TURNING ON AND TUNINGIN
 

MEDIA PARTICIPATION IN THE ARTS 

,Charles M. Gray 

Research Division Report #33 
Turning On and Tuning In
 

Public Participation in the Arts via
 

Media in the United States
 
Turning On and Tuning In
 

Public Participation in the Arts via
 

Media in the United States
 

Charles M. Gray 

Research Division Report #33 

National Endowment for the Arts
 

Seven Locks Press
 

Carson, California
 
Turning On and Tuning In: Public Participation in the Arts via Media in the United 

States is #33 in a series on matters of interest to the arts community commissioned by 

the Research Division of the National Endowment for the Arts. 

Cover: Inside a mobile television truck during a Live~om Lincoln Center performance, 

"Luciano Pavarotti in Concert," transmitted nationally via the Public Broadcasting 

Service (PBS). Photo by Susanne Faulkner Stevens. 

First printed 1995 

Library of Congress Cataloging-in-Publication Data 

Gray, Charles M. (Charles Melvin), 1944-

Turning on and tuning in : public participation in the arts via media in the 

United States / Charles M. Gray. 

p. cm.- (Research Division report : 33) 

Includes bibliographical references. 

ISBN 0-929765-39-7 (paperback) 

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

II. Series: Research Division report (National Endowment for the Arts. 

Research Division) ; 33. 

NX220.G73 1995 

700’. 1’030973--dc20 95-34806 

CIP 

Manufactured in the United States of America 

Seven Locks Press 

Carson, California 

1-800-354-5348 
Table of Contents 

List of Tables 

List of Figures 

Preface 

Executive Summary 

PART I: Overview, Background, and Hypotheses 

Media Arts as Economic Goods 

"Supply" Factors 

Factors Influencing Arts Participation: Hypotheses 

PART I1: Participation Patterns and Changes, 1982-1992
 

Overview of Public Participation, 1992
 

Participation Patterns
 

Summary and Conclusions
 

PART II1: Multivariate Statistical Results 

Logistic Models 

Overall Logistic Regression Results 

Jazz 

Classical Music 

Opera 

Musicals 

Theater (Plays) 

Dance 

Art 

Summary 

PART IV: The Cross Effects of Media and Live Participation 

Jazz 

Classical Music
 

Opera
 

Musicals
 

Theater (Plays)
 

Ballet/Dance
 

Art
 

Summary and Conclusions
 

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vi I Turning On and Tuning In 

PART V:	 Summary and Conclusions 79 

Major Findings 79 

Policy Implications 8O 

Future Research 80 

APPENDIX A: 1992 Survey of Public Participation in the Arts 82 

APPENDIX B: Technical Discussion of Logistic Regression 89 

Notes 91 

Bibliography 94 

About the Author 95 

Other Reports on the 1992 SPPA 96 
Table of Contents I vii 

TABLES 

Table 1. 

Table 2. 

Table 3. 

Table 4. 

Table 5. 

Table 6. 

Table 7. 

Table 8. 

Table 9. 

Table 10. 

Table 11. 

Table 12. 

Table 13. 

Table 14. 

Table 15. 

Table 16. 

Table 17. 

Table 18. 

Table 19. 

Table 20. 

Table 21. 

