Americans or Hispanic-.Americans in most of 

these activities that involved attendance at museums, visual art exhibitions, 

and live performances. African-Americans participate at higher rates than 

others, however, as members of jazz audiences. 

Differences in rates of participation between whites, on the one hand, 

and African-Americans and Hispanics on the other, were modest for two 

kinds of active performing: playing a musical instrument onstage and singing, dancing, or acting in public. With respect to the former, however, 

differences between whites and African-Americans were greater if only 

public performances of classical music or jazz were considered. Whites were 

also more likely than African-Americans or Hispanics to participate in 

producing visual arts objects such as drawings, paintings, or crafts. For most 

of these activities, rates of participation were somewhat higher for Hispanic 

than for African-American respondents, although the differences between 

white and Hispanic rates exceeded those between ttispanic and AfricanAmerican rates. 

Except for reading imaginative literature, fewer than half of the people 

surveyed participated in any of the activities about which the "core" and 

"other activity" questions of the SPPA asked. With respect to all of the 

activities but reading, visiting art exhibits, visiting science and history 

museums, visiting historical monuments, and doing needlecrafts, fewer than 

20 percent were active. Fewer than 5 percent of respondents attended opera 

102 
Conclusions 

or musical performances, or performed publicly on musical instruments or 

by singing, acting, or dancing. 

Because relatively few people participated, especially in core activities, 

absolute differences in participation rates between groups were often small. 

But absolute differences between participation rates of whites and those of 

African-Americans were. 10 or more in both 1982 and 1985 for visiting art 

exhibitions, reading works of imaginative literature, visiting science or 

history museums, visiting historical monuments, attending arts and crafts 

fairs, and engaging in such needlecrafts as sewing or knitting. White rates 

exceeded Hispanic rates by this margin in both years for these same activities, except for visiting science or history museums and visiting art exhibits. 

By contrast to the relatively small absolute margins of difference, ratios 

of whites’ to others’ participation rates were in many cases greater than two 

to one. African-Americans were less than half as likely as whites in both 

1982 and 1985 to work in pottery or other craft media, or to attend classical 

music concerts, opera performances, musicals, plays, arts and crafts fairs, or 

ballet performances. Hispanic respondents were less than half as likely to 

attend plays in both years. 

Thus, there were persistent and substantial gaps in the extent to which 

non-Hispanic white Americans, on the one hand, and African-Americans 

and Hispanic-Americans, on the other, reported participating in the arts 

about which the SPPA asked. African-Americans and Hispanics were less 

likely than whites to be consumers of both the performing arts and the visual 

arts. Both groups were less likely to participate in visual-arts activities. 

Differences between groups were less for performing onstage, particularly 

in popular genres. Differences were not restricted to Euro-American "high 

culture" art forms, however. They also appeared for making crafts, reading 

literature, and visiting historical or scientific museums or exhibits. 

Does Participation Vary Net of 

Sociodemographic Factors? 

Do African-American, Hispanic, and white Americans who are similar 

with respect to such characteristics as gender, age, educational attainment, 

marital status, occupation, family income, and residence in a Standard 

Metropolitan Statistical Area (SMSA) participate at different levels? Here 

the answer is more complicated. 

If we take each of the core activities, one at a time, and control for 

socioeconomic and demographic effects, we find different patterns for 

103 
Race, Ethnicity, and Participation in the Arts 

African-American and Hispanic respondents. For most of the core activities 

in which whites participated significantly more than African-Americans (all 

but jazz attendance and performing in public), between approximately 25 

and 40 percent of the gap resulted from differences, in sociodemographic 

position between the races. The remaining margins were statistically significant, but small compared to differences associated with educational attainment and other background factors. These differences indicate that some 

factor or factors make the probability that African-Americans participate in 

these activities significantly lower than the probability of participation by 

white Americans who are similar with respect to the socioeconomic and 

demographic factors for which we controlled. Nonetheless, policies that 

made African-Americans more similar to whites with respect to educational 

attainment, occupational status, and family income would diminish differences in rates of participation for every core activity but jazz attendance. 

Sociodemographic differences between white and Hispanic respondents 

accounted for most of the gross differences between whites and Hispanics in 

attendance at classical music concerts, ballet performances, and art exhibits. 

With such factors controlled, white participation was significantly greater 

than Hispanic participation only for attendance at musical stage performances, plays, and (in 1985 only) opera; and for reading: imaginative literature 

and (in 1982 only) acting, singing, or dancing onstage. In 1982, Hispanic 

respondents were significantly more likely than comparable non-Hispanic 

whites to attend ballet performances. Because the core activities for which 

significant differences persisted tended to be those that in the United States 

are usually presented in the English language (musicals, plays, literature), 

we speculated that the high proportion of Hispanic-Americans for whom 

Spanish is the native language may have played a role. If this speculation is 

correct, then differences between whites and Hispanics in core participation 

are largely attributable to socioeconomic and linguistic differences. Thus, 

policies that increased the educational attainment, occupational levels, and 

incomes of Hispanic-Americans would eliminate much or all of the significant differences between Hispanics and non-Hispanic whites in participation 

in most of the core activities. Moreover, differences in attendance at plays 

and musicals and differences in reading literature might be moderated by 

increasing the availability of such works in Spanish. 

We also looked at net differences between groups in scores on five scales 

developed with the use of factor analysis. These scales represented the 

number of activities in which respondents participated, rather than the 

probability of participating in a specific activity. Drawing on a smaller 

sample of respondents who were asked a wider range of questions, these 

104 
Conclusions 

analyses looked at scores on five scales: participation as consumers at live 

performances (with and without jazz included); participation as consumers 

of visual materials (art and history museums and exhibits and imaginative 

literature); participation as producers onstage or backstage of performing 

arts events; participation as producers of visual arts and crafts. 

Nearly all of the difference between African-Americans and whites on 

the performing-arts attendance scale (all of it when jazz was included on the 

scale) resulted from sociodemographic differences between members of the 

two racial groups. Once such factors were taken into account, no significant 

differences remained between comparable African-Americans and whites in 

the number of kinds of performing-arts activities they reported attending. 

There was no significant difference between white and African-American 

scores on the performing-arts production scale. 

African-American respondents participated in significantly fewer visualarts and literature consumption and production activities than whites. Moreover, only about 40 percent of these differences were attributable to the 

socioeconomic and demographic factors for which we controlled. 

In other words, these analyses indicate that one cannot generalize about 

net differences between African-Americans and whites in artistic participation. African-Americans are more likely than whites to attend jazz concerts, 

and the margin only increases when sociodemographic differences between 

the races are taken into account. African-Americans are no less likely than 

whites to participate in performing-arts activities as performers or by working backstage. African-Americans on average attend fewer kinds of the 

performing-arts activities about which the SPPA asked (excluding jazz) than 

whites, but about the same number as whites who are comparable with 

respect to socioeconomic and demographic characteristics. By contrast, 

African-Americans participate in significantly fewer kinds of visual-arts 

activities than comparable whites, both as consumers and as producers. 

Differences between white and Hispanic respondents can be described 

more succinctly. There were no significant differences between non-Hispanic whites and Hispanics on either performing-arts or visual-arts production scales. Hispanic respondents scored significantly lower than whites on 

each of the consumption scales, but both of these differences resulted from 

differences between the groups in socioeconomic standing and demographic 

characteristics. In other words, there are no significant differences in any of 

these scales between sociodemographically comparable white and Hispanic 

respondents. 

105
 
Race, Ethnicity, and Participation in the Arts 

Does Demand for Artistic Participation Vary? 

This question is the hardest to address with the resources provided by the 

SPPAs, and we have reached no definitive conclusions. The best we can do 

is to hold the data up like so many prisms and report the results from a variety 

of angles. 

The SPPAs asked a subsample of respondents whether they liked a wide 

range of musical genres. Within each group, responses were very stable 

between 1982 and 1985. White and Hispanic tastes were quite similar. 

African-American and white respondents’ tastes differed more, although, 

like Hispanics and whites, African-Americans tended to prefer commercially popular genres to most other kinds of music. Larger proportions of 

whites and Hispanics liked country western, rock and easy listening music 

than any other kind of music, whereas African-American respondents were 

most likely to choose hymns/gospel music, soul/blues/rhythm and blues, and 

jazz. Those genres favored by whites and Hispanics ranked fourth, fifth, and 

sixth among African-American respondents, well ahead of the seven other 

genres about which the survey asked. Moreover, substantial minorities of 

whites and Hispanics enjoyed gospel, rhythm and blues, and jazz. Such 

genres as bluegrass, barbershop, and opera were distinctly less popular 

among all three groups. Taken together, the results demonstrate strong 

similarity of tastes between whites and Hispanics, and patterns of musical 

taste for whites and African-Americans that, although different, involve 

different degrees of participation in the same commercially popular musical 

forms rather than sharply opposed preferences. 

Looking more closely at the four kinds of music related to the SPPA core 

participation activities (classical music, opera, show tunes, and jazz), we see 

that differences between African-Americans and whites in taste for classical 

music mirrored differences in African-American and white rates of attendance at classical music concerts. By contrast, the proportion of Hispanic 

respondents who said they enjoyed classical music was close to that of 

whites in 1982 and greater in 1985. Taken together with the finding that 

Hispanics were about as likely to attend classical music concerts as sociodemographically comparable white respondents, this pattern suggests that 

Hispanics would attend classical music performance, s at the same rates as 

whites if they had the resources to do so. 

Similarly, differences between African-Americans and whites with respect to opera, show tunes, and jazz are comparable to differences in 

attendance at operas, musicals, and jazz performances. So were differences 

between Hispanics and whites for opera and show tunes in 1982, but not in 

106 
Conclusions 

1985, when differences in attendance far exceeded differences in taste. 

Hispanic respondents were more likely than whites to report liking jazz in 

both years, but less likely to report attending jazz concerts. Taken together, 

these results again suggest that disparities between Hispanics and non-Hispanic whites in attendance at these activities reflect socioeconomic barriers 

rather than differences in taste, whereas differences between African-Americans and whites would appear to be largely accounted for by differences in 

taste. 

This conclusion, however, would conflict with results of analyses predicting probabilities of participation in the core attendance activities (other 

than jazz), which showed that between 25 and 40 percent of differences 

between African-Americans and whites were accounted for by differences 

in socioeconomic and demographic factors. In other words, it seems likely 

that some portion of differences in taste are themselves the result of socioeconomic inequality. Consistent with this interpretation, once sociodemographic factors are taken into account, differences in musical taste or in 

childhood socialization explain little of the intergroup variation that remains. 

The SPPAs also asked respondents if they wanted to participate in the 

seven core attendance activities more than they had in the previous year. 

Respondents from all groups who had participated in a given activity in the 

previous year were much more likely than those who had not to wish that 

they had attended more. And respondents who had not participated were 

more likely to wish that they had if they were members of groups that 

participated at relatively high rates. For most activities, the proportion of 

people who did not participate but said that they wanted to exceeded the 

proportion that actually participated. 

What this implies is that if all reported barriers to attendance were 

removed -- that is, if everyone who reported wanting to participate, but did 

not, joined the ranks of attenders -- the absolute differences in probabilities 

of attendance at core activities between members of different groups would 

increase. The margin between African-American attendance at jazz concerts 

and attendance by whites and Hispanics would become greater, as would the 

margin between white attendance at classical concerts, operas, musicals, 

plays, ballet performances, and art exhibitions, and African-American and 

Hispanic attendance. For many activities, however, the large increase in the 

proportions attending in each group would reduce the ratios of rates of 

participation between groups. 

We caution against taking this finding too seriously for several reasons. 

First, we are not sure what respondents meant when they said they wanted 

to attend more than they did. Second, we suspect that respondents factored 

107 
Race, Ethnicity, and Participation in the Arts 

in the cost of attendance in deciding whether they wiished to do something 

they had not done, so that respondents facing socioeconomic barriers would 

have been less likely to report "wanting" to attend an event than more 

well-to-do respondents whose taste for the activity in question was similar 

to theirs. Finally, we suspect that many barriers to participation work by 

reducing demand for participation in such activities, rather than by keeping 

people from satisfying demand. 

Indeed, other analyses, including the results on Hispanic musical tastes 

mentioned above, cast doubt upon the degree to which whites do value the 

SPPA core arts more highly than do African-Americans or Hispanics. 

Differences in the extent to which whites, on the one hand, and AfricanAmericans and Hispanics, on the other, watch the core attendance activities 

(other than jazz) on television are not so great as differences in the extent of 

live participation. This may suggest that when cost is not a factor (because 

most Americans have access to televised arts programs), intergroup rates of 

participation are more comparable than when participation is more costly 

and time-consuming. 

Moreover, parents of Hispanic and African-Americans appeared to value 

certain kinds of artistic guidance even more highly than comparable white 

parents. When age, gender, and educational attainment of parents are controlled, Hispanic and African-American respondents reported significantly 

if modestly higher scores on a parental guidance scale comprising being 

encouraged to read, being taken to museums, being exposed to classical 

music, and being taken to live performances. 

Taken individually, the results of the analyses described in this section 

point in somewhat different directions. Taken together they suggest that the 

issue of motivation is extremely complex. On the one hand, participation in 

the artistic activities for which intergroup differences appear is not something that everyone clearly desires. For example, eliminating all barriers to 

attendance at jazz concerts or ballet or opera (by providing free vouchers, 

transportation, and babysitting), would seem unlikely to eliminate differences between African-Americans and whites in rates of attendance. On the 

other hand, it would be simplistic, and at odds with many of our other 

findings, to suggest that African-Americans and Hispanics attend certain 

activities less than whites simply because they like them less. Rather, 

differences in participation rates appear to result, in part, from differences in 

socioeconomic opportunity, in part from differences in taste, and in part 

from the interaction of these two factors. 

108 
Conclusions 

Summary Conclusions 

1.	 Rates of participation in the activities about which the SPPA asked differ 

by race and ethnicity. White rates are greatest for almost all these 

activities (with the notable exception of those associated with jazz, for 

which African-American rates are highest). In general, differences are 

greater for attendance and reading than for viewing the arts on television, 

parental guidance into the arts through home activities and (for AfricanAmericans) taking formal classes and lessons, participating in most art 

producing activities, and (for Hispanics) musical tastes. For most activities, absolute differences are relatively small (with minorities of any 

group participating), although ratios of white to other rates are often as 

high as two to one. 

2.	 African-Americans participate somewhat less than sociodemographically comparable white Americans in most of the core activities, but most 

of these net differences are small. Net differences between AfricanAmericans and whites are more marked for the visual arts than for the 

performing arts. African-Americans are significantly more likely than 

comparable whites to attend jazz concerts. 

3.	 Hispanic-Americans participate somewhat less than comparable whites 

in some core activities, especially those usually presented in the English 

language. In general, however, Hispanic-Americans participate at rates 

similar to those of socioeconomically comparable white Americans. 

4.	 Differences in participation associated with race are very small compared to those associated with educational attainment and are usually 

exceeded by those associated with income, occupational status, and 

gender. The principal barriers to participation for African-Americans 

and, especially, Hispanics, are socioeconomic. These barriers reduce 

minority participation by influencing demand for the arts and by making 

it difficult for less well-off Americans to satisfy their demand. 

5. Measurable differences in taste or in parental guidance into the arts, other 

than those associated with differences in socioeconomic standing, play 

a small role in explaining most of the observed differences in participation between African-American, Hispanic, and white Americans. Much 

of the observed differences in taste, demand, or childhood experience 

appears to result from socioeconomic differences between these groups. 

6. Intergroup differences in participation in most of the activities about 

which the SPPA asked are smaller for younger than for older respondents. Most of this apparent decline in the participation gap is probably 

109 
Race, Ethnicity, and Participation in the Arts 

the result of increases in socioeconomic resources, especially years of 

schooling, of African-American and Hispanic respondents. 

Further Research 

We have emphasized throughout this report that one cannot generalize 

meaningfully about "artistic participation." Patterns of differences between 

non-Hispanic whites, on the one hand, and African-Americans and Hispanics, on the other, vary among activities. 

The SPPA questions focused upon categories of participation that a 

pretest indicated were widely understood by all or most people interviewed. 

The requirements of a national survey tended to exclude such forms as 

mariachi music or clog dancing that are unfamiliar to most Americans, 

including many forms with roots in specific ethnic or racial communities. 

The questions also tended to focus on consumption activities associated with 

nonprofit cultural institutions rather than on the most widely consumed 

forms of popular culture. We suspect that there are many activities (like jazz) 

for’ which white participation is lower than Afric, an-American. Consequently, we would not generalize the findings of this report beyond the 

specific kinds of activities that the SPPA considere, d. Because the SPPA 

items cover a broad range of activities, including ones with which public 

policy has been particularly concerned, we do not regard this as a serious 

problem given the purposes of this report. But it does mean that it would be 

a mistake to consider this a full treatment of all .aspects of the artistic 

participation of African-Americans, Hispanics, and white Americans. 

Even within the scope of artistic participation as defined by the SPPA, 

this report could not address a number of questions that are of substantial 

interest. The limitations we describe below are natural ones for a national 

survey that was not designed specifically to address racial and ethnic differences in participation. Nonetheless, without questioning the importance of 

what the SPPAs have already accomplished, it may be useful to sketch a few 

tasks that remain. 

Each of the groups we examined is heterogeneous. The SPPA data did 

not permit close analysis of participation by ethnic subgroups, in part 

because the number of Hispanic respondents (other than Mexican-Americans) was relatively small, in part because of the way in which ethnic 

background was coded on the SPPA. In particular, ill is important from the 

standpoint of public policy to distinguish among the ethnic groups that 

constitute the Hispanic and Asian categories, between native-born and 

110 
Conclusions 

immigrant (e.g., West Indian) African-Americans, and between Native 

Americans and other respondents. A design that stratified the sample on 

ethnicity and oversampled these groups relative to their percentage of the 

population, and a coding scheme that distinguished more clearly among 

groups would be helpful in this respect. 

To mask the identity of respondents, the Census Bureau did not include 

regional data on the SPPA files. Broad regional classifications would permit 

investigation of regional differences (which may interact with race or ethnicity) without breaching confidentiality. 

Especially for those groups for which recent immigration rates have been 

relatively high (Hispanics and Asians), it is important to be able to assess the 

impact of native language on participation in activities relying on the spoken 

or written word. A question on language should be included in subsequent 

surveys. 

Even if we had found no differences in the rates of participation of 

African-Americans, Hispanics, and white Americans in the activities that the 

SPPA described, we could not have concluded that these groups participated 

in the same way. Do African-Americans, Hispanics, and whites who attend 

theater, for example, see the same kind of plays at the same kind of venues? 

If attenders vary by race or ethnic origin in the kinds of activities they prefer, 

we might be able to assess the extent to which different rates of participation 

result from the undersupply of the kinds of activity preferred by members of 

the groups that participate less. Such questions could perhaps be addressed 

best in local surveys that would ask respondents about attendance at specific 

events or specific institutions. We suspect that such questions would reveal 

greater intergroup diversity than questions phrased in more general terms. 

We found some suggestive evidence of differences in the effects of 

gender, education, occupation, and artistic socialization on participation by 

members of different groups, but could explore them only superficially due 

to the relatively small number of African-American, Hispanic, and especially Asian respondents. Particularly with respect to activities in which 

relatively few people participate, cell sizes (e.g., for college-educated Hispanic opera attenders) were very small. A research design that permitted 

oversampling of minority respondents (relative to their share of the population) would alleviate this problem to some degree. 

Although one can make rough inferences about change over time on the 

basis of cohort analysis, as we have attempted to do in this report, confident 

conclusions require data collected over a wide range of time. The 1982 and 

1985 SPPAs represent an excellent first step in this process. There can be no 

substitute for the routine collection of comparable data at regular intervals. 

111 
Race, Ethnicity, and Participation in the Arts 

How widespread is participation in the activities about which the SPPA 

could not ask because they were not sufficiently familiar to the average 

American? Some of these activities, such as reggae music or Balkan folk 

dance, might be characterized by racially or ethnically homogeneous audiences, even though the proportion of persons in the relevant ethnic groups 

who participate would be low. Such art forms may add a great deal to our 

national cultures and to specific artistic subcultures even if they are participated in by too few persons to catch in a national sample survey. Regional 

or SMSA-based surveys might be able to explore the distribution of participation in such activities more effectively. 