Public Television Programming (Percentages of 

Broadcast Hours) 8 

Number of U.S. Radio Stations Offering Various 

Formats, 1992 9 

Manufacturers’ Shipments of Recorded Music 

(Millions of Units) 9 

Sales of Recorded Music by Genre (Percentage of 

U.S. Dollar Value) 10 

Live Arts Participation Rates by Place, 1992 

(Percentages of Adult Population) 11 

Arts Participation Rates by Income Group, 1992 

(Percentages of Adult Population) 13 

Rates of Public Participation in the Arts via Media, 1992 

(Percentages of Adult Population) 16 

Jazz Participation Rates by Variable, 1982 and 1992 

(Percentages of Adult Population) 17 

Change in Jazz Participation Rates by Age, 1982-1992 18 

Change in Jazz Participation Rates by Education, 

1982-1992 19 

Change in Jazz Participation Rates by Race, 

1982-1992 20 

Classical Music Participation Rates by Variable, 

1982 and 1992 (Percentages of Adult Population) 21 

Change in Classical Music Participation Rates by Age, 

1982-1992 22 

Change in Classical Music Participation Rates by Education, 

1982-1992 23 

Change in Classical Music Participation Rates by Race, 

1982-1992 24 

Opera Participation Rates by Variable, 1982 and 1992 

(Percentages of Adult Population) 26 

Change in Opera Participation Rates by Age, 1982-1992 27 

Change in Opera Participation Rates by Education, 

1982-1992 28 

Change in Opera Participation Rates by Race, 1982-1992 29 

Musical Participation Rates by Variable, 1982 and 1992 

(Percentages of Adult Population) 30 

Change in Musical Participation Rates by Age, 1982-1992 31 
viii I Turning On and Tuning In 

Table 22. 

Table 23.
 

Table 24.
 

Table 25.
 

Table 26. 

Table 27. 

Table 28. 

Table 29.
 

Table 30.
 

Table 31.
 

Table 32.
 

Table 33.
 

Table 34.
 

Table 35.
 

Table 36.
 

Table 37.
 

Table 38.
 

Table 39.
 

Table 40.
 

Table 41.
 

Table 42.
 

Table 43.
 

Table 44.
 

Table 45.
 

Table 46.
 

Table 47.
 

Table 48.
 

Table 49.
 

Table 50.
 

Table 51.
 

Change in Musical Participation Rates by Education,
 

1982-1992
 

Change in Musical Participation Rates by Race, 1982-1992
 

Theater (Plays) Participation Rates by Variable, 1982
 

and 1992 (Percentages of Adult Population)
 

Change in Theater (Plays) Participation Rates by Age,
 

1982-1992
 

Change in Theater (Plays) Participation Rates by
 

Education, 1982-1992
 

Change in Theater (Plays) Participation Rates by Race,
 

1982-1992
 

Ballet/Dance Participation Rates by Variable,
 

1982 and 1992 (Percentages of Adult Population)
 

Change in Ballet/Dance Participation Rates by Age,
 

1982-1992
 

Change in Ballet/Dance Participation Rates by Education,
 

1982-1992
 

Change in Ballet/Dance Participation Rates by Race,
 

1982-1992
 

Art Participation Rates by Variable, 1982 and 1992
 

(Percentages of Adult Population)
 

Change in Art Participation Rates by Age, 1982-1992
 

Change in Art Participation Rates by Education,
 

1982-1992
 

Change in Art Participation Rates by Race, 1982-1992
 

Variables, Definitions, and References
 

Logistic Regression, Jazz Participation, 1982
 

Logistic Regression,Jazz Participation, 1992
 

Logistic Regression, 

Logistic Regression, 

Logistic Regression, 

Logistic Regressmn, 

Logistic Regression, 

Logistic Regression, 

Classical Music Participation, 1982
 

Classical Music Participation, 1992
 

Opera Participation, 1982
 

Opera Participation, 1992
 

Musical Participation, 1982
 

Musical Participation, 1992
 

Logistic Regression,Theater (Plays) Participation, 1982
 

Logistic Regressmn,Theater (Plays) Participation, 1992
 

Logistic Regression,Ballet Participation, 1982
 

Logistic Regression,Dance Participation, 1992
 

Logistic Regression,Art Participation, 1982
 

Logistic Regression, Art Participation, 1992
 

Hypothetical Table Entries 

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Table of Contents I ix
 

Table 52. 

Table 53. 

Table 54. 

Table 55. 

Table 56. 

Table 57. 

Table 58. 

Table 59. 

Table 60. 

Table 61. 

Table 62. 

Table 63. 

Table 64. 

Table 65. 

Jazz Cross-Participation, 1982
 

Jazz Cross-Participation, 1992
 

Classical Music Cross-Participation, 1982
 

Classical Music Cross-Participation, 1992
 

Opera Cross-Participation, 1982
 

Opera Cross-Participation, 1992
 

Musical Cross-Participation, 1982
 

Musical Cross-Participation, 1992
 

Theater (Plays) Cross-Participation, 1982
 

Theater (Plays) Cross-Participation, 1992
 

Ballet Cross-Participation, 1982
 

Dance Cross-Participation, 1992
 

Art Cross-Participation, 1982
 

Art Cross-Participation, 1992
 

71
 

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x I Turning On and Tuning In 

FIGURES
 

Figure 1.
 

Figure 2.
 

Figure 3.
 

Figure 4.
 

Figure 5.
 

Figure 6.
 

Figure 7.
 

Figure 8.
 

Figure 9.
 

Figure 10.
 

Figure 11.
 

Figure 12.
 

Figure 13.
 

Figure 14.
 

Figure 15.
 

Figure 16.
 

Figure 17.
 

Figure 18.
 

Figure 19.
 

Figure 20.
 

Figure 21.
 

Jazz Participation Rates by Age, 1982 and 1992 (Percent)
 

Jazz Participation Rates by Education, 1982 and 1992
 

(Percent)
 

Jazz Participation Rates by Race, 1982 and 1992 (Percent)
 

Classical Music Participation Rates by Age, 1982 and 1992
 

(Percent)
 

Classical Music Participation Rates by Education,
 

1982 and 1992 (Percent)
 

Classical Music Participation Rates by Race, 1982 and 1992
 

(Percent)
 

Opera Participation Rates by Age, 1982 and 1992 (Percent)
 

Opera Participation Rates by Education, 1982 and 1992
 

(Percent)
 

Opera Participation Rates by Race, 1982 and 1992 (Percent)
 

Musical Participation Rates by Age, 1982 and 1992 (Percent)
 

Musical Participation Rates by Education, 1982 and 1992
 

(Percent)
 

Musical Participation Rates by Race, 1982 and 1992
 

(Percent)
 

Theater (Plays) Participation Rates by Age, 1982 and 1992
 

(Percent)
 

Theater (Plays) Participation Rates by Education,
 

1982 and 1992 (Percent)
 

Theater (Plays) Participation Rates by Race, 1982 and 1992
 

(Percent)
 

Ballet/Dance Participation Rates by Age, 1982 and 1992
 

(Percent)
 

Ballet/Dance Participation Rates by Education,
 

1982 and 1992 (Percent)
 

Ballet/Dance Partici ~ation Rates by Race, 1982 and 1992
 

(Percent)
 

Art Participation Rates by Age, 1982 and 1992 (Percent)
 

Art Participation Rates by Education, 1982 and 1992
 

(Percent)
 

Art Participation Rates by Race, 1982 and 1992 (Percent)
 

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Preface 

Much of the data analysis and writing of this monograph was conducted 

while I was a visiting professor in the Department of Political Science-­

the organizational home of the Administration of Justice and Master of Public 

Administration programs--at the University of North Carolina-Chapel Hill. 

I am deeply indebted to a number of departmental colleagues and university 

staff members who overlooked the fact that I am an economist and helped 

create a welcoming atmosphere. Chairman David Lowery and Professor 

George Rabinowicz were especially supportive. Candy Terrell, department 

administrator, simply made things happen. Sue Dodd and Josie Marsh of the 

Institute for Research in the Social Sciences were instrumental in arranging to 

have the data tape uploaded and cataloged; and Jim Cassell provided answers 

to technical questions. One of my co-researchers, Jeffrey Love of the National 

Assembly of State Arts Agencies, provided reassurances regarding data, analytical techniques, and results. Tom Bradshaw of the National Endowment for 

the Arts (NEA) was supportive throughout this process, as my ideas evolved 

and as Murphy’s Law brought down disks both hard and floppy, disabled entire 

computing systems, uncovered previously unknown software glitches, and 

otherwise impeded progress. 

This research was completed under contract for the National Endowment 

for the Arts. Ideas and opinions expressed are those of the author and do not 

reflect an official position of the NEA or any other public or private agency. 

Any errors or omissions are solely the responsibility of the author. 
Executive Summary 

This monograph examines and interprets survey data pertaining to public 

participation in the arts via television, radio, and sound recordings. The data 

derive from 1982 and 1992 surveys of leisure activities and public participation 

in the arts conducted by the U.S. Bureau of the Census and funded by the 

National Endowment for the Arts (NEA). The seven "core" or "benchmark" 

arts, listed in their order on the survey instruments, are jazz, classical music, 

opera, musicals and operettas, plays, dance, and the visual arts. 

Participation via media is especially important for at least two reasons: media 

may provide arts access to those who are otherwise unable to participate through 

live attendance--because of location, income, or other factors; and the media 

may be influential in cultivating a taste for the arts, which could lead to higher 

overall participation. 