The one SPPA question that provided information about taste for largescale commercial popular-culture genres, the music: preference question, 

revealed patterns of racial and ethnic cleavage and convergence that were 

not apparent in responses to questions about other activities. Because much, 

probably most, of the arts that Americans consume are provided by the 

national popular-culture industries, a comprehensive analysis of differences 

in artistic participation would require attention to participation in popular 

culture broadly defined. 

The foregoing is a wish list and, as such, is unrestricted by the costs, 

multiple priorities, and tradeoffs that constrain actual research decisions. 

Some of the suggestions offered above will be impractical, while others may 

not. In conclusion, we offer the following recommendations: 

 ̄ That information on region of residence be inclluded in the SPPA data 

file. 

 ̄ That information on native language be collected and included in the 

SPPA data file. 

 ̄	 That the Arts Endowment explore the possibility of a design for the 

SPPA that oversamples African-American, Hispanic, Asian, and 

Native American respondents relative to their share of the population. 

 ̄	 That ethnicity codes comparable to those provided in the Census of 

Population, including multiple ethnic origins, be collected for the 

SPPA. 

 ̄	 That the Arts Endowment or other research sponsors explore the 

possibility of supporting comparable local surveys of participation in 

the arts in several regions that include questions about attendance at 

specific events or specific institutions. 

112 
NOTES
 

Executive Summary 

1. For the sake of simplicity, we drop the modifier "non-Hispanic" when 

referring to whites and African-Americans throughout this report. The 

reader should recognize that this modifier is implicit. 

2. Throughout this report, "childhood socialization" or "socialization" refer 

to both forms of early experience: "parental guidance" and "lessons and 

classes." 

3. SMSA residence refers to whether respondents lived in an urban area, 

an area within an SMSA but not a city (ordinarily, a suburb), or an area 

outside a center of concentrated population. SMSA stands for Standard 

Metropolitan Statistical Area. 

Chapter One 

1. See, e.g., Richard Bach, The Place of the Arts in American Life (New 

York: The Carnegie Corporation, 1924); and Frederick P. Keppel and 

Robert L. Duffus, The Arts in American Life (New York: McGraw Hill, 

1933); Melvin E. Haggerty, Art as a Way of Life (Minneapolis: University of Minnesota Press, 1935). 

2. A detailed technical description of the procedures for the 1982 SPPA 

(which were similar to those for the 1985 survey) is available in John P. 

Robinson, Carol A. Keegan, Terry Hartford, and Timothy A. Triplett, 

Public Participation in the Arts: Final Report on the 1982 Survey, 

October 1985 report to the Research Division, National Endowment for 

the Arts. Background information on the 1985 survey is available in 

Timothy A. Triplett and Jeffrey M. Holland, Public Participation in the 

Arts: The 1982 and 1985 User’s Manual (draft, October 1985), report 

to the Research Division, National Endowment for the Arts. 

113 
Race, Ethnicity, and Participation in the Arts 

3. The text of the survey is available from the National Endowment for the 

Arts, Research Division. Because only tiny percentages engaged in any 

given activity more than once in the month preceding the survey, only 

data on participation during the previous year are analyzed in this report. 

4. The survey was administered each month for 12 months in 1982, and 6 

months in 1985, with all but the core questions rotated from month to 

month. (All questions were asked in the final two months of 1982.) 

Consequently, analyses of responses to all but the core questions are 

based on only a portion of the total number of respondents. Because 

responses were weighted to be representative of the non-institutionalized 

population over 18 for each month, as well as for each of the two years, 

findings are equally generalizable. 

5. William L. Yancey, Eugene P. Ericksen, and Richard Juliani, "Emergent 

Ethnicity: A Review and Reformulation," American Sociological Review 41 (1976): 391-403; Susan Olzak, "Contemporary Ethnic Mobilization," Annual Review of Sociology 9 (1983): 355-74. 

6. Ninety-five percent of respondents to the 1982 SPPA who reported their 

race as Black reported their ethnicity as Afro-American or Negro. In 

1985, the figure was 92 percent. Each year, most other Black respondents 

reported their ethnicity as "other," a category that would have included 

such Caribbean ethnicities as Jamaican or Haitian. In each year more 

than 99 percent of respondents who reported their ethnicity as AfroAmerican or Negro reported their race as Black. We use "African-American," which has come into common usage since the surveys were 

conducted. 

7. The "Other" category in 1982 consists of Asian-Americans, American 

Indians, and persons who failed to choose one of several races from a 

set presented by the interviewer. In 1985, it excluded Asian-Americans 

and included only a very small number of respondents. We do not report 

results for the "Other" category. Because of its heterogeneity and because we do not have data on its composition, such results could not be 

interpreted. Unfortunately, then, the data do not permit us to describe the 

artistic participation of Native Americans. 

8. Our aggregation of ethnic categories into a broader Hispanic group yields 

a category consistent with the federal government’s definition of Hispanic as "A person of Mexican, Puerto Rican, Cuban, Central or South 

American or other Spanish culture or origin, regardless of race" (OMB 

Directive Number 15, as revised May 12, 1977). 

9. By contrast, in the 1980 Census (the report cited in the note at the bottom 

of Table 1-2), 41 percent of Hispanic respondents reported their race as 

114 
Notes 

something other than Black or White. The difference is a result of 

different question phrasing: SPPA respondents were asked to designate 

their race and given a brief set of options that did not include "other." 

Census respondents, by contrast, were asked to choose from among a 

longer list that included both racial and ethnic categories. We are grateful 

to Carmen DeNavas, Helen Montagliani, and Robert Tinari of the Bureau 

of the Census for explaining the manner in which the Bureau asked about 

race and ethnicity in its interviews. 

10.	 As Table 1-1 indicates, the percentages of Hispanic-Americans in the 

SPPA samples are close to, but not identical with, the proportion of these 

groups in the American population. Furthermore, a review of census data 

reveals that 1985 SPPA Hispanic-American respondents were typical of 

their specific ethnic groups with respect to educational attainment, a 

variable of particular interest in the analysis of arts participation. Census 

data are from U.S. Bureau of the Census, Current Population Reports, 

Persons of Spanish Origin in the United States." March 1985 (Advance 

Report), December 1985 Series P-20, No. 403, p. 4. For insightful 

criticism of the "Hispanic" category, see David E. Hayes Bautista and 

Jorge Chapa, "Latino terminology: Conceptual bases for standardized 

terminology," American Journal of Public Health 77 (1987): 61-68; for 

a pragmatic defense, see Femando M. Trevino, "Standardized terminology for Hispanic populations," pp. 69-72 in the same issue. 

Chapter Two 

1. A second reason for focusing on the annual rather than the monthly rates 

is the evidence reported by John Robinson and his colleagues that 

respondents’ recollections "telescoped" their annual attendance into the 

previous month, thus making the monthly estimates less reliable than the 

annual ones. See John P. Robinson, Carol A. Keegan, Terry Hartford, 

and Timothy A. Triplett, Public Participation in the Arts: Final Report 

on the 1982 Survey, Report of the Research Division of the National 

Endowment for the Arts, October, 1985, pp. 227-29. 

2. Paul DiMaggio, Michael Useem, and Paula Brown, Audience Studies of 

the Performing Arts andMuseums: A Critical Review, Research Division 

Report #9 (Washington, D.C.: National Endowment for the Arts, 1978), 

pp. 37-38. 

3. For the sake of simplicity, we drop the modifier "non-Hispanic" when 

referring to whites and African-Americans throughout this report. The 

115 
Race, Ethnicity, and Participation in the Arts 

reader should recognize that this modifier is implicit in the remainder of 

the report. 

4. For a careful analysis of responses to the SPPA questions about jazz, see 

Harold Horowitz, The American Jazz Music Audience (Washington, 

D.C.: National Jazz Service Organization, 1986). 

5. We know that people who watch an art form on television are more likely 

than those who do not to attend it in person; but, without data over time 

on the same people, we cannot ascertain whether this is the case because 

television viewing leads to attendance, because attenders are more likely 

to watch arts programming on television, or because attending live events 

and watching the arts on television are caused by some third set of factors. 

6. Pierre Bourdieu, Distinction (Cambridge: Harward University Press, 

1984); Paul DiMaggio, "Cultural capital and school success: The impact 

of status culture participation on the grades of U.S. high school students," 

American Sociological Review 47 (1982): 189-201; and Paul DiMaggio 

and John Mohr, "Cultural capital, educational attainment, and marital 

selection," American Journal of Sociology 90 ( 1985): 1231-61. 

7. John P. Robinson et al., Public Participation in the Arts, p. 368. 

8. The 1985 figures showed an increase for whites, African-Americans, and 

Hispanics in the extent to which parents listened to classical music while 

the respondents were growing up. Because the question referred to 

previous parental behavior, which by definition could not have changed 

between 1982 and 1985, as opposed to respondentbehavior (which could 

have), we do not regard these increases as meaningful ones. None of the 

differences are statistically significant. Moreover, because the sample 

was not designed to be representative of Hispanic-Americans, it is 

possible that some portion of the difference for that group, which is the 

largest, is an artifact of sample composition changes. Because the 

number of respondents in 1982 was substantially greater than that in 

1985, we place more confidence in the results for the earlier year. 

9. Fewer than 10 percent of respondents in any group in either year reported 

that their parents "often" listened to classical music, though whites were 

somewhat more likely than members of other groups to give this response. 

10.	 Fewer than 5 percent of any group in either year reported that their 

parents "often" took them to art museums or galleries. 

11.	 White respondents were more likely than others to report that their 

parents "often" took them to such events, but fewer than 6 percent of any 

group in either year reported this frequency of attendance. 

12. The single exception: in 1982, 7.31 percent of the Hispanic respondents 

116 
Notes 

as compared to 6.92 percent of the African-Americans reported having 

taken acting lessons. 

13. It may be that Hispanic-Americans have gone to schools where fewer 

arts courses have been offered or required; that they are less likely than 

African-Americans or whites to take optional arts courses; or that they 

have in some way been excluded from courses that were available to 

African-Americans or whites. Note, however, that a far higher proportion of Hispanic-Americans than of whites or African-Americans are 

immigrants who received their schooling outside of the United States. 

Unfortunately, data on where respondents were born are not available in 

the SPPA. 

14.	 To pursue this issue further, we compared the percentages of AfricanAmerican, Hispanic, and white respondents participating in the core 

consumption items among respondents who did and did not take lessons 

relevant to each item before the age of 18. (For example, we compared 

attendance at classical music concerts by respondents who took music 

appreciation courses to the attendance by those who did not take such 

courses. See Appendix tables 2-4 and 2-5.) As expected, persons in each 

group who had taken relevant classes or lessons participated in most 

activities at higher levels than others. In 1982, the difference between 

respondents with and without lessons was greatest for most activities for 

African-Americans and Hispanics, and the odds ratio of participation 

between whites and other groups was in most cases lower among persons 

who had taken lessons or classes, suggesting the possibility that formal 

instruction tends to depress intergroup differences. (Alternatively, African-Americans and Hispanics who reported taking lessons or classes in 

their youth in 1982 may simply have had more of other characteristics 

that are associated with attendance than did whites who reported having 

taken lessons.) These differences were not so apparent, however, among 

respondents to the 1985 SPPA. Because the number of African-American and Hispanic respondents is greater in the 1982 SPPA, we have more 

confidence in those data. But given the discrepancy in results between 

the two years, it would be incautious to regard the 1982 patterns as any 

more than bases for hypotheses for further research. 

Chapter Three 

1. We ask the same question about Asian-Americans, but there are so few 

Asian-Americans in the sample that we answer it with less confidence 

than for the other groups. 

117 
Race, Ethnicity, and Participation in the Arts 

2. In Chapter 5, we shall return to other forms of participation and explore
 

similar questions using different methods and a wider range of variables.
 

3. The following description of our approach will be somewhat tedious for
 

the reader unfamiliar with statistical analyses of the type reported here;
 

but reading it is necessary if one is to interpret the tables in this chapter.
 

4. For a fuller description, see John H. Aldrich and Forrest D. Nelson,
 

Linear Probability, Logit, and Probit Models (Beverly Hills, California:
 

Sage Publications, 1984). We used the LOGIST procedure provided by
 

SAS (a statistical package) and developed by Frank E. Harrell, Jr.
 

5. Education and income, which were categorized in the survey, were
 

recoded to their natural metric (using midpoints of categories where
 

appropriate). Because of changes in the federal occupational classification system between the 1982 and 1985 surveys, the occupational
 

classifications were somewhat different, although occupations were
 

aggregated to maximize comparability between the two years. For
 

residence, the omitted category was "outside SlVISA." For occupation,
 

the omitted category in 1982 was "craft, operative, service, farm, transport, laborers, private household, and armed fo:vces"; in 1985, it was
 

"craft, operative, service, farm, armed forces." For marital status, the
 

omitted category was "married."
 

6. Because logistic regression analyses cannot generate standardized regression coefficients, comparison of effects is less straightforward than
 

for ordinary least squares regression analysis of the kind used in Chapter
 

5. We compare the magnitude of effects by comparing the R statistic for 

specific independent variables. The R statistic measures the net contribution of each predictor to the model’s total explanatory power. 

7. William Julius Wilson, The Declining Significance of Race: Blacks and
 

Changing American Institutions, 2nd ed. (Chicago: University of Chicago Press, 1980); Stanley Lieberson, A Piece of the Pie: Blacks and
 

White Immigrants Since 1880 (Berkeley: University of California Press,
 

1980).
 

8. The results of these analyses are presented in Appendix Table 3-1. Note
 

that the coefficient for each independent variable represents the effect of
 

that variable on participation among members of the group in question.
 

9. By "more likely," we mean "more likely after controlling for other 

sociodemographic differences between white men and white women." 

Unless otherwise specified, all comparative statements in this chapter 

refer to net differences after the inclusion of sociodemographic controls. 

118 
Notes 

Chapter Four 

1. Questions on unsated demand for and barriers preventing the other three 

core activities (two kinds of public performance and reading imaginative 

literature) were not included in the SPPA. 

2. See Roger A. McCain, "Reflections on the Cultivation of Taste," Journal 

of Cultural Economics 3, 1 (1979): pp. 30-52; and "Game Theory and 

Cultivation of Taste," Journal of Cultural Economics 10, 1 ( ! 986): 1-16. 

3. John Robinson, Public Participation in the Arts." A Project Summary 

(College Park, Maryland: University of Maryland Survey Research 

Center, 1985), pp. 2-3ff. 

4. Note that there is nothing circular about this argument. In the case of 

most other goods, demand is greater among those with less. If I do not 

have a washing machine, I am likely to want one. Once I have one, I will 

not need another until the one I have breaks down. Similarly, my demand 

for breakfast is higher before rather than after I have eaten. The arts may 

be different. 

5. See, e.g., David Featherman and Robert Hauser, "Changes in Socioeconomic Stratification of the Races, 1962-1973," American Journal of 

Sociology 82 (1976): 621-51. 

6. The 1982 SPPA data set contained several precoded "Other" responses, 

none of which was chosen by even 10 percent of the would-be attenders. 

7. Results for any group are not reported when the base number of respondents -- those "wanting more" of something -- is smaller than 10. 

Results for a given reason are not reported when fewer than 10 percent 

of any group in either year marked that reason as applicable. 

8. In 1982, none of the percentages for Hispanic-Americans is based on 

more than 48 respondents and in 1985, none is based on more than 21. 

Ns for African-Americans ranged from 23 (for opera) to 113 (for jazz 

performance) in 1982; and from 10 (opera) to 59 (jazz) in 1985. 

9. Can we assume that underlying valuations of arts attendance are the same 

for all three groups? The answer to this question is not obvious. The most 

cautious assumption is that the underlying distributions of value that 

African-American, Hispanic, and white respondents place on the activities in which they report wanting to take part are basically similar. On 

the one hand, we have seen in chapter 3 that after controlling for measures 

of educational and economic resources (which can be interpreted as 

measures of economic barriers to participation), African-Americans are 

more likely to attend jazz performances and less likely to attend the other 

activities than white Americans, whereas Hispanic-Americans attend 

119 
Race, Ethnicity, and Participation in the Arts 

most activities at levels not significantly different from those of white 

Americans. A rough inference from these results would be that the 

average African-American values jazz more highly and the other activities less highly than the average white American, and that white and 

Hispanic-Americans value them more or less to the same degree. But the 

figures in this section are based not on average African-American, 

Hispanic, or white respondents but on those who did not attend but said 

that they wanted to do so. Such persons seem likely to value the arts more 

than their peers who neither participated nor wish to participate; and, if 

the speculations about social-desirability bias set out earlier in this 

chapter are correct, such bias may be less important for African-Americans and Hispanics than for whites. Consistent with this hypothesis, 

white respondents tended to give such reasons as procrastination, a lack 

of motivation, or a preference for watching television (each of which we 

regard as evidence of a relatively low valuation of the activity in 

question) more frequently than African-Americans or Hispanics. However, the differences are small and inconsistent. 

Chapter Five 

1. Non-Hispanic respondents whose race was coded as "Other" (including 

Asian-Americans, Native Americans, and those not classifiable) were 

removed from the sample. (There were too few of these respondents for 

most of our purposes and, in any case, the heterogeneity of the category 

would have made any results uninterpretable.) A few respondents for 

whom data on key variables were missing were likewise eliminated. 

Respondents classified as "Other" were not included in these analyses. 

2. Although we undertook all of the analyses reported below on both the 

full November/December subsample and the partial subsample (of respondents reporting data on parental education), in most cases we report 

only the results from the full subsample, because of the nonresponse bias 

problem. For most taste and participation outcomes, parental education 

exerts a small positive influence by virtue of its causal relationship to the 

two socialization measures, which are positively related to participation. 

In other words, because it seems that more educated parents lead their 

children to participate more in the arts as adults because they help them 

have more artistic experiences in their youth (rather than through some 

other means not measured by the socialization scores), we can use the 

120 
Notes 

more reliable full sample without fear that including measures of parental 

education would alter our results. 

3. In Chapter 2, we raised the question of whether the lesser gross differences between African-American and white respondents in television 

viewing than in live attendance were the result of the fact that AfricanAmericans also watched more television, in general, than whites. To 

explore this possibility, we controlled for hours of television viewing of 

all kinds. Although people who watch a great deal of television in general 

also watch significantly more arts television than people who do not, the 

effect is very small and does not explain the relatively high levels of arts 

viewing among African-American respondents. See Appendix Table 5-6 

for the full model. 

4. The full models are displayed in Appendix Tables 5-6 through 5-10. 

5. This finding was unexpected for the performance attendance scale that 

excluded jazz attendance, which African-American respondents reported at higher rates that whites, because the logistic regression analyses 

reported in Chapter 3 revealed that African-American respondents were 

less likely to have attended most of the activities included in the performance attendance scale even after controlling for sociodemographic factors. But although they were statistically significant, these differences 

were small. The apparent difference stems from the difference in sizes 

between the full sample and the November/December subsample. Because the latter is smaller than the former, effects are less likely to be 

statistically significant. To confirm this, we reran logistic models using 

only November/December data. Although the coefficients for race were 

comparable in magnitude to those for the full sample, once sociodemographic controls were added, the effects of race on attendance at performing-arts events (other than jazz) were not statistically significant. We also 

considered and ruled out three alternative explanations for the apparent 

disparity in results. First, we asked if they resulted from systematic 

differences between the November/December subsample and the sample 

for 1982 as a whole. But, as Table 5-1 indicates, African-American/white 

differences in the likelihood of attendance at core performing-arts activities were about as large for the November/December subsample as for 

the 1982 sample as a whole. Moreover, regression analyses to predict 

the performing-arts attendance scales using the full sample (Appendix 

Table 5-5) yielded results that were substantively the same as those from 

the November/December subsample (although the large size of the full 

sample made the tiny effect of race statistically significant). Second, we 

121 
Race, Ethnicity, and Participation in the Arts 

considered the possibility that racial effects might have been altered 

because a somewhat shorter list of control variables was employed in the 

analyses in Chapter 5 than in the analyses in Chapter 3 (due to the 

merging of several occupational, marital, and residential categories). If 

anything, however, this would have magnified the effects of race by 

eliminating variation in control variables with which both race and 

participation are correlated. Third, we considered the possibility that the 

logarithmic form used in the logistic regression analyses in Chapter 3 

better represented the relationship between race and participation than 

the linear models reported above. To test this possibility, we ran the 

models using the logarithmic form of the attendance scale as our dependent variable, and discovered that this transformation made no substantive 

difference to the results. Having eliminated these three alternative explanations, we feel confident in attributing the differe, nce to the smaller size 

of the November/December subsample. Because a sample of 2,255 (the 

size of the November/December subsample) is sufficiently large that no 

substantively important effect could be deemed insignificant, we are 

satisfied with the reliability of these findings. 

6. For more detailed analyses of intercohort differences in the relationship 

between race and participation, see Paul DiMaggio and Francie Ostrower, "Participation in the Arts by Black and White Americans," Social 

Forces 68 (1990): 753-78. 

Chapter Six 

1. We do not include Asian-Americans in this summary because the 

SPPA’s information on this group was so limited.. 

122 
Appendix
 

Appendix Table 2-1
 

Z Scores for Musical Tastes by Racial/Ethnic Group and Year
 

Whites African-Americans Hispanics 

1982 1985 1982 1985 1982 1985 

Classical -0.14 -0.44 -0.44 -0.68 0,18 0.13 

Opera -1.55 -1.68 -0.96 -0.92 -1,36 -1.33 

Show tunes -0.43 -0.47 -0.62 -0.70 -0.59 -0.43 

Jazz -0.51 -0.20 0.95 1.27 0.26 0.84 

Soul/blues -0.62 -0,30 1.87 1.90 0.42 0,37 

Big band 0.31 0.20 -0.30 -0.32 0.05 -0.55 

C&W 2.38 1.95 0.00 -0.05 2.00 1.63 

Bluegrass -0.23 -0.41 -0.99 -1.10 -1,05 -0.94 

Rock 0,39 0.82 0.26 0.16 1.09 1.49 

Easy listening 1,55 1.74 0.02 0.63 1,31 1.17 

Folk -0.25 -0.42 -0.80 -0.64 -0,40 -0.66 

Barbershop -1.09 -1.20 -1.01 -1.10 -1.39 -1.51 

Hymns/gospel 0.21 0.43 2.04 1.58 -0.52 -0.20 

123 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 2-2
 

Percentages Participating in Core Activities by Respondents Who
 

Did and Did Not Watch Such Events on Television, 1982 SPPA
 

Core Item: Jazz Classical 

No Yes Y/N No Yes Y/N 

W 5.64 29.36 5.21 6.56 31.68 4.83 

(N) (2,733) (550) (2,421) (865) 

A 10.70 28.39 2.65 3.66 12.92 3.53 

(N) (269) (97) (308) (58) 

H 4.41 4.66 1.06 1.76 20.49 11.64 

(N) (170) (33) (160) (43) 

W/A odds 0.53 1.03 1.79 2.45 

W/H odds 1.28 6.30 3.73 1.55 

Core Item: 

No 

Opera 

Yes Y/N No 

Musical theater 

Yes Y/N 

W 1.39 11.22 8.07 14.94 42.46 2.84 

(N) (2,863) (423) (2,584) (694) 

A 0.32 2.83 8.84 5.17 27.22 5.26 

(N) (333) (33) (303) (63) 

H 0.48 9.57 19.93 7.68 35.58 4.63 

(N) (183) (20) (167) (36) 

W/A odds 4.34 3.96 2.89 1.56 

W/H odds 2.90 1.17 1.95 1.19 

Core Item: 

No 

Plays 

Yes Y/N No 

Ballet 

Yes Y/N 

W 7.27 25.98 3.57 2.49 16.03 6.44 

(N) (2,375) (909) (2,712) (566) 

A 1.83 18.14 9.91 0.51 2.87 5.63 

(N) (302) (64) (327) (38) 

H 4.37 8.37 1.92 0.49 17.14 34.98 

(N) (173) (30) (172) (31) 

W/A Odds 3.97 1.43 4.88 5.59 

W/H Odds 1.66 3.10 5.08 0.94 

124 
Appendix 

Appendix Table 2-2 (Continued) 

Percentages Participating in Core Activities by Respondents Who
 

Did and Did Not Watch Such Events on Television, 1982 SPPA
 

Core Item: Art 

No Yes Y/N 

W 16.13 47.93 2.97 

(N) (2,492) (781) 

A 9.14 26.64 2.91 

(N) (299) (67) 

H 11.16 44.87 4.02 

(N) (169) (33) 

W/A Odds 1.76 1.80 

W/H Odds 1.45 1.07 

Ns unweighted, percentages weighted. "Yes" refers to respondents who watched relevant television 

programs, "No" to those who did not. Y/N=probability of participation for persons who watched 

programs to those who did not. W/A Odds=probability of participation for whites/probability of 

participation for African-Americans.W/H Odds=probability of participation for whites/probability for 

Hispanics. 

125 
 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 2-3
 

Percentages Participating in Core Activities by Respondents Who
 

Did and Did Not Watch Such Events on Television, 1985 SPPA
 

Core Item: Jazz Classical 

No Yes Y/N No Yes Y/N 

W 6.05 25.59 4.23 6.00 34.55 5.76 

(N) (1,443) (257) (1,263) (446) 

A 2.81 34.27 12.19 4.52 34.25 7.58 

(N) (116) (69) (146) (41) 

H 2.98 24.86 8.34 2.32 28.98 12.49 

(N) (105) (18) (101) (23) 

W/A odds 2.15 .75 1.33 1.01 

W/H odds 2.03 1.03 2.59 1.19 

Core Item: Opera Musical theater 

No Yes Y/N No Yes Y/N 

W 1.33 12.02 9.04 13.44 42.07 3.13 

(N) (1,474) (234) (1,394) (313) 

A 0.00 11.68 NA 4.89 30.96 6.33 

(N) (169) (18) (151) (35) 

H 0.82 6.41 7.82 4.86 28.07 5.78 

(N) (108) (15) (104) (20) 

W/A odds NA 1.03 2.75 1.36 

W/H odds 1.62 1.88 2.77 1.50 

Core Item: Plays Ballet 

No Yes Y/N No Yes Y/N 

W 6.65 28.16 4.23 2.97 16.99 5.72 

(N) (1,299) (406) (1,431) (276) 

A 4.00 14.30 3.58 0.00 14.30 NA 

(N) (150) (36) (155) (32) 

H 3.97 23.41 5.90 1.97 23.34 11.85 

(N) (105) (18) (102) (21) 

W/A Odds 1.66 1.97 NA 1.19 

W/H Odds 1.68 1.20 1.51 0.72 

126 
Appendix 

Appendix Table 2-3 (Continued) 

Percentages Participating in Core Activities by Respondents Who
 

Did and Did Not Watch Such Events on Television, 1985 SPPA
 

Core Item: Art 

No Yes Y/N 

W 16.49 44.09 2.67 

(N) (1,242) (461) 

A 11.04 18,96 1.72 

(N) (143) (44) 

H 8.11 56.30 6.94 

(a) (101) (23) 

W/A Odds 1.49 2.33 

W/H Odds 2.03 0.78 

Ns unweighted, percentages weighted. "Yes" refers to respondents who watched relevant television 

programs, "No"to those who did not. Y/N=probability of participation for persons who watched 

programs to those who did not. W/A Odds=probability of participation for whites/probability of 

participation for African-Americans. W/H Odds=probability of participation for whites/probability for 

Hispanics. 

127 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 2-4
 

Percentage Participating in Core Activities, Respondents with
 

and without Specific Lessons or Classes Before Age 18,
 

1982 SPPA
 

Core Item: Jazz attendance Jazz attendance 

Lesson: Music Music appreciation 

No Yes Y/N No Yes Y/N 

W 4.70 13.22 2.81 6.37 18.56 2.91 

(N) (2,283) (2,301) (3,593) (991) 

A 8.76 33.96 3.87 14.87 34.47 2.32 

(N) (318) (195) (414) (99) 

H 9.18 11.23 1.22 7.69 29.36 3.82 

(N) (240) (65) (276) (29) 

W/A odds 0.54 039 0.43 0.54 

W/H odds 0.51 1.18 0.83 0.63 

Core Item: Classical attendance Classical attendance 

Lesson: Music Music appreciation 

No Yes Y/N No Yes Y/N 

W 7.58 21.45 2.83 10.53 29.34 2.79 

(N) 

A 

(2,287) 

3.98 

(2,301) 

11.62 2.92 

(3,597)

4.17 

(991) 

18.09 4.34 

(N) (318) (195) (414) (99) 

H 4.42 12.66 2.86 3.79 31.32 8.26 

(N) (240) (65) (276) (29) 

W/A odds 1.90 1.85 2.53 1.62 

W/H odds 1.71 1.69 2.78 0.94 

Core Item: 

Lesson: 

Opera 

Music 

Opera 

Music appreciation 

No Yes Y/N No Yes Y/N 

W 2.00 3.81 1.91 2.17 5.64 2.60 

(N) 

A 

(2,286) 

0.21 

(2,301) 

1.79 8.52 

(3,597) 

0.44 

(990) 

2.42 5.50 

(N) 

H 

(318) 

1.42 

(195) 

1.44 1.01 

(414) 

0.54 

(99) 

10.39 19.24 

(N) (240) (65) (276) (29) 

W/A Odds 9.52 2.13 4.93 2.33 

W/H Odds 1.41 2.65 4.02 0.54 

128
 
Appendix 

Appendix Table 2-4 (Continued)
 

Percentage Participating in Core Activities, Respondents with
 

and without Specific Lessons or Classes Before Age 18,
 

1982 SPPA 

Core Item: Musical Musical 

Lesson: 

No 

Music 

Yes Y/N 

Music appreciation 

No Yes Y/N 

W 13.65 27.50 2.01 15.91 37.89 2.38 

(N) (2,287) (2,302) (3,598) (991) 

A 5.05 18.31 3.63 6.75 24.38 3.61 

(N) 

H 

(318) 

6.25 

(195) 

14.54 2.33 

(414) 

5.23 

(99) 

37.20 7.11 

N 

W/A Odds 

(240) 

2.70 

(65) 

1.50 

(276) 

2.36 

(29) 

1.55 

W/H Odds 2.18 1.89 3.04 1.02 

Core Item: Musical Plays 

Lesson: Acting Acting 

No Yes Y/N No Yes Y/N 

W 18.01 44.53 2.47 11.34 29.55 2.61 

(N) 

A 

(4,139) 

9.52 

(450) 

22.72 2.39 

(4,138) 

4.24 

(449) 

14.69 3.46 

(N) 

H 

(481) 

7.36 

(32) 

17.55 2.38 

(481) 

3.22 

(32) 

12.51 3.89 

(N) 

W/A Odds 

(282) 

1.89 

(23) 

1.96 

(282) 

2.67 

(23) 

2.01 

W/H Odds 2.45 2.54 3.52 2.36 

Core Item: Art exhibits Art exhibits 

Lesson: Art Crafts 

No Yes Y/N No Yes Y/N 

W 15.39 45.43 2.95 16.28 36.42 2.24 

(N) 

A 

(3,441) 

9.37 

(1,144) 

33.22 3.55 

(3,065) 

6.70 

(1,519) 

35.92 5.36 

(N) 

H 

(426) 

12.54 

(88) 

35.10 2.80 

(396) 

12.11 

(118) 

33.56 2.77 

(N) 

W/A Odds 

(256) 

1.64 

(49) 

1.37 

(246) 

2.43 

(59) 

1.01 

W/H Odds 1.25 1.29 1.34 1.09 

129 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 2-4 (Continued)
 

Percentage Participating in Core Activities, Respondents with
 

and without Specific Lessons or Classes Before Age 18,
 

1982 SPPA
 

Core Item: Art exhibits Ballet 

Lesson: Art appreciation Ballet 

No Yes Y/N No Yes Y/N 

W 16.11 49,50 3.07 2.65 22.89 8.64 

(N) 

A 

(3,647) 

9.53 

(938) 

36.39 3.82 

(4,215) 

1.23 

(374) 

15.14 12.31 

(N) 

H 

(437) 

12.16 

(77) 

50.52 4.15 

(493) 

2.19 

(21) 

32.44 14.81 

(N) (272) (33) (294) (11) 

W/A Odds 1.69 1.36 2.15 1.51 

W/H Odds 1.32 0.98 1.21 0.71 

Core Item: Reading literature 

Lesson: Creative writing 

No Yes Y/N 

W 55.82 84.38 1.51 

(N) (3,694) (879)
 

A 37.18 82.59 2.22
 

(N) (445) (68)
 

H 32.69 60.82 1.86
 

(N) (266) (37)
 

W/A Odds 1.50 1.02
 

W/H Odds 1.71 1.39
 

Ns unweighted, percentages weighted. Y/N=probability of participation for persons who have taken 

lessons/probability for those who have not. W/A Odds=probability of participation for whites/probability 

of participation for African-Americans. W/H Odds=probability of participation for whites/probability for 

Hispanics. 

130 
 

Appendix 

Appendix Table 2-5
 

Percentage Participating in Core Activities, Respondents with
 

and without Specific Lessons or Classes Before Age 18,
 

1985 SPPA
 

Core Item: Jazz attendance Jazz attendance 

Lesson: Music Music appreciation 

No Yes Y/N No Yes Y/N 

W 5.45 15.52 2.85 7.38 22.21 3.00 

(N) (928) (993) (1,482) (439) 

A 8.12 16.99 2.09 7.16 32.15 4.49 

(N) (122) (77) (166) (33) 

H 0.57 14.56 25.54 2.55 22.72 8.91 

(N) (105) (37) (129) (13) 

W/A odds 0.67 0.93 1.03 0.69 

W/H odds 9.56 1.07 2.89 0.98 

Core Item: Classical attendance Classical attendance 

Lesson: Music Music appreciation 

No Yes Y/N No Yes Y/N 

W 7.34 24.19 3.30 10.88 34.18 3.14 

(N) (929) (992) (1,482) (439) 

A 2.39 9.29 3.89 3.90 10.09 2.59 

(N) (122) (77) (166) (33) 

H 1.68 31.60 18.81 7.78 22.91 2.94 

(N) (106) (37) (130) (13) 

W/A odds 3.07 2.60 2.79 3.39 

W/H odds 4.37 0.77 1.40 1.49 

Core Item: 

Lesson: 

No 

Opera 

Music 

Yes Y/N 

Opera 

Music appreciation 

No Yes Y/N 

W 1.71 4.51 2.64 2.23 6.43 2.88 

(N) (928) (992) (1,481) (439) 

A 0.00 3.56 NA 0.00 7.76 NA 

(N) (122) (77) (166) (33) 

H 0.00 2.24 NA 0.58 0.00 0.00 

(N) (105) (37) (129) (13) 

W/A Odds NA 1.27 NA 0.85 

W/H Odds NA 2.01 3.84 NA 

131 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 2-5 (Continued)
 

Percentage Participating in Core Activities, Respondents with
 

and without Specific Lessons or Classes Before Age 18,
 

1985 SPPA
 

Core Item: Musical Musical 

Lesson: Music Music appreciation 

No Yes Y/N No Yes Y/N 

W 10.80 26.25 2.43 14.39 34.17 2.37 

(N) (929) (991) (1,481) (439) 

A 7.59 11.69 1.54 6.36 22.56 3.55 

(N) (122) (77) (166) (33) 

H 3.46 18.92 5.47 5.48 29.60 5.40 

(N) (106) (37) (130) (13) 

W/A Odds 1.42 2.25 2.26 1.51 

W/H Odds 3.12 1.39 2.63 1.15 

Core Item: 

Lesson: 

Musical 

Acting 

Plays 

Acting 

No Yes Y/N No Yes Y/N 

W 15.84 42.24 2.67 11.57 33.56 2.90 

(N) (1,714) (206) (1,715) (207) 

A 8.65 14.04 1.62 4.41 15.79 3.58 

(N) (182) (17) (181) (17) 

H 6.58 18.93 2.88 6.58 0.00 0.00 

(N) (133) (10) (133) (10) 

W/A Odds 1.83 3.01 2.62 2.13 

W/H Odds 2.41 2.23 1.76 NA 

Core Item: Art exhibits Art exhibits 

Lesson: Art Crafts 

No Yes Y/N No Yes Y/N 

W 16.26 46.46 2.86 10.57 37.53 3.55 

(N) 

A 

(1,383) 

4.25 

(538) 

30.71 7.23 

(1,183) 

6.40 

(738) 

14.93 2.33 

(N) 

H 

(161) 

17.91 

(38) 

36.89 2.06 

(140) 

19.05 

(59) 

25.46 1.34 

(N) (123) (20) (116) (27) 

W/A Odds 3.83 1.51 1.65 2.51 

W/H Odds 0.91 1.26 0.55 1.47 

132
 
Appendix 

Appendix Table 2-5 (Continued)
 

Percentage Participating in Core Activities, Respondents with
 

and without Specific Lessons or Classes Before Age 18,
 

1985 SPPA
 

Core Item: Art exhibits Ballet 

Lesson: Art appreciation Ballet 

No Yes Y/N No Yes Y/N 

W 16.37 54.98 3.36 3.56 18.40 5.17 

(N) 

A 

(1,492) 

4.93 

(429) 

28.00 5.68 

(1,731) 

1.14 

(191) 

14.38 12.61 

(N) (166) (33) (193) (6) 

H 18.63 39.15 2.10 2.95 0.00 0.00 

(N) (133) (10) (137) (6) 

W/A Odds 3.32 1.96 3.12 1.28 

W/H Odds 0.88 1.40 1.21 NA 

Core Item: Reading literature 

Lesson: Creative writing 

No Yes Y/N 

W 53.45 90.37 1.69 

(N) (1,508) (4!0)
 

A 38.55 62.99 1.62
 

(N) (173) (25)
 

H 36.04 89.18 2.47
 

(N) (138) (5)
 

W/A Odds 1.39 1.43
 

W/H Odds 1.48 1.01
 

Ns unweighted, percentages weighted. Y/N=probability of participation for persons who have taken 

lessons/probability for those who have not. W/A Odds=probability of participation for whites/probability 

of participation for African-Americans. W/H Odds=probability of participation for whites/probability for 

Hispanics. 

133
 
 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 3-1
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1982 Disaggregated Subsamples: Whites (W),
 

African-Americans (A), and Hispanics (H) 

Attend jazz Attend Attend 

concerts classical concerts opera 

W A H W A H W A H 

WOMEN 

b .101 -.451 -.026 .650 .226 .066 .444 .521 1.573 

se .065 .158 .252 .057 .228 .260 .107 .518 .558 

s~g NS a NS d NS NS d NS a 

SMSA 

b .373 .658 -.318 .107 .602 .453 .666 .357 -.387 

se .077 .207 .341 .062 .310 .453 .139 .686 .702 

slg d a NS NS NS NS d NS NS 

AGE 

b -.028 -.041 -.028 .016 .018 .003 .031 -.012 .013 

se .003 .007 .012 .002 .008 .010 .003 .022 .019 

slg d d a d a NS d NS NS 

EDUC 

b .216 .235 .083 .335 .274 .191 .250 .385 .427 

se .015 .038 .046 .012 .048 .049 .022 .120 .101 

s~g d d NS d d c d a d 

INC 

b .073 .002 .071 .114 .037 .142 .200 .325 .143 

se .021 .065 .095 .018 .088 .095 .032 .158 .163 

sig b NS NS d NS N,S d a NS 

OCC 

b .184 .422 .838 .252 ,546 .463 .392 .519 .063 

se .072 .178 .282 .061 .258 .287 .121 .628 .512 

sig a a a d a NS a NS NS 

MARIT 

b .810 .236 .010 .467 .736 .602 .773 .031 .753 

se .073 .172 .290 .067 .245 .293 .124 .550 .536 

sig d NS NS d a a d NS NS 

INT 4.98 -3.66 -2.52 -7.89 -7.93 -5.8;3 -9.85 -10.58 -10.72 

134 
Appendix 

Appendix Table 3-1 (Continued)
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1982 Disaggregated Subsamples: Whites (W),
 

African-Americans (A), and Hispanics (H) 

Attend Attend Attend 

musical play ballet 

W A H W A H W A H 

WOMEN 

b .583 -.139 .510 .581 -.050 -.175 1.101 .960 1.202 

se .049 .186 .235 .058 .240 .316 .097 .477 .394 

s~g d NS a d NS NS d a a 

SMSA 

b .482 .659 .737 .202 1.266 .226 .617 1.155 8.073 

se .055 .258 .427 .064 .423 .539 .114 .705 * 

s~g d a NS a a NS d NS * 

AGE 

b .009 .001 -.001 .013 .017 .009 .010 -.032 .019 

se .002 ,007 .009 .002 .009 .012 .003 .020 .014 

s~g d NS NS d NS NS b NS NS 

EDUC 

b .241 .219 .189 .288 .211 .275 .283 .462 .380 

se .010 .041 .044 .012 .051 ,064 .019 .106 .077 

s~g d d d d d d d d d 

INC 

b .189 .262 .197 .187 .256 .146 .112 ,032 .211 

se .016 .068 .086 .018 .086 .111 .028 .167 .131 

s~g d c a d a NS d NS NS 

OCC 

b .400 .314 .644 .459 .310 .738 .471 -.088 .769 

se .053 ,214 .255 .063 .277 .351 .102 .493 .399 

slg ci NS a d NS a d NS NS 

MARIT 

b .271 .184 .360 .504 .582 .145 .525 .668 .645 

se .059 .206 .263 .063 .264 .366 .104 ,458 .415 

s~g d NS NS d a NS d NS NS 

INT -6.25 -6.02 -5.91 -7.54 -7.92 -7.22 -9.12 -10.94 -18.09 

135 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 3-1 (Continued)
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1982 Disaggregated Subsamples: Whites (W),
 

African-Americans (A), and Hispanics (H) 

Visit art museum Perform: Play Perform: Act, 

or gallery musical instrument sing, or dance 

W A H W A H W A C 

WOMEN 

b .436 -.157 .101 .011 .046 .237 .300 .069 .295 

se .047 .177 .202 .091 .293 .424 .086 .248 .420 

sig d NS NS NS NS NS b NS NS 

SMSA 

b .245 1.364 -.071 -.006 -.522 8.080 -.061 -.190 7.959 

se .051 .297 .298 .099 .304 * .092 ~274 * 

sig d d NS NS NS * NS NS * 

AGE 

b .001 -.000 -.012 -.011 -.001 -.018 -.020 -.016 -.020 

se .002 .007 .009 .003 .011 .018 .003 .010 .018 

sig NS NS NS b NS NS d NS NS 

EDUC 

b .320 .279 .279 .106 .091 .001 .112 .084 -.072 

se .011 .040 .042 .019 .057 .067 .019 .050 .065 

sig d d d d NS NS d NS NS 

INC 

b .115 .152 .226 -.089 .072 -.145 -.062 .042 .202 

se .015 .068 .076 .033 .117 .199 .030 .100 .166 

sig d a a a NS NS a NS NS 

OCC 

b .255 .710 .444 -.055 .161 .65,7 .209 .403 .906 

se .050 .197 ,219 .103 .343 .488 ,095 .282 .488 

sig d b a NS NS NS a NS NS 

MARIT 

b .415 .194 .019 .418 .515 .018 .245 .275 .444 

se .056 .193 .234 .105 .325 .47’8 .099 .273 .473 

sig d NS NS d NS NS a NS NS 

INT -6.29 -7.07 -5.02 -3.96 -4.40 -10.98 -3.80 -3.58 -10.94 

136 
 

Appendix 

Appendix Table 3-1 (Continued)
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1982 Disaggregated Subsamples: Whites (W),
 

African-Americans (A), and Hispanics (H)
 

Read novels, short stories, 

poems, or plays 

W A H 

WOMEN 

b .889 .552 .496 

se .041 .123 .156 

s~g d d a 

SMSA 

b .085 .310 -.120 

se .043 .137 .219 

s~g a a NS 

AGE 

b .002 -.014 -.004 

se .001 .004 .006 

sig NS a NS 

EDUC 

b .288 .204 .222 

se .009 .026 .028 

sig d d d 

INC 

b .079 .126 .034 

se .015 .053 .065 

sig d a NS 

OCC 

b .225 .711 .411 

se .047 .146 .183 

sig d d a 

MARIT 

b .245 .261 .029 

se .052 .134 .183 

sig d NS NS 

INT -4.03 -3.09 -3.15 

Notes: b is the unstandardized logistic regression coefficient, se is the standard error, sig refers to the level of 

statistical significance, where a=probability less than .05, b=-probability less than .01, c=probability less than .001, 

c=probabitity less than .00005, and NS= not significant. Variables are defined in the text. The coefficients and 

standard errors for INC are multiplied by 10,000 for purposes of display. *=The program does not compute reliable 

standard errors and significance tests for coefficients of this magnitude. 

137 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 3-2
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1985 Disaggregated Subsamples:
 

Whites (W), African-Americans (A), and Hispanics (H)
 

Attend jazz Attend Attend 

concerts classical concerts opera 

W A H W A HI W A H 

WOMEN 

b .143 -.491 -.161 .542 .336 .276 .473 .156 -1.415 

se .072 .182 .316 .064 .256 .315 .125 .501 1.262 

sig a a NS c NS NS c NS NS 

SMSA 

b .359 .358 -.388 .165 .090 .269 .099 8.227 7.111 

se .088 .232 .403 .072 .331 .474 .147 * * 

s~g c NS NS a NS N:S NS * * 

AGE 

b -.024 -.034 -.010 .016 .024 .012 .019 .029 -.032 

se .003 .008 .014 .002 .009 .012 .004 .016 .054 

sig c c NS c a NS c NS NS 

EDUC 

b .265 .235 .175 .342 .280 .369 .320 .361 .214 

se .017 .043 .059 .014 .051 .065 .027 .103 .215 

sig c c a c c c c b NS 

INC 

b .081 .230 -.014 .103 .268 .100 .133 .031 .470 

se .021 .061 .112 .018 .079 ,102 .034 .169 .267 

sig c b NS c b NS c NS NS 

OCC 

b .193 -.340 .429 .299 .068 -.592 .549 .345 7.805 

se .082 .214 .349 .071 .280 .354 .150 .561 * 

sig a NS NS c NS NS b NS * 

MARIT 

b .548 .132 .040 .477 .816 .337 .431 .819 -.155 

se .083 .200 .348 .076 .277 .350 .147 .536 1.135 

s~g c NS NS c a NS a NS NS 

INT -5.72 -3.97 -4.12 -8.08 --8.31 -7.97 -9.92 -18.67 -21.56 

138 
Appendix 

Appendix Table 3-2 (Continued)
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1985 Disaggregated Subsamples:
 

Whites (W), African-Americans (A), and Hispanics (H)
 

Attend Attend Attend 

musical play ballet 

W A H W A H W A H 

WOMEN 

b .513 .560 ,186 .436 .285 .189 .980 .198 -.161 

se .057 .233 .284 .065 .269 .325 .105 .416 .429 

slg d a NS d NS NS d NS NS 

SMSA 

b .593 .636 -.021 .402 .594 .111 .233 8.544 -.084 

se .067 ,353 .417 .077 .393 .477 .120 * .600 

s~g d a NS d NS NS NS * NS 

AGE 

b .007 .014 .023 .009 .009 ,021 .004 .006 -.002 

se .002 .008 .011 .002 .010 .012 .003 .014 .019 

slg d NS a d NS NS NS NS NS 

EDUC 

b ,217 ,255 ,394 .294 ,372 ,251 ,318 ,259 ,205 

se .012 .046 ,060 .014 .059 .061 .022 .082 .082 

s~g d d d d d d d a a 

INC 

b .162 .188 .089 .117 .226 .126 .125 ,016 .170 

se .016 .072 .093 .018 .083 ,105 .027 .143 .133 

s~g d a NS d a NS d NS NS 

OCC 

b .377 .492 .448 .414 -.180 -.080 .287 .744 .311 

se .063 .242 .308 .073 ,296 .363 .115 .453 .479 

s~g d a NS d NS NS a NS NS 

MARtT 

b .244 .458 -.071 .415 .712 .304 .445 -.726 ,106 

se .069 .242 .323 .077 .290 .363 .115 .482 .477 

slg a NS NS d a NS c NS NS 

INT -6.11 -7.88 -6.35 -7.45 -9.25 -6.97 --8.94 -15.93 -6.12 

139 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 3-2 (Continued)
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1985 Disaggregated Subsamples:
 

Whites (W), African-Americans (A), and Hispanics (H)
 

Visit art museum 

or gallery 

Perform: Play 

musical instrument 

Perform: Act, 

sing, or dance 

W A H W A H W A H 

WOMEN 

b .383 .276 .141 -.147 .051 -1.185 .240 .129 -.258 

se .052 .203 .203 .124 .433 .60,4 .103 .326 .471 

s~g d NS NS NS NS a a NS NS 

SMSA 

b .495 .362 -.083 -.483 .154 -.125 196.278 .020 8.004 

se .060 .269 .286 .131 .533 .687 .109 .396 * 

s~g d NS NS b NS NS a NS * 

AGE 

b -.001 -.007 .007 -.023 -.042 6.026 -.016 .003 -.066 

se .002 .008 .008 .005 .020 .026 .004 .012 .029 

s~g NS NS NS d a NS d NS a 

EDUC 

b .312 .272 .155 .179 .058 .15,3 .143 .101 -.037 

se .012 .044 .037 .028 .095 .097 .022 .064 .084 

slg d d d d NS NS d NS NS 

INC 

b .097 .208 .114 .090 .017 .019 -.056 .084 -.031 

se .015 .065 .072 .039 .154 .180 .032 .112 .173 

s~g d a NS a NS NS NS NS NS 

OCC 

b .257 .385 .688 .412 .743 .058 .348 .413 .820 

se .058 .217 .224 .143 .466 .585 .117 .360 .537 

slg d NS a a NS NS a NS NS 

MARIT 

b .297 .252 .125 .155 -.104 .149 .101 .631 .074 

se .063 .218 .228 .143 .471 .571 .120 .356 .532 

sig d NS NS NS NS NS NS NS NS 

INT -6.23 -6.34 -3.98 -4.64 -3.58 -4.26 -4.35 -5.33 -9.10 

140 
 

Appendix 

Appendix Table 3-2 (Continued)
 

Logistic Regression Analyses Predicting Participation in Core
 

Activities for 1985 Disaggregated Subsamples:
 

Whites (W), African-Americans (A), and Hispanics (H)
 

Read novels, short stories, 

poems, or plays 

W A H 

WOMEN 

b .912 .362 .595 

se .046 .127 .171 

sig d a b 

SMSA 

b .122 .797 .119 

se .048 .155 .239 

sig a d NS 

AGE 

b .002 -.007 .013 

se .001 .004 .007 

sig NS NS a 

EDUC 

b .24O .171 .187 

se .010 .026 .029 

sig d d d 

INC 

b .091 .069 .102 

se .015 .050 .066 

sig c NS NS 

OCC 

b .290 .648 .776 

se .052 .152 .193 

stg d d c 

MARIT 

b .101 .031 .234 

se .057 .143 .193 

sig NS NS NS 

INT -3.60 -3.10 -3.72 

Notes: b is the unstandardized logistic regression coefficient, se is the standard error, sig refers to the level of 

statistical significance, where a=probability less than .05, b=probability less than .01, c=probability less than .001, 

c=probability less than .00005, and NS=not significant. Variables are defined in the text. The coefficients and 

standard errors for INC are multiplied by 10,000 for purposes of display. *=Program does not compute reliable 

standard errors or significance statistics when regression coefficients are this high. 

141 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 4-1
 

Weighted Percentages of Respondents Who Wished to Attend
 

Jazz Music Performances More, Citing Selected Reasons for Not
 

Doing So: Whites (W), African-Americans (A), and Hispanics (H)
 

p

Attended during 

revious 12 months 

Did not attend during 

previous12 months 

W A H W A H 

1982 

Tickets sold out 3.96 4.77 14.87 1.18 0.80 0.00 

Cost 31.35 59.05 34.14 25.62 45.05 39.94 

Not available 29.07 16.66 31.52 22.43 12.67 14.06 

Child care 3.80 8.90 12.87 7.94 8.26 11.49 

Too far to go 13.98 2.02 20.04 15.59 7.00 12.95 

Transportation 7.28 10.91 28.47 5.66 13.75 6.35 

Fear crime 0.66 0.00 0.00 2.89 5.17 0.00 

Lack motivation 8.33 6.11 14.08 13.85 9.53 11.12 

Too little time 42.97 37.83 29.52 41.39 24.20 37.22 

N (unweighted) 220 55 15 532 113 39 

1985 

Tickets sold out 0.87 3.90 NA 1.40 1.23 0.00 

Cost 21.68 51.31 NA 28.63 39.26 54.62 

Not available 24.25 30.81 NA 23.43 12.73 15.56 

Child care 8.69 8.76 NA 10.97 2.57 21.15 

Too far to go 15.13 9.30 NA 14.22 5.75 0.00 

Transportation 5.74 22.93 NA 5.20 7.56 2.68 

Fear crime 2.71 11.42 NA 1.12 3.52 4.04 

Lack motivation 11.05 0.00 NA 14.88 3.62 31.32 

Too little time 47.23 19.83 NA 45.16 41.48 30.54 

N (unweighted) 102 20 4 241 59 21 

In 1985, too few Hispanic attenders reported wanting to go more to report statistics. Fewer than 10 

percent of any group reported discomfort, no one to go with, handicap, poor quality, publicity, workrelated reasons, performance times, or transience. 

142 
 

Appendix 

Appendix Table 4-2
 

Weighted Percentages of Respondents Wishing to Attend
 

Classical Music Performances More, Citing Selected Reasons for
 

Not Doing So: Whites (W), African-Americans (A),
 

and Hispanics (H)
 

Attended during Did not attend during 

previous 12 months previous 12 months 

W A H W A H 

1982 

Cost 32.83 34.71 55.96 28.30 43.96 48.43 

Not available 21.44 0.00 8.92 23.27 14.32 8.07 

No one to go with 7.63 9.61 19.11 7.18 6.40 2.31 

Child care 5.28 21.98 0.00 7.51 9.96 8.66 

Handicap 2.32 0.00 8.78 10.04 7.81 2.88 

Too far to go 17.24 0.00 15.76 15.02 12.31 19.69 

Transportation 7.19 8.00 19.11 8.15 20.50 15.43 

Lack motivation 11.79 17.61 9.00 14.71 6.73 3.18 

Too little time 41.40 35.30 16.13 39.10 34.53 32.96 

N (unweighted) 303 14 10 552 48 36 

1985 

Cost 22.93 NA NA 30.08 23.53 NA 

Not available 18.34 NA NA 23.79 3.76 NA 

No one to go with 9.14 NA NA 5.83 8.32 NA 

Child care 7.65 NA NA 10.17 10.74 NA 

Handicap 3.27 NA NA 6.43 3.03 NA 

Too far to go 11.50 NA NA 25.46 10.28 NA 

Transportation 5.76 NA NA 8.55 16.86 NA 

Lack motivation 16.42 NA NA 12.06 9.50 NA 

Too little time 51.06 NA NA 34.70 47.98 NA 

N (unweighted) 130 7 4 207 23 9 

In 1985, too few African-American and Hispanic attenders and Hispanic nonattenders reported 

wanting to go more to report statistics. Fewer than 10 percent of any group reported tickets sold out, 

discomfort, crime, poor quality, publicity, work-related reasons, performance times, or transience as 

reasons for not attending. 

143 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 4-3
 

Weighted Percentages of Respondents Wishing to Attend Opera
 

Performances More, Citing Selected Reasons for Not Doing So:
 

Whites (W), African-Americans (A), and Hispanics (H)
 

p

Attended during 

revious 12 months 

Did not attend during 

previous 12 months 

W A H W A H 

1982 

Cost 38.47 NA NA 34.55 38.52 68.01 

Not available 

No one to go with 

Handicap 

Too far to go 

Transportation 

Lack motivation 

32.95 

11.68 

4,32 

14.15 

9.84 

7.02 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

25.98 

9.22 

10.56 

17.40 

8.39 

10.34 

8.63 

3.30 

2.09 

12.27 

11.52 

10.28 

6.82 

11.98 

7.24 

36.14 

7.24 

0.00 

Too little time 20.21 NA NA 30.27 30.48 15.05 

N (unweighted) 50 1 1 311 23 14 

1985 

Cost 43.54 NA NA 36.59 8.99 NA 

Not available 17.55 NA NA 14.31 10.87 NA 

No one to go with 3.56 NA NA 6.38 5.68 NA 

Handicap 0.00 NA NA 5.42 0.00 NA 

Too far to go 16.14 NA NA 25.97 13.59 NA 

Transportation 4.51 NA NA 13.00 30.16 NA 

Lack motivation 4.61 NA NA 16.49 0.00 NA 

Too little time 56.36 NA NA 33.48 61.20 NA 

N (unweighted) 21 2 0 141 10 7 

In 1982 and 1985, too few African-American and Hispanic attenders, and in 1985 too few Hispanic nonattenders, 

reported wanting to go more to report statistics. Fewer than 10 percent of any group reported tickets sold out, 

discomfort, child care, crime, poor quality, publidty, work-related reasons, performance times, or transience as 

reasons for not attending. 

144 
 

Appendix 

Appendix Table 4-4
 

Weighted Percentages of Respondents Wishing to Attend Musical
 

Theater Performances More, Citing Selected Reasons for Not
 

Doing So: Whites (W), African-Americans (A), and Hispanics (H)
 

Attended during Did not attend during 

previous 12 months previous 12 months 

W A H W A H 

1982 

Cost 36.56 55.08 62.86 30.93 47.08 37.41 

Not available 22.75 13.90 19.15 21.02 11.85 13.12 

No one to go with 6.92 9.33 7.14 8,79 3.09 8,81 

Child care 6.09 10.98 3,18 7.58 11,68 16.15 

Too far to go 15.65 5,26 15.98 15.95 4.95 29,42 

Transportation 7.42 4.46 8.92 7.56 8.18 17.40 

Fear crime 2.75 7.49 3.95 3.57 3.4! 5.17 

Lack motivation 10,79 24.01 3.99 12.07 12.18 9.44 

Too little time 36.58 44.78 33.08 36.52 29.30 32.90 

N (unweighted) 620 24 23 969 81 44 

1985 

Cost 28.83 53.27 NA 32.10 43,48 53.39 

Not available 17,86 13.47 NA 19.07 15.20 0.00 

No one to go with 5.81 4.81 NA 5.55 12,04 14.46 

Child care 4,99 0,00 NA 10.33 7.07 17.07 

Too far to go 16.31 0.00 NA 18.84 15.40 5.99 

Transportation 7,26 4.29 NA 8.83 14.24 0,00 

Fear crime 2.35 0.00 NA 2.95 12.24 0.00 

Lack motivation 13.19 10.17 NA 15.14 2.95 14.38 

Too little time 47,05 33.31 NA 34.07 25,51 37.28 

N (unweighted) 247 17 5 373 40 15 

In 1985, too few Hispanic attenders reported wanting to go more to report statistics. Fewer than 10 percent of 

any group reported tickets sold out, discomfort, handicap, poor quality, publicity, work-related reasons, performance times, or transience as reasons for not attending. 

145 
 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 4-5
 

Weighted Percentages of Respondents Wishing to Attend Plays
 

More, Citing Selected Reasons for Not Doing So: Whites (W),
 

African-Americans (A), and Hispanics (H)
 

Attended during Did not attend during 

previous 12 months previous 12 months 

W A H W A 

1982 

Cost 30.83 69.64 NA 31.10 24.18 43.63 

Not available 22.32 7.81 NA 19.59 20.23 10.72 

Child care 5.90 0.00 NA 8.49 13.64 9.50 

Handicap 2.79 11.45 NA 5.34 3.91 0.00 

Too far to go 14.91 8.69 NA 15.35 9.93 6.07 

Transportation 5.79 12.08 NA 5.98 8.51 5.93 

Fear crime 1.52 11.45 NA 3.20 0.00 3.45 

Poor quality 5.18 0.00 NA 3.27 10.29 0.00 

Lack motivation 11.33 13.20 NA 13.85 10.12 11.53 

Too little time 41.17 42,89 NA 38.68 14.80 40.82 

N (unweighted) 364 15 NA 852 48 27 

1985 

Cost 28.32 43.07 NA 25.14 37.64 60.19 

Not available 22.01 18.70 NA 21.39 9.54 0,00 

Child care 8.87 8.06 NA 7.40 7,96 5.76 

Handicap 2.58 0.00 NA 3.82 4.73 0.00 

Too far to go 14,44 10.63 NA 17.25 4.14 0.00 

Transportation 5.78 10.63 NA 5.08 13.51 5.82 

Fear crime 3.30 8.06 NA 1,61 4.14 0.00 

Poor quality 6.37 4.66 NA 1.15 0.00 0.00 

Lack motivation 12.23 0.00 NA 12.81 2.41 25.30 

Too little time 43.38 21.54 NA 39.10 38.72 50.91 

N (unweighted) 149 12 1 358 24 13 

In 1982 and 1985, too few Hispanic attenders reported wanting to go more to report statistics. Under 10 percent 

of any group reported tickets sold out, discomfort, no one to go with, publicity, work-related reasons, performance 

times, or transience. 

146 
Appendix 

Appendix Table 4-6
 

Weighted Percentages of Respondents Wishing to Attend Ballet
 

Performances More, Citing Selected Reasons for Not Doing So:
 

Whites (W), African-Americans (A), and Hispanics (H)
 

p

Attended during 

revious 12 months 

Did not attend during 

previous 12 months 

W A H W 

1982 

Cost 43.21 NA NA 28.98 42.93 45.93 

Not available 

No one to go with 

Child care 

27.91 

8.15 

6.07 

NA 

NA 

NA 

NA 

NA 

NA 

27,08 

11,96 

7,22 

13,90 

6,97 

11,62 

16.33 

12.85 

16,72 

Handicap 

Too far to go 

Transportation 

Fear crime 

Lack motivation 

3.00 

10.91 

8.37 

1,76 

3.12 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

8.27 

15.88 

7.74 

2.84 

13.35 

3,09 

13,61 

10,69 

0,00 

2.61 

10.01 

20.38 

17,29 

14.32 

21.39 

Too little time 

N (unweighted) 

27,35 

100 

NA 

2 

NA 

4 

32.23 

468 

32.72 

31 

26.47 

22 

1985 

Cost 

Not available 

No one to go with 

Child care 

23.60 

26.81 

8.71 

8.26 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

33.31 

17.72 

10.90 

11.23 

36,98 

0,00 

9.07 

6.19 

43.72 

7.50 

14.03 

12.60 

Handicap 

Too far to go 

Transportation 

Fear crime 

1.87 

10.61 

1.94 

0.00 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

5.89 

22,11 

6.93 

3.18 

0.00 

5.65 

0.00 

11.84 

0.00 

15.63 

5.43 

0.00 

Lack motivation 

Too little time 

N (unweighted) 

8.26 

42,47 

45 

NA 

NA 

5 

NA 

NA 

2 

14.20 

35,29 

204 

0,00 

51.09 

16 

9.05 

28,31 

16 

In 1982 and 1985, too few African-American and Hispanic attenders reported wanting to go more to report 

statistics. Under 10 percent of any group reported tickets sold out, discomfort, poor quality, publicity, work-related 

reasons, performance times, or transience. 

147 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 4-7
 

Weighted Percentages of Respondents Wishing to Attend Art
 

Museums and Galleries More, Citing Selected Reasons for Not
 

Doing So: Whites (W), African-Americans (A), and Hispanics (H)
 

Attended during Did not attend during 

previous 12 months previous 12 months 

W A H W A H 

1982 

Cost 6.95 7.40 28.98 10,73 22.66 0.00 

Not available 25.09 5.79 19.00 24.81 15.31 7.11 

No one to go with 5.23 2.99 10.22 5.97 6.62 9.67 

Child care 3.49 15.86 4.69 5.44 6.46 15.43 

Too far to go 16.96 5.05 28.05 20.25 10.46 5.85 

Transportal~on 5.23 22.31 6.97 6.46 11.68 13.21 

Lack mo~vation 14.58 13.34 2.81 12.84 17.76 13.19 

Too little time 51.01 51.80 67.86 40.12 30.85 47.33 

N (unweighted) 606 26 40 812 89 48 

1985 

Cost 9.40 11.07 11.00 13.78 17.37 29.65 

Not available 20.04 0.00 16.61 23.98 15.09 0.00 

No one to go with 2.39 20.42 9.98 6.74 5.37 0.00 

Child care 5.79 0.00 5.92 5.39 3.60 8.54 

Too far to go 25.20 15.51 7.81 21.28 6.80 8.96 

Transportation 6.30 14.82 3.33 10.70 18.94 14.82 

Lack motivation 14.32 0.00 21.71 16.75 7.94 34.49 

Too little time 48.29 33.72 45.77 38.90 52.72 74.05 

N (unweighted) 274 52 21 323 20 18 

Under 10 percent of any group reported tickets sold out, discomfort, handicap, crime, poor quality, publicity, workrelated reasons, performance times, or transience. 

148 
Appendix 

Appendix Table 5-1
 

Results of Factor Analysis of Core and Other Activity
 

Participation Measures: Rotated Factor Loadings
 

Factors 

Variables 

Attend jazz .018 .407 .343 .060 

Attend classical .307 .551 .029 .108 

Attend opera -.031 .479 .001 .039 

Attend musical .360 .573 -.019 .047 

Attend play .272 .607 .040 .064 

Attend ballet .003 .602 .151 .054 

Visit art exhibit .599 .341 .172 -.018 

Perform on 

instrument .049 -.002 -.045 .716 

Perform: act, 

sing, dance .057 .002 .002 .777 

Read novels, etc. .481 .148 .210 .044 

Visit science or 

history museum .651 .164 .023 .011 

Visit historic 

monument .686 .153 .144 .000 

Read/listen to 

poetry .284 .234 .415 .092 

Visit art/craft fair .670 .084 .173 .034 

Art lessons .098 .038 .603 .150 

Make pottery .297 -.216 .435 .065 

Do needlecrafts .397 -.150 .136 .102 

Work on play set .104 .105 .187 .565 

Work on music set -.044 .155 .087 .557 

Creative writing -.014 .220 .618 .167 

Do photography .192 .070 .452 -.044 

Paint or draw .172 -.025 .622 -.077 

Based on data from November and December, 1982, Underlined variables are included in additive 

scales. 

149
 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-2 

Results of Factor Analysis of Socialization Measures: 

Rotated Factor Loadings
 

Factors 

Variables 1 2 

Parents listened to classical music .097 .748 

Parents took child to art museums .174 .747 

Parents took child to plays/concerts .128 .777 

Parents encouraged child to read .208 .604 

Instrumental/singing class/lessons .494 .320 

Art class/lessons ,693 .082 

Acting class/lessons .542 .072 

Ballet class/lessons .322 .268 

Writing class/lessons .667 .113 

Craft class/lessons .559 .083 

Art appreciation class/lessons .680 .220 

Music appreciation class/lessons .618 .256 

Based on data from November and December, 1982. Underlined variables are included in additive 

scales. Only lessons taken before age of 18 are included. 

150 
Appendix 

Appendix Table 5-3 

Results of Factor Analysis of Music Preference Measures: 

Rotated Factor Loadings
 

Factors 

Variables 1 2 3 

Classical/chamber .713 .030 -.004 

Opera .665 -.075 -.092 

Operetta/show tunes .695 .115 .165 

Jazz .353 -.006 .648 

Soul/blues .204 .099 .659 

Big band .549 .299 .153 

Country western -214 .701 .024 

Bluegrass .063 .730 .207 

Rock -.202 .058 .712 

Mood/easy listening .437 .226 .202 

Folk .362 .623 .144 

Barbershop .420 .526 -.107 

Hymns/gospel .214 .430 -.315 

Based on data from November and December, 1982. Underlined variables are included in additive 

scales. 

151
 
Race, Ethnicity, and Participation in the Arts 

Table 5-4
 

Means and Standard Deviations for Regression Variables for the
 

Full Sample, and by Race and Spanish Origin, by Education, by
 

Gender and by Age -- Including Respondents without Data on
 

Parental Education
 

Art Attend 

N Lessons None music Attend Visit no jazz Perform Dovis TV arts 

FULLSAMPLE 2,255 1.166 1.005 1.396 0.533 2.177 0.436 0.116 0.723 1.347 

1.408 0.957 1.407 0.980 1.745 0.854 0.438 1.105 1.795 

RACE/SP ORIGIN 

White 1,908 1.240 1.134 1.509 0.571 2.208 0.483 0.116 0,762 1.404 

1.426 0.973 1.416 1.015 1.734 0,895 0.443 1.124 1.822 

African-American 230 0.864 0.860 0.720 0.365 1.203 0.~197 0.094 0,449 1.092 

1.318 0.839 1.193 0.768 1.531 0.564 0.360 0.860 1.609 

Hispanic 117 0.667 0.900 1.084 0.305 1.597 0.214 0.166 0.708 1.027 

1.072 0.799 1.230 0.738 1.609 0.,547 0.515 1.191 1.665 

EDUCATION 

11 & Less 607 0.467 0.550 0.785 0.143 0.945 0.112 0.075 0.273 0.675 

0.989 0.697 1.179 0.446 1.176 0.403 0.337 0.685 1.379 

12 Years 919 1.192 1.014 1.312 0.376 2.174 0.296 0.099 0.675 1.241 

1.338 0.858 1.276 0.763 1.648 0.667 0.380 1.027 1.662 

13-15 Yrs 390 1.646 1.517 1.744 0.811 2.689 0.665 0.158 1.034 1.644 

1.547 0.945 1.486 1.153 1.676 0.999 0.516 1.288 1.820 

16 & Over 339 1.766 1.708 2.275 1.305 3.416 1.101 0.183 1.279 2.450 

1.510 1.020 1.445 1.356 1.614 1.190 0.399 1.294 2.118 

GENDER 

Male 1,008 1.118 0.993 1.259 0.449 1.714 0.352 0.096 0.665 1.277 

1.348 0.884 1.341 0.882 1.576 0.752 0.398 1.065 1.747 

Female 1247 1.209 1.167 1.517 0.608 2.494 0.511 0.134 0.775 1.409 

1.458 1.010 1.453 1.054 1.805 0.929 0.471 1.137 1.835 

152 
 

Appendix 

Table 5-4 (Continued)
 Means and Standard Deviations for Regression Variables for the
 

Full Sample, and by Race and Spanish Origin, by Education, by
 

Gender and by Age --Including Respondents without Data on
 

Parental Education
 

Art Attend 

N Lessons N~e music Attend Visit no jazz Perform Dovis TV arts 

AGE 

18-30 729 1.800 1.229 0.989 0.515 2.350 0.361 0.143 1.071 1.160 

1.632 0.897 1.121 0.950 1.725 0.771 0.479 1.325 1.559 

31-51 768 1.098 1.089 1.618 0.632 2.325 0.535 0.135 0.739 1.457 

1.289 0.955 1.471 1.046 1.742 0.920 0.487 1.063 1.837 

Over 51 758 0.603 0.937 1.569 0.448 1.696 0.407 0.065 0.358 1.419 

0.953 0.994 1.505 0.928 1.688 0.852 0.322 0.723 1.951 

153
 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-5
 

Regression Analyses Predicting Number of Performing-Arts
 

Events Attended, 1982 Full Sample
 

I,Vo 

Jazz 

included 

Jazz not 

included 

African-American -.074 

d 

-.008 -.103 

d 

-.033 

d 

Hispanic -.056 

d 

.013 -.061 

d 

,012 

Female .088 

d 

.100 

d 

Age .095 

d 

.132 

d 

Education .299 

d 

.298 

d 

Occupa~on .109 

d 

.105 

d 

Income x 10,000 .132 

d 

.141 

d 

Single/divorced .110 

d 

.089 

d 

SMSA residence .063 

d 

.057 

d 

d.f. 

R squared 

15,012 

.008 

15,012 

.193 

1~5,012 

.013 

15,012 

.191 

Standardized regression coefficients, a: p less than or equal to .05 b: p less than or equal to .01 c: p 

less than or equal to .001 d: p less than or equal to .0001 

154 
Appendix 

Appendix Table 5-6 

Regression Analyses Predicting Scores 

on Fine-Arts Music Scale 

I,V, 2 3 

African-American -.179 -.093 -.080
 

d d d
 

Hispanic -.067 .001 .019
 

b
 

Female .107 .073 

d d 

Age .273 .312 

d d 

Education .338 .234
 

d d
 

Occupation .073 .057 

c b 

Income x 10,000 .095 .074 

d c 

Single/divorced .035 .007 

Lives in SMSA .076 .055 

d b 

Childhood lessons .163 

d 

Parental guidance .200 

d 

d.f. 2,254 2,254 2,254 

R Squared .034 .218 .286 

Additive scale of number of kinds of fine-arts music respondents reported enjoying. Based on 

November/December 1982 subsample, a: p less than or equal to .05 b: p less than or equal to .01 c: 

p less than or equal to .001 d: p less than or equal to .0001 

155 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-7 

Regression Analyses Predicting Scores on Television Arts Scale 

African-American -.057 .017 .028 

b 

Hispanic -.047 .009 .030 

a 

Female .054 .009 

b 

Age .192 

d 

.233 

d 

EducaUon .306 .181 

d d 

Occupation .042 .029 

Income x 10,000  ̄100 .078 

d c 

Single/divorced .081 .047 

c a 

Lives in SMSA .072 .047 

c a 

Childhood lessons .173 

d 

Parental guidance .266 

d 

Hours watch TV .044 

a 

d.f. 2,254 2,254 2,254 

R Squared .004 .140 .243 

Additive scale of number of kinds of artistic programs respondents reported watching on television 

during previous year. Models based on data from November/December 1982 subsample, a: p less 

than or equal to .05 b: p less than or equal to .01 c: p less than or equal to .001 d: p less than or equal 

to .0001 

156 
Appendix 

Appendix Table 5-8
 

Regression Analyses Predicting Number of Performing Events
 

Attended (Including Jazz)
 

African-American -.067 .015 .026 .031 

b 

Hispanic -.061 -.002 .012 .001 

b 

Female .107 .080 .076 

d d d 

Age .119 .150 .065 

d d b 

Education .280 .196 .123 

d d d 

Occupation .125 .112 .090 

d d d 

Income x 10,000 .144 .128 .098 

d d d 

Single/divorced .088 .065 .052 

d b b 

Metropolitan .051 .034 .017 

a 

Parental guidance .165 .076 

d c 

Childhood lessons .129 .074 

d c 

Hours watch TV -.077 

d 

Likes art music .085 

c 

Watch TV arts .257 

d 

d .f. 2,254 2,254 2,254 2,254 

R Squared .007 .182 .226 .299 

Standardized beta coefficients, a: p less than or equal to .05 b: p tess than or equal to .01 c: p less 

than or equal to .001 d: p less than or equal to .0001 Models based on data from November/December 

1982 subsample. 

157
 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-9
 

Regression Analyses Predicting Number of Performing Events
 

Attended (Excluding Jazz)
 

I.V. 1 2 3 4 

African-American -.107 -.022 -.013 -.006 

d 

Hispanic -.070 -.008 .004 -.007 

c 

Female .117 .094 .089 

d d d 

Age .152 .178 .093 

d d d 

Education .275 .202 .129 

d d d 

Occupation .123 .112 .089 

d d d 

Income x 10,000 .150 .136 .106 

d d d 

Single/divorced .068 .048 .036 

b a 

Metropolitan .043 .029 .012 

a 

Parental guidance .144 .058 

d b 

Childhood lessons .106 .052 

d a 

Hours watch TV -.079 

d 

Likes art music .101 

d 

Watch TV arts .234 

d 

d.f. 2,254 2,254 2,254 2,254 

R Squared .014 .183 .215 .283 

Standardized beta coefficients, a: p less than or equal to .05 b: p less than or equal to .01 c: p less 

than or equal to .001 d: p less than or equal to .0001 Based on data from November/December 1982 

subsample. 

158 
 

Appendix 

Appendix Table 5-10 

Regression Analyses Predicting Number of Visually Oriented 

Consumption Activities 

I.V. 1 2 3 4 

African-American -.199 -.115 -.101 

d d d 

Hispanic -.088 -.024 -.004 

d 

Female .255 .219 

d d 

Age -.059 -.013 

b 

Education .371 .260 

d d 

Occupation .080 .063 

d c 

Income x 10,000 .084 .062 

d b 

Single/divorced -.012 -.043 

a 

Metropolitan .024 .002 

Parental guidance .208 

d 

Childhood lessons .186 

d 

Hours watch TV 

Likes art music 

Watch TV arts 

d .f. 2,254 2,254 2,254 

R Squared .043 .310 .390 

-.094 

d 

-.016 

.213 

d 

-.103 

d 

.184 

d 

.040 

a 

.031 

-.056 

b 

-.016 

.118 

d 

.129 

d 

-.077 

d 

.106 

d 

.247 

d 

2,254 

.465 

Standardized beta coefficients, a: p less than or equal to .05 b: p less than or equal to .01 c: p less 

than or equal to .001 d:p less than or equal to .0001 Based on November/December 1982 subsample. 

159 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-11
 

Regression Analyses Predicting Number
 

of Kinds of Performance Activities
 

I,V, 1 2 3 4 

African-American -.016 -.004 .003 .007 

Hispanic .025 .038 .049 .045 

a a 

Female .050 .035 .031 

a 

Age -.039 -.010 -.049 

Education .088 .044 .013 

C 

Occupation .039 .033 .025 

Income x 10,000 -.042 -.051 -.062 

a b 

Single/divorced .034 .020 .015 

Metropolitan -.030 -.041 -.048 

a 

Parental guidance .063 .028 

b 

Childhood lessons .112 .088 

d C 

Hours watch TV -.015 

Likes art music .O59 

a 

Watch TV arts .085 

b 

d.f. 2,254 2,254 2,254 2,254 

R Squared .000 .016 .032 .006 

Standardized beta coefficients, a: p less than or equal to .05 b: p less than or equal to .01 c: p less 

than or equal to .001 d: p less than or equal to .0001 Data from November/December 1982 subsample. 

160 
 

Appendix 

Appendix Table 5-12 

Regression Analyses Predicting Number of Kinds of 

Nonperformance Creative Activities
 

I.V. 1 2 3 4 

African-American -.091 -.056 -,035 -.032 

d b 

Hispanic -.011 .016 .043 .034 

a 

Female ,074 .038 .039 

c a a 

Age -.151 -.074 -.133 

d c d 

Education .215 .104 .050 

d d a 

Occupation .098 .082 .062 

d d b 

Income x 10,000 -.024 -.047 -.070 

a c 

Single/divorced .096 .059 .049 

d b a 

Metropolitan -.018 -.044 -.056 

a b 

Parental guidance 148 .081 

d c 

Childhood lessons .300 .261 

d d 

Hours watch TV -.088 

d 

Likes art music .039 

Watch TV arts ,205 

d 

d.f. 2,254 2,254 2,254 2,254 

R Squared .007 .149 .258 .301 

Standardized beta coefficients, a: p less than or equal to .05 b: p less than or equal to .01 c: p less 

than or equal to ,001 d: p less than or equal to ,0001 Based on data from November/December 1982 

subsample. 

161 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-13
 

Regression Analyses Predicting Number of Kinds of Art Lessons
 

Taken Before Age 18 and Number of Kinds of Activities with
 

Parents as Child, by Race
 

Kinds of lessons Activities with parents 

W A H W A H 

Age -.016 -.025 -.015 .009 -.003 .007 

.002 .066 .008 .001 .004 .005 

-.194 -.333 -.206 .159 -.064 .132 

d d d 

Female .185 -.106 .168 .223 .295 .048 

.067 .204 .253 .043 .124 .164 

.064 -.039 .073 .114 .166 .030 

b d a 

Father’s .070 .061 .109 .100 .098 .068 

education .014 .047 .052 .009 .029 .033 

.161 .130 .313 .340 .317 .283 

d a d d a 

Mother’s .085 .061 -.055 .090 .085 .053 

education .016 .051 .064 .011 .031 .041 

.171 .128 -.127 .269 .273 .181 

d d b 

d.f. 1,525 140 83 1,525 140 83 

Adj. R squared .187 .217 .047 .267 .329 .154 

a: p less than or equal to .05 b: p less than or equal to .01 c: p less than or equal to .001 d: p less 

than or equal to .0001 Based on data from November/December 1982 subsample, respondents with 

information on parents’ education only. 

162 
Appendix 

Appendix Table 5-14 

Regression Analyses Predicting Number of Kinds of Art Music 

and Related Genres Enjoyed, by Race 

Model 1 Model 2 

I.V.s W A H W 

Age .023 

.002 

.296 

d 

.004 

.005 

.069 

.003 

.008 

.046 

.026 

.002 

.337 

d 

.011 

.005 

.174 

a 

.003 

.008 

.036 

Female .353 

.058 

.124 

d 

.110 

,153 

.046 

.201 

,229 

.082 

.243 

.057 

.086 

d 

,089 

,140 

.037 

.198 

.220 

.080 

Educa~on .175 

.012 

.346 

d 

.070 

.028 

.225 

a 

.077 

.038 

,243 

a 

.122 

.013 

.241 

d 

.041 

.025 

.131 

,038 

,038 

,122 

Occupa~on .190 

.068 

.065 

b 

.574 

.196 

,205 

b 

-.186 

.278 

-.067 

,175 

.066 

.060 

b 

.265 

.183 

,095 

-.193 

.266 

-.069 

Income 

x 10,000 

.098 

.021 

,105 

d 

.008 

.075 

.008 

-.052 

.103 

-.051 

.080 

,021 

.086 

d 

.023 

.069 

,022 

-.059 

.100 

-.058 

Single/divorced .128 

.073 

.039 

-,106 

.178 

-.041 

.405 

.268 

.155 

,023 

.071 

.007 

-.074 

,t61 

-,029 

.280 

.261 

.107 

Lives in SMSA .201 

.062 

,068 

b 

,358 

.189 

,124 

,305 

.411 

,069 

.153 

,060 

.052 

a 

.222 

,172 

,077 

,239 

.395 

,054 

163 
 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-14 (Continued)
 

Regression Analyses Predicting Number of Kinds of Art Music
 

and Related Genres Enjoyed, by Race 

Model 1 Model 2 

W A H W A H 

Parental .261 .491 .350 

guidance .033 .095 .148 

.180 .345 .227 

d d a 

Childhood lessons .158 .176 .205 

.023 .061 .114 

.159 .195 .179 

d b 

d.f. 1,907 229 116 1,907 229 116 

Adj. R Squared .214 .133 .028 .272 .290 .108 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December subsample. 

164 
Appendix 

Appendix Table 5-15
 

Regression Analyses Predicting Number of Kinds of Television
 

Arts Program Watched in Previous 12 Months, by Race
 

Model 1 Model 2 

W A H W A H 

Age ,020 

.002 

.204 

d 

,003 

,007 

.037 

.005 

.012 

.046 

.024 

.002 

.245 

d 

.015 

.007 

.174 

a 

.001 

.011 

.015 

Female ,255 

.078 

.070 

C 

.099 

.208 

.031 

-.096 

.316 

-,029 

.073 

.075 

,020 

.034 

.188 

.010 

-.074 

.285 

-.022 

Educa~on .206 

.016 

.317 

d 

.064 

.037 

.151 

.096 

.052 

.225 

.124 

.017 

.191 

d 

.026 

.034 

.061 

.017 

.049 

.041 

Occupa~on .120 

.091 

.032 

.594 

.266 

,157 

a 

-.291 

,383 

-.077 

.114 

.087 

.030 

.169 

,243 

.045 

-.303 

.347 

-,080 

Income 

x 10,000 

.116 

.029 

.097 

d 

.166 

.102 

.117 

.037 

.142 

,027 

.090 

.027 

.075 

c 

.188 

.091 

.132 

a 

.048 

.129 

.034 

Single/divorced .335 

.098 

.080 

C 

.323 

.242 

.094 

.370 

.369 

.104 

.177 

.093 

.042 

.363 

.213 

.105 

.177 

.338 

.050 

Lives in SMSA .256 

.083 

.067 

b 

.477 

.256 

.123 

-.230 

.566 

-.038 

.183 

,079 

.048 

a 

.244 

.228 

.063 

-.303 

.5!6 

-.050 

165
 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-15 (Continued)
 

Regression Analyses Predicting Number of Kinds of Television
 

Arts Program Watched in Previous 12 Months, by Race
 

Model 1 Model 2 

W A H W A H 

Parental .451 .693 .875 

guidance .044 .126 .192 

.241 .361 .419 

d d d 

Childhood lessons .215 .294 .223 

.030 .082 .147 

.168 .240 .143 

d c 

Hours TV .030 .037 -.001 

.018 .028 .069 

.035 .077 -.001 

d.f. 1,907 229 116 1,907 229 116 

Adj. R Squared .151 .121 -.004 .236 .319 .186 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

166 
Appendix 

Appendix Table 5-16 

Regression Analyses Predicting Number of Kinds of Performing 

Events Attended in Previous 12 Months, Including Jazz, by Race 

Model 1 Model 2 Model3 

W A H W A H W A H 

Age .006 

.001 

.118 

d 

,002 

.003 

,042 

.001 

.005 

.027 

.008 

.001 

.151 

d 

.004 

.003 

.097 

,000 

,005 

.011 

.003 

,001 

.063 

b 

.002 

.003 

.045 

.000 

.005 

.001 

Female .257 

.042 

.126 

d 

.018 

.093 

.012 

.127 

.137 

.086 

.192 

.042 

.095 

d 

.007 

.091 

.005 

.132 

.134 

,090 

.175 

.040 

.086 

d 

.004 

.090 

.002 

.145 

.131 

.098 

Education ,112 

.009 

.309 

d 

.045 

.017 

.222 

b 

.003 

.022 

.014 

.081 

,009 

,223 

d 

.034 

.016 

.168 

a 

-.016 

.023 

-.082 

.052 

.009 

.144 

d 

.029 

.016 

.145 

-.019 

.023 

-.099 

Occupation .198 

.050 

.094 

d 

,529 

.119 

.294 

d 

.269 

.166 

.161 

.189 

.048 

.090 

d 

.417 

.119 

.232 

c 

.266 

.162 

.159 

.141 

.046 

.067 

b 

.386 

.117 

.214 

b 

.296 

.159 

.177 

Income 

x 10,000 

.086 

.016 

.128 

d 

.113 

,046 

.168 

a 

.121 

.061 

.196 

.076 

.015 

.113 

d 

.117 

.044 

.174 

b 

.124 

.061 

.201 

a 

.055 

.015 

.082 

c 

.096 

.044 

.143 

a 

.113 

.059 

.183 

Single/ 

divorced 

.242 

.053 

.104 

d 

-.013 

.108 

-.008 

.151 

,160 

.096 

.181 

,052 

.078 

c 

-.093 

.112 

-.050 

.107 

.159 

.068 

.150 

.050 

.064 

b 

-.038 

.103 

-.023 

.087 

,155 

.055 

Lives in 

SMSA 

!16 

.045 

.055 

a 

-.046 

.114 

-.025 

-.203 

.245 

-.077 

.088 

.041 

.042 

a 

-.093 

.112 

-.050 

-.220 

.241 

-.083 

.051 

.042 

.024 

-.126 

.110 

-.068 

-.154 

.237 

-.058 

Parental 

guidance 

.153 

.025 

.147 

d 

.191 

.062 

.209 

b 

.204 

.090 

.220 

a 

.069 

,024 

.066 

b 

.096 

.066 

.105 

.088 

.096 

.096 

167 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-16 (Continued) 

Regression Analyses Predicting Number of Kinds of Performing 

Events Attended in Previous 12 Months, Including Jazz, by Race 

Model 1 Model 2 Model 3 

I.V.s W A H W A H W A 

Childhood lessons .092 .053 .050 .053 .016 .023 

.017 .040 .089 .016 .040 .068 

.129 .092 .073 .075 .027 .033 

d d 

Hours TV -.037 -.007 -.018 

.010 .013 .032 

-.078 -.030 -.050 

C 

Art music .063 .037 -.020 

.018 .046 .066 

.088 .058 -.033 

c 

TV art programs .143 .109 .142 

.014 .035 .051 

.257 .229 .320 

d b b 

d.f. 1,907 229 116 1,907 229 1’16 1,907 229 116 

R Squared .188 .234 .039 .226 .280 .081 .301 .315 .134 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 Based on data from November/December 1982 subsample. 

168 
Appendix 

Appendix Table 5-17 

Regression Analyses Predicting Number of Kinds of Performing 

Events Attended in Previous 12 Months, Excluding Jazz, by Race 

Model 1 Model 2 Model 3 

I.V.s W A H W A H W A H 

Age .007 

.001 

.140 

d 

.007 

.002 

.237 

b 

.002 

.004 

.061 

.008 

.001 

.168 

d 

.008 

.002 

.258 

b 

.001 

.004 

.041 

.004 

.001 

.079 

b 

.006 

.002 

,205 

b 

.001 

.004 

.034 

Female .239 

.037 

.134 

d 

.070 

.067 

.062 

.095 

.100 

,087 

.190 

.037 

.106 

d 

.057 

.067 

.050 

.100 

.098 

.091 

.172 

.036 

.096 

d 

.057 

.066 

.050 

.108 

.098 

.098 

Education .097 

.008 

.304 

d 

.038 

.012 

.254 

b 

.010 

.016 

.073 

.073 

.008 

.230 

d 

.032 

.012 

.215 

b 

-.004 

.017 

-.027 

.048 

.008 

.149 

d 

.028 

.012 

.188 

a 

-.005 

.017 

-.039 

Occupation .174 

.044 

.094 

d 

.411 

.086 

,311 

d 

.196 

.122 

.158 

.168 

.043 

.090 

d 

.358 

.087 

.270 

d 

.194 

.119 

.156 

.125 

.042 

.067 

b 

.331 

.086 

.250 

c 

.210 

.118 

.169 

Income 

x 10,000 

.077 

.014 

,131 

d 

.113 

.033 

.227 

c 

.099 

.045 

,216 

a 

.069 

.014 

.117 

d 

.112 

.033 

.225 

c 

.I02 

.044 

.222 

a 

.051 

.013 

,086 

d 

.098 

.032 

.198 

b 

.095 

.044 

.209 

a 

Single/ 

divorced 

.158 

.047 

.077 

c 

.041 

.078 

.034 

.098 

.117 

.084 

.111 

.047 

.054 

a 

.046 

.077 

.038 

,066 

.116 

.057 

.085 

.044 

.041 

.025 

.076 

.021 

.055 

,116 

.047 

Lives in 

SMSA 

.095 

.040 

.051 

a 

-,155 

.083 

-.113 

-.003 

.180 

-.002 

.074 

.039 

.039 

-.171 

.082 

-,125 

a 

-.014 

.176 

-.007 

.040 

.038 

.022 

-.194 

.081 

-.142 

a 

.023 

.177 

.012 

Parental 

guidance 

.118 

.022 

.128 

d 

.122 

.045 

.181 

b 

.163 

.066 

.239 

a 

,044 

.022 

.048 

a 

.054 

.048 

.080 

.099 

.071 

.145 

169 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-17 (Continued) 

Regression Analyses Predicting Number of Kinds of Performing 

Events Attended in Previous 12 Months, Excluding Jazz, by Race 

Model 1 Model 2 Model 3 

W A H W A H W A H 

Childhood lessons .070 .001 .031 .037 -.025 .016 

.015 .029 .051 ,015 .030 .051 

.112 .002 .062 .058 -.058 .032 

d a 

Hours TV -.032 -.007 -.010 

.009 .010 .024 

-.076 -.043 -.037 

d 

Art music .067 .038 -.012 

.016 .034 .049 

,105 .081 -.027 

d 

TV art programs .118 

.012 

.070 

.026 

,079 

.038 

.239 .198 .241 

d b a 

d.f. 1,907 229 116 1,907 229 116 1,907 229 116 

R Squared .182 .258 .058 .210 .278 .106 .283 .309 .125 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

170 
 

Appendix 

Appendix Table 5--18
 

Regression Analyses Predicting Number of Kinds of Visually
 

Oriented Consumption Activities in Previous 12 Months, by Race
 

Model 1 Model 2 Model 3 

W A H W A H W A 

Age -.007 -,009 -.002 -.002 -.008 -.001 -.011 -.005 -,001 

.002 ,006 .010 .002 .006 ,009 .002 .006 ,008 

-.071 -.109 -,017 -.025 -.009 -,015 -.118 -.062 -.012 

b d 

Female 1.015 .537 .182 .874 .503 .152 .838 .518 .197 

.067 .178 .276 .065 .158 .250 .061 .157 .215 

.292 .174 .057 ,252 .163 ,047 .241 .168 .061 

d b d b d b 

Education ,256 .089 .141 .188 .051 .081 .136 .039 .078 

,014 .032 .045 .015 .029 .043 .014 .028 .037 

.413 .222 .343 ,303 ,127 .197 .220 ,097 .190 

d b b d d a 

Occupation .129 1.009 .732 .111 ,613 .721 .024 ,531 .890 

.079 .228 .334 .075 .207 .302 .071 .204 .260 

.036 .281 .201 ,031 ,171 .198 .007 ,148 .244 

d a b a b c 

Income .085 .130 .048 .062 .146 .016 ,026 .116 .002 

x 10,000 .025 .088 .124 .024 .078 .113 ,022 .076 .097 

.074 ,097 .035 .054 .109 ,012 ,022 .086 .002 

c b 

Single/ .036 -.427 -.107 -.100 -.386 -.359 -.151 -.430 -.436 

divorced .084 .207 .323 .081 .183 .296 .076 .180 .254 

.009 -.130 -.031 -.025 -.118 -.105 -.038 -.131 -.127 

a a a a 

Lives in ,092 -.012 -.361 .030 -.181 -.515 -.037 -.233 -.423 

SMSA .072 .219 .494 .069 ,195 .448 .064 .191 .388 

.025 -.003 -.062 .008 -.049 -.089 -.010 -.063 -.073 

Parental ,326 .658 .421 .178 ,485 .009 

guidance .038 .108 ,168 .037 .114 .157 

.183 .360 ,209 .100 .266 ,004 

d d a d d 

171 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-18 (Continued)
 

Regression Analyses Predicting Number of Kinds of Visually
 

Oriented Consumption Activities in Previous 12 Months, by Race
 

Model 1 Model 2 Model 3 

I.V.s W A H W A H W A H 

Childhood lessons .214 .203 .485 

.026 .070 .129 

.176 .174 .323 

d b c 

.146 

.025 

.120 

d 

.143 

.071 

.123 

a 

.384 

.120 

.256 

c 

Hours TV -.065 

.015 

-.079 

d 

-.029 

.023 

-.064 

.057 

.052 

.074 

Art music .136 

.028 

.111 

d 

.113 

.080 

.088 

-.025 

.107 

-.019 

TV art programs .234 

.021 

.246 

d 

.163 

.061 

.171 

b 

.476 

.083 

.494 

d 

d.f. 

R Squared 

1,907 229 

.302 .290 

116 1,907 229 116 1,907 

.176 .367 .448 .330 .445 

229 

.476 

116 

.511 

First row is unstandardized regression coefficient.
 

Second row is standard error.
 

Third row is standardized regression coefficient.
 

Fourth row indicates significance:
 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on November/December 1982 subsample. 

172 
 

Appendix 

Appendix Table 5-19 

Regression Analyses Predicting Number of Kinds of Performance
 

Activities in Previous 12 Months, by Race 

Model 1 Model 2 Model 3 

W A H W A H W A H 

Age -.001 

.001 

-.045 

-.000 

.002 

-.018 

-.004 

.004 

-,123 

-.000 

.001 

-.014 

-.000 

.002 

-.008 

-.004 

.003 

-.155 

-.001 

.001 

-.058 

a 

-.000 

.002 

-.016 

-.004 

.003 

-.140 

Female .050 

.020 

.057 

a 

-.001 

.050 

-.001 

.090 

.096 

.087 

.034 

.020 

.039 

-.002 

.050 

-.003 

.091 

.094 

.088 

.028 

.020 

.032 

-.011 

.051 

-.006 

.101 

.095 

.098 

Education .017 

.004 

.109 

d 

.003 

.009 

.031 

-.016 

.016 

-.123 

.010 

.005 

.061 

a 

.002 

.009 

.020 

-.029 

.016 

-.223 

.004 

.005 

.024 

.002 

.009 

.024 

-.030 

.016 

-.224 

Occupation .025 

.024 

.027 

.099 

.064 

.117 

.042 

.116 

.036 

.024 

.024 

.026 

.088 

.066 

.105 

.039 

.114 

.034 

.015 

.024 

.016 

.092 

.067 

.109 

.039 

.115 

.033 

Income 

x 10,000 

-.017 

.008 

-.059 

a 

-.017 

.024 

-.053 

.091 

.043 

.212 

a 

-.020 

.007 

-.068 

b 

-.017 

.025 

-.052 

.091 

.042 

.212 

a 

-.024 

.007 

-.082 

b 

-.018 

.025 

-.055 

.085 

.043 

.197 

Single/ 

divorced 

.020 

.026 

.019 

.084 

.058 

.109 

.186 

.112 

.169 

.002 

.025 

.002 

.085 

.058 

.110 

.148 

.111 

.135 

-.003 

.025 

-.002 

.084 

.059 

.109 

.151 

.113 

.137 

Lives in 

SMSA 

-.035 

.022 

-.038 

.002 

.061 

.002 

.188 

.172 

.102 

-.043 

.022 

-.046 

a 

-.002 

.062 

-.002 

.170 

.168 

.092 

-.050 

.022 

-.054 

a 

-.008 

.063 

-.009 

.204 

.172 

.110 

Parental 

guidance 

.026 

.012 

.057 

a 

.019 

.034 

.044 

.133 

.063 

.207 

a 

.010 

.012 

.022 

.015 

.037 

.035 

.111 

.070 

.I72 

Childhood lessons .037 

,008 

.118 

d 

.004 

.022 

.014 

.055 

.048 

.115 

.029 

.008 

.093 

c 

-.000 

.023 

-.001 

.054 

.050 

.111 

173 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-19 (Continued) 

Regression Analyses Predicting Number of Kinds of Performance
 

Activities in Previous 12 Months, by Race 

Model 1 Model 2 Model 3 

W A H W A H W A H 

Hours TV -.004 .006 -.012 

.005 .008 .023 

-.021 .057 -.047 

Art music .022 .011 -.038 

.009 .026 .048 

.070 .036 -.090 

a 

TV art programs .022 

.007 

-.000 

.020 

.042 

.037 

.089 -.001 .135 

b 

d.f. 

R Squared 

1,907 

.018 

229 

.002 

116 1,907 

.028 .034 

229 

-.004 

116 

.075 

1,907 

.047 

229 

-.014 

116 

.063 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

174 
 

Appendix 

Appendix Table 5-20
 

Regression Analyses Predicting Number of Kinds of
 

Nonperformance Activities in Previous 12 Months, by Race
 

Age 

Female 

Education 

Occupation 

Income 

x 10,000 

Single/ 

divorced 

Lives in 

SMSA 

Parental 

guidance 

Model 1 Model 2 Model 3 

W A H W A H W A 

-.010 -.003 -.011 -.005 .004 -.012 -.009 .003 -.013 

.001 .004 .008 .001 ,004 .007 .001 .004 .007 

-.168 -.054 -.157 -,091 .092 -.176 -.150 .060 -.185 

d d d 

.223 -.041 -.042 .124 .001 -.038 .116 .010 .010 

.048 .107 .219 .045 .098 .203 .044 .099 .184 

.099 -.024 -.018 .055 .000 -.016 .052 .006 .004 

d b b 

.099 .039 .040 .052 .026 -,008 .028 .022 -.011 

.010 .019 .036 .010 .018 ,035 .010 .018 .032 

.247 .172 .132 .129 .117 -.025 .069 .099 -.037 

d a d b 

.129 .702 ,311 .121 .527 .303 .073 .499 .376 

.056 .137 .266 .053 .128 .245 .052 ,129 .223 

.056 .348 .115 .052 .261 .112 .031 .247 .139 

a d a d d 

-.023 -.043 .020 -.039 -.015 .019 -.057 -.025 -.011 

.018 .053 .098 .017 .048 .092 .016 .048 .083 

-.031 -.056 .020 -.053 -.019 .019 -.076 -.033 -.011 

a c 

.313 -.022 .075 .206 .002 -.064 .179 -.016 -.094 

.060 .124 .256 .057 .113 .240 .055 .114 .217 

.121 -.012 .030 .080 .001 -.025 .069 -.008 -.037 

d c b 

-.064 .072 -.171 -.111 -.044 -.236 -.142 -.059 -.070 

.051 .132 .392 .048 .121 .363 .047 .121 .332 

-.028 .035 -.040 -.047 -.021 -.055 -.060 -.028 -.016 

a b 

.158 .067 .481 .088 .009 .210 

.027 .066 .136 .027 .072 .134 

.137 .065 .323 ,077 .009 .141 

d c c 

175 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-20 (Continued)
 

Regression Analyses Predicting Number of Kinds of
 

NonPerformance Activities in Previous 12 Months, by Race
 

Model 1 Model 2 Model 3 

I,V.s W A H W A H W A H 

Childhood lessons .229 

.018 

.291 

d 

268 

.043 

.410 

d 

.202 

,104 

.182 

.200 

.018 

254 

d 

249 

.044 

.381 

d 

.146 

.096 

.131 

Hours TV -.046 

.011 

-.088 

d 

-.013 

.015 

-.050 

-.026 

.044 

-.046 

Art music .041 

.020 

.051 

a 

.026 

.051 

.035 

-.121 

.092 

-.125 

TV art programs	 .120 .061 .362 

.015 .039 .071 

.194 .115 .503 

d d 

d.f. 1,907 229 116 1,907 229 116 1,907 229 116 

R Squared .158 .188 .053 .257 .331 .194 .299 .336 .347 

First row is unstandardized regression coefficient.
 

Second row is standard error.
 

Third row is standardized regression coefficient.
 

Fourth row indicates significance:
 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

176 
Appendix 

Appendix Table 5-21
 

Regression Analyses Predicting Number of Kinds of Art Lessons
 

Taken Before Age 18, Number of Kinds of Activities with Parents
 

as Child, and Number of Kinds of Television Arts Programs
 

Watched, by Gender
 

Lessons Parents Arts on TV Arts on TV 

I.V.s M F M F	 M F M F 

African- -.251 -.595 -.248 -.334 ,163 .036 .167 .159 

American .126 .118 .088 .087 .172 .154 .164 .145 

-.058 -,133 -.088 -.108 .029 .006 .030 .028 

a d b d 

Hispanic -.689 -.707 -.260 -.472 .243 -.100 .357 .134 

.171 ,177 .120 .131 ,232 ,228 ,222 214 

-.117 -.105 -.068 -,101 .032 -,012 .047 .016 

d d a c 

Age -.029 -.028 -.009 -.008 .021 .017 .026 .021 

.002 .002 .002 .002 .003 .003 .003 .003 

-.381 -.365 -.178 -.141 .218 .176 .265 .213 

d d d d d d d d 

Educa~on	 ,149 .215 .098 ,120 

,020 .021 .019 .021 

.291 .324 .191 .180 

d d d d 

Occupa~on ,460 -.069 .322 -,035 

,123 .114 .119 .108 

.127 -.018 .089 -.009 

C b 

Income x .063 .161 ,040 ,133 

10,000 .040 .037 .038 .035 

.054 .131 .034 .108 

d d 

Single/ .462 .220 .349 .063 

divorced .130 .121 .124 .113 

.119 .052 .090 .015 

c b 

177 
 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-21 (Continued)
 

Regression Analyses Predicting Number of Kinds of Art Lessons 

Taken Before Age 18, Number of Kinds of Activities with Parents 

as Child, and Number of Kinds of Television Arts Programs 

Watched, by Gender 

Lessons Parents Arts on TV Arts on TV 

I.V.s M F M F M F M F 

Lives in .225 .313 .120 .236 

SMSA .114 .107 .109 .100 

.060 .080 .032 .060 

a b a 

Childhood .239 .205 

lessons .042 .036 

.184 .163 

d d 

Home .426 .536 

activities .064 .053 

.216 .295 

d d 

Hours TV/ .041 .031 

day .025 .018 

.047 .043 

d.f. 1,007 1,246 1,007 1,246 1,007 1,246 1,007 1,246 

R Squared .153 .148 .039 .034 .141 .150 .219 .265 

First row is unstandardized regression coefficient.
 

Second row is standard error.
 

Third row is standardized regression coefficient.
 

Fourth row indicates significance:
 

a less than or equal to .05
 

b less than or equal to .01
 

c less than or equal to .001
 

d less than or equal to .0001
 

Based on data from November/December 1982 subsample. 

178 
 

Appendix 

Appendix Table 5-22 

Regression Analyses Predicting Number of Kinds of Art Music 

African-


American
 

Hispanic 

Age 

Educa~on 

OccupaSon 

Income x 

10,000 

Single/ 

divorced 

Lives in 

SMSA 

and Related Genres Enjoyed, by Gender 

Model 1 Model 2 

M F M F 

-,305 -.507 -.297 -.398 

.125 ,118 ,122 .112 

-,071 -.113 -.069 -.089 

a d a c 

,111 -.094 ,184 .059 

,169 .175 .164 .166 

,019 -.014 ,032 ,009 

.020 .021 .024 .024 

.002 .002 .002 .002 

.273 .269 .315 .307 

d d d d 

.135 .178 .105 .111 

,014 .016 ,014 .016 

,343 .338 .268 .211 

d d d d 

,324 ,119 .235 .124 

,089 .088 .088 .083 

,116 ,039 ,085 .040 

c b 

.077 .096 ,063 .075 

.029 .028 ,028 .027 

.085 .099 .069 .076 

b c a b 

.039 .176 -.024 .063 

.094 .093 ,092 ,088 

.013 .052 -.008 ,019 

.230 .214 ,171 .160 

.083 .082 ,081 .078 

.080 ,069 ,060 .052 

b b a a 

179 
 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-22 (Continued)
 

Regression Analyses Predicting Number of Kinds of Art Music
 

and Related Genres Enjoyed, by Gender 

M 

Model 1 

F M 

Model 2 

Childhood 

lessons 

.155 

.031 

.155 

d 

.164 

.028 

.164 

d 

Parental 

guidance 

.217 

.047 

.143 

d 

.341 

.041 

.237 

d 

d.f. 

R Squared 

1,007 

.223 

1,246 

.201 

1,007 

.270 

1,246 

.287 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

180 
 

 

Appendix 

Appendix Table 5-23 

Regression Analyses Predicting Number of Kinds of Performing 

African-


American
 

Hispanic 

Age 

Educa~on 

Occupa~on 

Income x 

10,000 

Single/ 

divorced 

Lives in 

SMSA 

Events Attended, Including Jazz, by Gender 

Model 1 Model 2 Model 3 

M F M F M F 

.108 -.003 .113 .053 .101 .088 

,085 .086 .083 .085 .080 .081 

.038 -.001 .040 .016 .036 ,027 

-.016 -.002 .027 .073 -.022 .030 

.115 .128 .112 ,126 .108 ,119 

-.004 -.000 .007 .015 -,006 ,006 

.004 .008 .006 .010 .002 .004 

,002 .002 .002 .002 ,002 .002 

,086 .145 .123 .176 ,051 .080 

a d c d b 

.061 ,125 .038 .096 .023 .064 

.010 .012 ,010 .012 .010 ,012 

.237 .327 .149 .252 .090 .168 

d d d d a d 

.334 .211 .266 ,215 .212 ,183 

.061 .064 ,059 .063 .058 .060 

.183 .094 .146 .096 .116 .082 

d c d c c b 

.066 .116 ,055 .107 .049 .077 

.020 .021 .019 .020 .018 .019 

.111 .164 .093 .151 .082 ,109 

c d b d b d 

.156 .204 .111 .150 .068 .133 

.064 .068 .062 .067 .060 .063 

.080 .084 .056 .062 .035 .054 

a b a a 

,133 .071 .089 .046 .072 -.004 

.057 .060 .055 .059 .053 .056 

,070 ,032 .047 .020 .038 -.002 

a 

181 
 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-23 (Continued)
 

Regression Analyses Predicting Number of Kinds of Performing
 

Events Attended, Including Jazz, by Gender
 

I.V.s M 

Model 1 

F M F 

Model 2 

M F 

Parental 

guidance 

.089 

.021 

.137 

d 

.093 

.021 

.128 

d 

Home 

activi~es 

.196 

.032 

.197 

.131 

.031 

.125 

d 

Hours TV/day 

Art music 

TV arts programs 

d.f. 1,007 1,246 1,007 1,246 

R Squared .169 .196 .224 .229 

First row is unstandardized regression coefficient.
 

Second row is standard error.
 

Third row is standardized regression coefficient.
 

Fourth row indicates significance:
 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

Model 3 

.058 

.021 

.088 

b 

.048 

.020 

.066 

a 

.134 

.032 

.135 

d 

.018 

.031 

.017 

-.023 

.012 

-.053 

-o031 

.010 

-.075 

b 

.015 

.023 

.023 

.093 

.023 

.128 

d 

.131 

.017 

.259 

d 

.149 

.018 

.258 

d 

1,007 

.280 

1,246 

.313 

182 
 

 

Appendix 

Appendix Table 5-24 

Regression Analyses Predicting Number of Kinds of Performing 

African-


American
 

Hispanic 

Age 

Educa~on 

Occupagon 

Income x 

10,000 

Single/ 

divorced 

Lives in 

SMSA 

Events Attended, Excluding Jazz, by Gender
 

Model 1 Model 2 Model 3 

M F M F M F 

-.017 -.091 -,013 -.049 -.018 -.013 

.073 .076 .071 .075 .069 .072 

-.007 -.032 -.005 -.017 -.007 -.005 

-.012 -.050 ,018 .007 -.021 -.031 

.098 .113 .096 .112 .093 .106 

-.004 -.012 .005 .002 -.006 -.007 

.006 .008 .007 .010 .004 ,005 

.001 .001 .001 .001 .001 .001 

.137 ,168 .168 .194 ,098 .098 

d d d d b c 

.056 .104 .039 .082 .026 .054 

.008 .010 .008 .011 .008 .011 

.251 .310 .177 .243 ,118 .160 

d d d d b d 

,247 .214 .198 .217 .152 .187 

.052 ,057 .051 .056 .050 .054 

.158 .109 .127 .110 .097 .095 

d c d d b c 

.066 ,101 .058 .094 .052 .068 

.017 .018 .016 .018 .016 ,017 

.130 .161 .115 .150 .103 .108 

d d c d b d 

.109 .126 ,076 ,085 .045 ,070 

.055 .060 .054 ,059 .052 .056 

.065 .059 .046 ,040 .027 .033 

a a 

.085 .064 .053 .044 .038 .001
 

.048 .053 .047 ,052 .046 .050
 

.053 .032 .033 .022 .024 .001
 

183 
 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-24 (Continued) 

Regression Analyses Predicting Number of Kinds of Performing 

Events Attended, Excluding Jazz, by Gender 

Model 1 Model 2 Model 3 

I.V.s M F M F M F 

Childhood .063 .069 .037 .030 

lessons .018 .019 ,018 .018 

.112 .108 .067 .047 

c c a 

Parental .143 .104 .092 .006 

guidance .028 .028 .027 .027 

.168 .113 .108 .007 

d c c 

Hours TV/day -.023 -.027 

.011 .009 

-.060 .076 

a b 

Ar~ music .023 .091 

.020 .020 

.042 .142 

d 

TV arts programs ,100 .122 

.015 .016 

.232 .241 

d d 

d.f. 1,007 1,246 1,007 1,246 1,007 1,246 

R Squared .170 .191 .208 .215 .258 .297 

First row is unstandardized regression coefficient.
 

Second row is standard error.
 

Third row is standardized regression coefficient.
 

Fourth row indicates significance:
 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

184 
 

 

Appendix 

Appendix Table 5-25 

Regression Analyses Predicting Number of Kinds of Visually 

Oriented Consumption Activities, by Gender 

Model 1 Model 2 Model 3 

M F M F M F 

African- -.414 -.813 -.402 -.664 -.407 -.596 

American .142 .139 .134 .132 .128 .124 

-.082 -,147 -.080 -.120 -.081 -.108 

b d b d b d 

Hispanic	 ,129 -.492 ,228 -,294 .131 -.369 

.192 .206 .181 .195 .171 .182 

.019 -,059 .033 -.035 ,019 -.044 

a	 a 

Age -.004 -,007 ,001 -.002 -.007 -.011 

.003 .003 .003 .003 ,003 .003 

-.042 -.069 .006 -.019 -.080 -.115 

a b d 

Educa~on	 .181 .255 .132 .181 .099 .126 

.016 .019 .016 ,019 .015 .018 

,391 .390 .285 .276 .213 .193 

d d	 d d d d 

Occupa~on	 .420 .196 .274 .207 .159 .148 

.101 .103 .096 .097 ,092 .092 

.128 .051 .084 ,054 .049 .039 

d	 b a 

Income x .050 .129 .027 .106 .011 .055 

10,000 .033 .033 ,031 ,031 .029 .029 

.047 .107 .026 .087 .011 .045 

d	 c 

Single/ -.039 -.059 -.138 -.200 -.213 -,230 

divorced ,107 ,109 .101 .103 .096 .097 

-.011 -.014 -.039 -,048 -.061 -,055 

a a 

Lives in .133 .035 .039 -.032 -.001 -.116 

SMSA .094 .097 .089 ,091 .085 .085 

,040 .009 .011 -.008 -.000 -.030 

185 
 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-25 (Continued)
 

Regression Analyses Predicting Number of Kinds of Visually
 

Oriented Consumption Activities, by Gender
 

Model1 Model2 Model3 

I.V.s M F M F M F 

Childhood .207 .249 .143 .174 

lessons .035 .033 .033 .031 

.177 .201 .122 .140 

d d d d 

Parental .406 .333 .281 .142 

guidance .052 .048 .050 .047 

.228 .186 .158 .080 

d d d b 

Hours TV/day -.051 -.055 

.O2O .016 

-.065 -.078 

b c 

Art music	 .080 .170 

.037 .035 

.068 .137 

a d 

TV arts programs	 .236 .241 

.028 .027 

.262 .245 

d d 

d.f. 1,007 1,246 1,007 1,246 1,007 1,246 

R Squared .277 .288 .358 .366 .428 .448 

First row is unstandardized regression coefficient.
 

Second row is standard error.
 

Third row is standardized regression coefficient.
 

Fourth row indicates significance:
 

a less than or equal to .05
 

b less than or equal to .01
 

c less than or equal to .001
 

d less than or equal to .0001
 

Based on data from November/December 1982 subsample. 

186 
 

 

Appendix 

Appendix Table 5-26
 

Regression Analyses Predicting Number of Kinds
 

of Performance Activities, by Gender
 

Model 1 Model 2 Model 3 

M F M F M F 

African­ .006 -.023 .007 .001 .006 .008 

American .042 .042 .042 .042 .042 .043 

.004 -.016 .005 .000 .005 .006 

Hispanic .046 .105 .055 ,134 ,043 .130 

.057 .062 ,056 .062 .056 .062 

.027 .048 .032 .061 ,025 .059 

a a 

Age -,000 -,001 ,000 -,000 -,001 -.001 

.001 .001 .001 .001 .001 .001 

-.011 -.056 .006 -,017 -.036 -.053 

Educa~on .005 ,022 .000 ,016 -,004 .011 

.005 .006 .005 ,006 .005 ,006 

,047 .131 ,003 .092 -.030 .065 

d b 

Occupa~on .053 ,020 .038 ,023 ,026 .020 

.030 .031 ,030 ,031 .030 ,032 

.065 .020 .046 .023 .031 .020 

Income x -.014 -.013 -.016 -.015 -,018 -.019 

10,000 .010 .010 .010 .010 .010 ,010 

-.052 -.041 -.061 -.047 -.068 -.059 

Single/ ,038 .033 .028 .015 .019 .013 

divorced ,032 .033 .031 .033 .032 .033 

.043 .030 ,031 .014 .021 .011 

Lives in .001 -.056 -.009 -.064 -.014 -.072 

SMSA .028 .029 .027 .029 .028 .029 

.001 -.056 -.010 -.064 -.016 -.072 

a a 

187 
 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-26 (Continued)
 

Regression Analyses Predicting Number of Kinds
 

of Performance Activities, by Gender
 

Model 1 Model 2 Model3 

M F M F M F 

Childhood .018 .047 .011 .040 

lessons .011 .011 .011 .011 

.063 .147 .036 .124 

d c 

Parental .045 .012 .031 -.005 

guidance .016 .015 .017 .016 

.100 .026 .068 -.010 

b 

Hours TV/day -.003 -.001 

.006 .005 

-.017 -.005 

Art music	 .010 .025 

.012 .012 

.035 .075 

a 

TV arts programs	 .028 .016 

.009 .009 

.121 .061 

b 

d.f. 1,007 1,246 1,007 1,246 1,007 1,246 

R Squared .005 .024 .016 .042 .029 .050 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to .001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

188 
 

 

Appendix 

Appendix Table 5-27
 

Regression Analyses Predicting Number of Kinds of
 

Nonperformance Activities, by Gender
 

Model 1 Model 2 Model 3 

M F M F M F 

African­ -,093 -.293 -.083 -,164 -.084 -.140 

American .104 .095 .098 ,089 ,096 .087 

-.027 -.084 -.024 -.047 -.025 -.040 

b 

Hispanic .137 .020 .239 ,181 ,197 .133 

.140 .141 .132 .132 ,130 .128 

.029 .004 .052 .034 ,043 .025 

Age -.008 -.010 -.004 -.005 -.007 -.009 

.002 ,002 .002 ,002 .002 .002 

-.140 -.062 -.067 -.079 -.119 -,142 

d d a b c d 

Educa~on .056 .103 .023 .057 ,009 .031 

.012 .013 .012 ,013 .012 .013 

,178 .250 .075 ,139 .028 .076 

d d a d a 

OccupaSon .442 .043 .343 .059 ,286 .022 

,074 .071 .070 ,066 ,070 .065 

,200 .018 .156 ,025 .130 .009 

d d d 

Income x -,060 ,013 -.077 -,000 -.084 -.027 

10,000 .024 .023 .023 .021 .022 .021 

-.084 .017 -,107 -,001 -,117 -.035 

a c c 

Single/ .203 .292 .131 .185 ,099 ,171 

divorced .078 .075 .074 .070 .073 .068 

.086 .111 .055 .070 ,042 .065 

b d b a 

Lives in .044 -,130 -,025 -,180 -.041 -.218 

SMSA .069 .066 .065 .062 .064 ,060 

.019 -,054 -.011 -.074 -.018 -.090 

a b c 

189 
 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-27 (Continued)
 

Regression Analyses Predicting Number of Kinds of
 

Nonperformance Activities, by Gender
 

Model 1 Model 2 Model 3 

M F M F M F 

Childhood .218 .246 .191 .214 

lessons .025 .022 .025 .022 

.276 .316 .242 .274 

d d d c 

Parental .193 .138 .135 .050 

guidance .038 .033 .038 .033 

.160 .123 .112 .045 

d d c 

Hours TV/day -.038 -.043 

.028 .011 

-.071 -.098 

a d 

Art music	 .028 .033 

.028 .024 

.036 .043 

TV arts programs .107 .139 

.021 .019 

.175 .224 

d d 

d.f. 1,007 1,246 1,007 1,246 1,007 1,246 

R Squared .158 .156 .252 .267 .284 .317 

First row is unstandardized regression coefficient. 

Second row is standard error. 

Third row is standardized regression coefficient. 

Fourth row indicates significance: 

a less than or equal to .05 

b less than or equal to .01 

c less than or equal to ,001 

d less than or equal to .0001 

Based on data from November/December 1982 subsample. 

190 
 

Appendix 

Appendix Table 5--28
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Gender (Female [G]) for Selected Models
 

18 to 31 years 32 to 51 years over 51 years 

(N=728) (N=767) (N=757) 

b se beta b se beta b se beta 

D.V.:Lesson~* 

A .060 .209 .012 -.109 .175 -.023 -.240 .161 -.063 

H -.235 .273 -.035 -.251 .221 -.044 -.041 .283 -.006 

G .293 .122 .091(a) .034 .097 .013 .158 .088 .075 

D.V.: Home/* 

A .265 .106 .092(a) .222 .119 .065 -.138 .148 -.036 

H .192 .138 .052 .178 .151 .042 .280 .260 .041 

G .256 .062 .144(d) .215 .066 .112(b) .187 .081 .088(a) 

D.V.:TVarts- Model1 

A .132 .172 .029 -.148 .200 -.025 .179 .232 .027 

H .064 .241 .010 -.112 .260 -.0!4 .184 .372 .017 

G .116 .115 .037 .281 ,121 .077(a) .221 .132 .056 

D.V.:TVads- Model2 

A .312 .166 ,068 -.164 .186 -.028 .143 .215 .022 

H .349 .229 .054 -.009 .243 -.001 .052 .345 .005 

G -.017 .111 -.005 .100 .114 .027 .034 .123 .009 

D.V.: Art music- Model 1 

A -.383 .121 -.117(b) -.471 .153 -.101(b) -,568 .169 -.113(c) 

H .252 .170 .054 -.328 .200 -.053 -.167 .271 -.020 

G .243 .081 .108(b) .421 .093 .143(d) .288 .096 .095(b) 

D.V.: Art music- Model 2 

A -.254 .115 -.077(a) -.482 .147 -.103(b) -.585 .157 -.116 

H ,461 .161 .099(b) -.266 .192 -.043 -.255 .251 -.031 

G .154 .077 .069(a) .307 .090 .104(c) .154 .090 .051 

D.V,:A~end performance, inc.jazz- Model1 

A .081 .101 .029 -.110 .109 -.033 .085 .111 .027 

H -,157 .141 -.040 .016 .143 .004 .114 .178 .022 

G .130 ,068 .069 ,347 .066 .166(d) .178 .063 .095(b) 

D.V.:A~end performance, inc.jazz- Model2 

A .161 .098 .058 -.115 .105 -.035 .073 .109 .023 

H -.028 .138 -.007 .061 .137 .014 .084 .175 .017 

G .074 .066 .039 .273 .064 .131(d) ,141 .062 .075(a) 

D.V.:Attend pedormance, inc.jazz- Model3 

A .171 .095 .061 -.033 .103 -.010 .071 .105 .023 

H -.125 .131 -.031 .066 .133 .015 ,073 .166 .014 

G .085 .063 .045 .243 .063 .116(d) .136 ,059 ,073(a) 

191
 
 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-28 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Gender (Female [G]) for Selected Models
 

18 to 31 years 32 to 51 years over 51 years
 

(N=728) (N=767) (N=757)
 b se beta b se beta b se beta
 

O.V.:A~end performance, exc.jazz- Model1 

A -.141 .082 -.063 -.141 .097 -.048 .067 .102 .O23 

H -.111 .114 -.034 -.033 .126 -.009 .027 .163 .006 

G .158 .055 .102(b) .306 .058 .166(d) .164 .058 .095(b) 

D.V.:A~end performance, exc.jazz- Model2 

A -.086 .080 -.038 -.144 .094 -.050 .057 .101 .020 

H -.022 .113 -.007 .001 .123 .000 .003 .162 .001 

G .120 .054 .077(a) .250 .058 .136(d) .133 .058 .078(a.) 

D.V.:A~end perbrmance, exc.jazz- Model3 

A -.065 .079 -.029 -.065 .092 -.022 .052 .097 .018 

H -.092 .109 -.029 .012 .119 .003 -.008 .154 -.002 

G .133 .053 .086(a) ,217 .056 .118(d) .129 .055 .075(a) 

D.V.: Visuallyorientedconsum~ion -Model1 

A -.772 .172 -.153(d) -.750 .173 -.136(d) -.347 .182 -.061 

H -.296 .241 -.041 -.220 .226 -.030 -.004 .291 -.000 

G .919 .115 .266(d) 1.022 .105 .293(d) .783 .103 .230(d) 

D.V.: Visually oriented consumption - Model 2
 

A -.564 .160 -.112(c) -.738 .164 -.134(d) .377 .172 -.067(a)
 

H .034 .224 .005 -.107 .214 -.015 -.093 .276 -.010 

G .771 .107 .223(d) .900 .100 .258(d) .662 .098 .195(d) 

D.V.: Visuallyorientedconsum~ion -Model3 

A -.572 .154 -.113(c) -.581 .157 -.105(c) -.312 .159 -.055 

H -.1!4 .213 -.016 -.093 .203 -.013 -.090 .253 -.010 

G .791 .103 .229(d) .838 .096 .240(d) .641 .090 .188(d) 

D.V.: Performance a~ivities- Model1 

A -.012 .054 -.009 -.025 .058 -.016 .020 .042 .018 

H 

G 

.102 

.018 

.075 

.036 

.051 

.071 

-.024 

.066 

.076 

.035 

-.012 

.068 

.197 

.008 

.067 

.024 

.112(b) 

.013 

D.V.: Performance a~ivities- Model2 

A .011 .054 .008 -.025 .058 -.016 .019 .042 .018 

H .141 .075 .071 -.010 .076 -.005 .193 .067 .110(b) 

G .053 .036 .055 .048 .035 .049 .003 .024 .004 

192 
 

 

 

 

Appendix 

Appendix Table 5-28 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Gender (Female [G]) for Selected Models
 

18 to 31 years 32 to 51 years over 51 years 

(N=728) (N=767) (N=757) 

b se beta b se beta b se 

D.V.: Pefformancea~ivities- Model3 

A -.006 .054 -.004 .007 .058 .004 .008 .043 .008 

H ,114 .075 .058 -.001 .075 -.001 .187 .067 .106(b) 

G .066 .036 .045 .033 .035 .034 .005 .024 .007 

D.V.: Nonpefformanceacti~ties- Model1 

A -.533 .143 -.137(c) -.037 .120 -.011 .083 .090 .034 

H .103 .201 .019 -.002 .156 -.000 .265 ,144 .067 

G .243 .096 .091(a) .222 .072 .104(b) .114 .051 .078(a) 

D.V.: Nonpe#ormanceacti~ties- Model2 

A -.349 .131 -.090(b) -.025 .116 -.007 .073 ,085 .030 

H .411 .184 .075(a) .067 .151 .015 .224 .137 .057 

G .124 .088 .047 .160 .071 .075(a) .054 .049 .037 

D.V.: Nonpe#ormanceacti~ties- Model3 

A -.316 .127 -.081(a) .038 .115 .011 .079 .083 .033 

H .293 .175 .053 .067 .148 ,015 .214 .131 .054 

G .162 .085 .061 .138 .070 .065(a) .052 .047 .036 

*For starred models only, respondents without data on father’s and mother’s education excluded, and 

mother’s and father’s educal~onal attainment used as controls. Ns for these models are 629 for the 

18-30 group, 629 for the 31-51 group, and 480 for the over 51 group. Model numbers refer to their 

counterparts in Appendix tables 5-14 through 5-20. a: p less than or equal to .05; b: p less than or 

equal to .01 ; c: p less than or equal to .001; d: p less than or equal to .001. Analyses based on 

November/December 1982 subsample. 

193
 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-29
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Female Gender (G), by Own Educational Attainment, for
 

Selected Models 

1-11 years high school 

N=606 N=918 

O,Vo I.V. b se beta b se beta 

Childhood A -.156 .128 -.056 .250 .178 .050 

lessons H -.031 .181 -.008 -.101 .234 -.017 

G .202 .095 .094(a) .137 .094 .051 

Parental A .166 .093 .085 .191 .113 .061 

guidance H .350 .132 .127(b) .194 .150 .049 

G .!09 .070 .072 .166 .060 .098(b) 

TV arts A .065 .150 .018 .115 .188 .021 

programs H .115 .204 .024 -.172 .257 -.021 

(Modell)r G .084 .114 .031 .207 .110 .062 

TV arts A .091 .142 .026 .139 .178 .025 

programs H .182 .196 .038 .023 .257 .003 

(Model 2) G -.047 .110 -.017 .083 .103 .025 

Art music A -.501 .123 -.166(d) .-.241 .138 -.057 

(Model 1) H -.010 .168 -.002 .103 .202 .016 

G .160 .093 .068 .361 .081 .140(d) 

Art music A -.466 .120 -.154(d) .-.206 .132 -.049 

(Model 2) H .061 .164 .015 .215 .194 .034 

G .076 .091 .032 .294 .078 .114(c) 

Pe#orming-arts A -.008 .048 -.007 -.032 .085 -.013 

a~endance, H -.007 .066 -.004 -.024 .125 -.006 

includingjazz G .032 .037 .036 .214 .050 .139(d) 

(Model1) 

Pe#orming-arts A .006 .047 .005 -.022 .085 -.009 

attendance, H .022 .065 .014 .012 .124 .003 

includingjazz G .004 .036 .004 .191 .050 .124(d) 

(Model2) 

194 
 

 

 

Appendix 

Appendix Table 5-29 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Female Gender (G), by Own Educational Attainment, for
 

Selected Models 

1-11 years high school 

N=606 N=918 

D,V, I.V. b se beta b se beta 

Performing-arts A .018 .047 .016 .005 .081 .002 

attendance, H .006 .064 .004 -.016 .117 -.004 

including jazz G .008 .036 .009 .155 .047 .101(b) 

(Model 3) 

Performing-arts A -.052 .044 -.050 -.162 .074 -.073(a) 

attendance, H ,056 .059 -.040 -.003 .128 -.001 

excluding jazz G .049 .033 .060 .209 .043 .155(d) 

(Model 1) 

13-15 years 16 or more 

N=389 N=338 

D,M, I,V, se beta b se beta 

Childhood A -.375 .296 -.065 .133 .393 .019 

lessons H -.856 .359 -.121(a) -.473 .645 -.041 

G .159 .156 .051 .300 .167 .100 

Parental A .193 .169 .055 .090 .266 .019 

guidance H .058 .205 .013 -.543 .403 -.068 

G .438 .089 .230(d) .412 .105 .199(d) 

TV arts A -.247 .328 -.038 -.096 .470 -.011 

programs H .228 .413 .028 -1.003 .901 -.059 

(Model 1)/* G .187 .180 .051 .714 .233 .167(b) 

TV arts A .011 .317 .002 .034 .443 ,004 

programs H .530 .401 .064 -.475 .846 -.028 

(Model 2) G -.046 .177 -.013 .412 .224 .096 

Art music A -,693 .259 -.131(b) -,666 .302 -.110(a) 

(Model 1) H -.200 .326 -.030 -1.068 .579 -.092 

G ,577 ,142 ,194(d) .330 .150 .113(a) 

195 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-29 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Female Gender (G), by Own Educational Attainment, for
 

Selected Models 

13-15 years 16 or more 

N=389 N=338 

D.V. I.V. b se beta b se 

An music A -.441 .247 -.083 -.565 .295 -.093 

(Model 2) H .123 .312 .018 -.802 .567 -.069 

G .396 .138 .133(b) .184 .150 .063 

Performing-arts A -.137 .208 -.034 .156 .299 .027 

attendance, H -.126 .262 -.024 -.862 .572 -.079 

including jazz G .380 .114 .165 .653 .148 .238(d) 

(Model 1) 

Performing-arts A .035 .202 .008 .279 .289 .049 

attendance, H .115 .256 .022 -.546 .555 -.050 

including jazz G .290 .113 .126(a) .475 .147 .173(b) 

(Model 2) 

Performing-arts A .106 .192 .026 .310 .278 .054 

attendance, H .039 .241 .008 -.427 .529 -.039 

including jazz G .277 .108 .120(a) .388 .140 .141(b) 

(Model 3) 

Performing-arts A -.246 .180 -.069 -.069 .263 -.014 

attendance, H -.122 .227 -.027 -.848 .503 -.088 

excluding jazz G .366 .099 .183(c) .552 .130 .229(d) 

(Model 1) 

196 
Appendix 

Appendix Table 5-29 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Female Gender (G), by Own Educational Attainment, for
 

Selected Models
 

D,M, I.V. 1-11 years high school 

Performing-arts 

attendance, 

excluding jazz 

(Model 2) 

A 

H 

G 

-,041 

-.034 

.027 

.043 

.059 

.033 

-.039 

-.024 

.033 

-.157 

-.022 

.192 

.073 

.107 

.043 

-.071(a) 

-.007 

.143(d) 

Performing-arts 

a~endance, 

excludingjazz 

(Model3) 

A 

H 

G 

-.029 

-.047 

.030 

.043 

.058 

.033 

-.028 

-.033 

,037 

-.125 

-.003 

.162 

.071 

.102 

.041 

-.057 

-.001 

.121(d) 

Visually oriented A -.456 .120 -.151(c) -.857 .177 -.157(d) 

consumption H -.068 .163 -.017 -.301 .260 -.037 

activities G .559 .090 .235(d) 1.041 .104 .313(d) 

(Model 1) 

Visually oriented A -.429 .113 -.142(c) -.801 .167 -.147(d) 

consumption H -.015 .155 -.004 -.129 .245 -.016 

activities G .462 .086 .195(d) .942 .098 .283(d) 

(Model 2) 

Visually oriented A -,376 .110 -.125(c) -.742 .158 -.136(d) 

consumption H -.059 .149 -.014 -.174 .228 -.021 

activities G .464 .083 .196(d) .891 .092 .268(d) 

(Model 3) 

Performance A -.034 .037 -.040 .082 .043 .065 

activities H .101 .051 .086(a) .149 .064 .078(a) 

(Model1) G .009 .028 .013 .014 .025 .018 

Performance 

activities 

A 

H 

-.026 

.119 

.037 

.051 

-.030 

.101(a) 

.087 

.161 

.043 

.064 

.069(a) 

.085(a) 

(Model 2) G -,005 .028 -.007 .007 .025 .009 

Performance A -.045 .038 -.052 .080 .044 .063 

activities 

(Model 3) 

H 

G 

.113 

.001 

.051 

,029 

.096(a) 

.001 

.159 

.001 

.063 

.026 

.084(a) 

.001 

197 
Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-29 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Female Gender (G), by Own Educational Attainment, for
 

Selected Models 

D,Mo I.V. 1-11 years high school 

Nonperformance A -.118 .072 -.067 -.360 .115 -.106(b) 

activities H .150 .098 .063 -.027 .168 -.005 

(Model 1) G .119 .055 .086(a) .103 .067 .049 

Nonperformance A -.060 .065 -,034 -.308 .107 -.090(b) 

activities H .268 ,089 .112(b) .097 .157 .019 

(Model 2) G .032 .050 .023 .041 .062 .020 

Nonperformance A -.055 .065 -.031 .-.270 .106 -.079(a) 

activities H .247 .088 .103(b) .081 .153 .016 

(Model 3) G .037 .049 .027 .031 .062 .015 

D,M, I.V. 13-15 years 16 or more 

Performing-arts A -.113 .177 -.032 .022 .258 .004 

attendance, H .077 .223 .017 --.617 .495 -.064 

excluding jazz G .317 .099 .158(b) .421 .131 .175(b) 

(Model 2) 

Performing-arts A -.045 .168 -.013 .066 .248 .013 

attendance, H .015 .211 .003 --.497 .472 -.052 

excluding jazz G .300 .094 .150(b) .343 .125 .143(b) 

(Model 3) 

Visually oriented A -.931 .289 -.156(b) .-.554 .352 -.082 

consumption H -.251 .364 -.033 --.874 .675 -.067 

activities G 1,205 .158 .360(d) 1.089 .175 .334(d) 

(Model 1) 

Visually oriented A -.640 .276 -.110(a) .-.426 .339 -.063 

consumption H -.656 .349 .0!3 .-.531 ,651 -.041 

activities G 1.009 .155 .301(d) .906 .173 .277(d) 

(Model 2) 

Visually oriented A -.506 .260 -.085 .-.383 .321 -.057 

consumption H .011 .327 .001 -.373 .609 -.029 

activities G .947 ,146 .282(d) .790 .162 .242(d) 

(Model 3) 

198 
Appendix 

Appendix Table 5-29 (Continued)
 

Effects of Race (African-American [A]), Ethnicity (Hispanic [H]),
 

and Female Gender (G), by Own Educational Attainment, for
 

Selected Models
 

D.V. I,V. 13-15 years 16 or more 

Performance A -.069 .096 -.038 -.166 .138 -.066 

activities H -.061 ,121 -.026 -.196 .264 -.041 

(Model 1) G .098 .053 .095 .165 .068 .136(a) 

Performance A -.017 .096 -.009 -.153 .138 -,061 

activiSes H .011 .122 .005 -.158 .265 -.033 

(Model2) G .069 .054 .067 .146 .061 .120(a) 

Performance A .009 ,095 .005 -.108 .138 -.043 

activiSes H -.009 .120 -.004 -.096 .263 -.020 

(Model3) G .056 .054 .054 .131 .070 .108 

Nonperformance 

activi~es 

A 

H 

-.249 

-.048 

.225 

.283 

-.054 

-.008 

-.149 

-.348 

.293 

.562 

-.028 

-.033 

(Model1) G .374 .123 .145(b) .411 .145 .157(b) 

Nonperformance A -.011 .213 -.002 -.055 .283 -.010 

activities H ,286 .269 .049 -.091 .544 -.009 

(Model 2) G .253 .119 .098(a) .276 .144 .105 

Nonperformance A .057 .207 .012 .043 .273 .008 

activities H .231 .260 .040 .052 .520 .005 

(Model3) G .242 .116 .094(a) .200 .138 .076 

*/For starred analyses only, cases without information on mother’s or father’s educa’don were omitted 

and controls for mother’s and father’s education were included. For these models, Ns are 365 for 1-11 

years, 717 for high school graduate, 352 for 13-15 years, and 317 for 16 or more years. Model 

numbers refer to their counterparts in Appendix tables 5-14 through 5-20. a=p less than or equal to 

.05; b=p less than or equal to .01; c=p less than or equal to .001; d=p less than or equal to .0001. 

Results based on analyses of November/December 1982 subsample. 

199 
 

 

 

 

 

 

 

Race, Ethnicity, and Participation in the Arts 

Appendix Table 5-30: Coefficients Representing Effects of 

African-American (A) and Hispanic (H) on Core Participation 

Items (1) with Race/Ethnicity only (2) with Demographic Controls 

for November/December 1982 Subsample 

Jazz Classical Opera Musical Play 

1 2 1 2 1 2 1 2 1 2 

A b .745 1.039 -.931 -.513 1.188 -.953 -.961 -.501 -.930 -.436 

se .185 ,207 .295 .319 .920 .934 .229 .246 .296 .318 

sig b c a NS NS NS c a a NS 

b .030 .223 -1.790 -1.275 -.725 -.374 -.601 -.056 -1.164 -.547 

se .331 .351 .638 .654 1.079 1.098 .291 .312 .479 .499 

sig NS NS a NS NS NS a. NS a NS 

Ballet Art Instrument Act, sing Read 

1 2 1 2 1 2 1 2 1 2 

b -1.660 -1.422 -1,032 -.730 -,024 .078 ,034 .129 -.883 -.564 

se .729 .741 .216 .236 .351 .365 .324 .339 .136 ,157 

sig a NS c a NS NS NS NS c b 

H 	 b -.333 .044 -.472 -.008 .207 .410 .644 ,863 -.713 -.282 

se .574 .597 .257 .282 .456 .474 .363 .384 .192 ,219 sig NS NS NS NS NS NS NS a b NS 

b is the logistic regression coefficient, se is the standard error, sig refers to the level of statistical 

significance, where a=probability less than .05, b=probability less than .001, c=probability less than 

.00005, and NS=not significant. 

200 
ABOUT THE AUTHORS 

Paul DiMaggio is Professor of Sociology at Princeton University and author 

of Managers of the Arts (NEA Research Division Report #20, Seven Locks 

Press, 1986) 

Francie Ostrower received her Ph.D. in sociology from Yale University and 

is currently Assistant Professor of Sociology at Harvard University. 

201
 
Race, Ethnicity, and
 

Participation in the Arts
 

Based on evidence from two trail-blazing national surveys, this 

volume examines rates of participation of African-Americans, 

Hispanic-Americans, and whites in activities ranging from performing-arts attendance and visits to art museums, to creating craft 

works and performing onstage. The study reveals a pattern of 

differentiation without segmentation for the activities included in 

the survey: significant differences, but many activities and experiences held in common. The study goes beyond simply demonstrating that patterns of participation vary among the groups to ask 

why these differences exist, exploring the impact of such factors as 

education, gender, and income. The authors conclude by highlighting the need for future surveys to collect information on more 

activities with roots in many different ethnic and racial communities, and on the rich ethnic diversity within the groups studied. By 

opening up the issues, however, this volume serves as essential 

background for any discussion of cultural diversity and the arts in 

the United States. 

A survey report by 

Paul DiMaggio Francie Ostrower 

,Princeton Harvard University 

NATIONAL
 

ENDOWMENT
 

FOR~THE Research Division Report #25 

ARTS 

ISBN 0-929765-03-6