While the primary focus of this monograph is participation by media, 

appropriate comparisons dictate that the analyses be extended to participation 

in live performances and live attendance as well. Many of the hypothesis tests 

necessarily include such live alternatives. 

Although we can speak meaningfully of "arts markets," the arts are widely 

regarded as entailing rnarleetfailures, one of which is especially important for 

the purposes of this research.1 The so-called exclusion principle, by which those 

who do not purchase a good or service are denied use, fails in the case of the 

broadcast media. Anyone with a receiver can listen to or view all programming, 

including arts programming. This is an important factor in providing arts access 

to lower income groups, and it informs the hypotheses developed below. 

Public participation in the arts, like consumption of any other good or 

service, is influenced by willingness and ability to pay. Willingness to pay 

encompasses consumer tastes and preferences, which are themselves very likely 

linked to identifiable demographic characteristics. Ability to pay is influenced 

largely by household income and purchase price. 

Simple bivariate techniques are used to test--and confirm--the hypotheses 

put forth in this monograph, but the conclusions rely primarily on logistic 

regression, a multivariate statistical technique that is especially well suited for 

this kind of data. (Logistic regression is further explained in Part III, as well as 

Appendix B.) The hypotheses tested in this monograph, and the results obtained, are as follows: 
2	 I Turning On and Tuning In 

 ̄	 Arts participation increases with age. The taste for art is an acquired or 

cultivated taste, and both acquisition and cultivation are time-dependent 

processes. It is said that one must learn how to enjoy the arts. Potentially 

offsetting this influence for older persons is their reduced mobility in 

attending live performances and the special challenge of adapting to new 

technology, which would influence media participation. The results for the 

most part support the hypothesis. The major exception is jazz participation, 

which seems to be a young persons’ art form. For other art forms and media, 

participation rates rise at least through the middle-age group and sometimes 

decline for the oldest group. 

 ̄	 An aging population will increase arts participation. This is really a 

corollary of the first hypothesis. It would follow that if participation rises 

with age, then an overall older population, other things being equal, would 

participate in the arts at a higher rate. Unfortunately, other things have not 

been equal. Specifically, participation rates among young adults and "30­

somethings" fell over the decade for many of the art forms and media 

categories, partially or totally offsetting the impact of an aging population. 

This suggests another matter deserving consideration: If arts audiences are 

aging and no efforts are made to increase participation among younger 

groups, the audiences will not be replenished. 

 ̄	 Arts participation increases with education. Students are exposed to the 

arts at every level of education, with the possible exception of postgraduate 

studies. From primary school rhythm bands through college art appreciation 

classes, students have the opportunity to gain increasingly sophisticated 

participation skills. With negligible exceptions, the results bear out the 

hypothesis. Participation rates for the college educated often are double 

those of less educated groups. The downside is that participation rates for 

the more highly educated segments have declined over time. 

 ̄	 Arts participation rises with income. At the very least, those in higher 

income categories are better able to afford arts participation. A relatively 

large segment of the population may regard the prices of symphony tickets 

and compact discs, for example, as high compared with their incomes. The 

statistical results are consistent with the hypothesis. 

 ̄	 Income plays a reduced role in participation via the broadcast media as 

compared with participation via live and recorded performances. The 

broadcast media entail no explicit user charge beyond possession of a 

receiving unit; subsequent participation requires no additional ability to 

pay. Live participation typically involves an admission fee, and listening to 

a recording follows a purchase by the listener or someone else. The tabular 

presentations and statistical results are consistent with this hypothesis. 

 ̄	 Urban residents are more likely to participate in the arts than are rural 
Executive Summary I 3 

residents. Most live participation opportunities are located in urban areas. 

It is likely that the availability of live arts creates a taste that can also be 

served through participation via media. The results bear out this expectation 

for each art form and for every medium, as well as for live performances. 

The ratios of urban-to-rural participation rates are declining, however, 

especially for the broadcast media, indicating that urban location was not 

so important a relative determinant of participation in 1992 as in 1982. 

This is further supported by the logistic regressions, where the urban 

coefficients in the broadcast equations declined from 1982 to 1992. 

Urban residence is not so important a determinant of participation via the 

broadcast media and recordings as it is for participation via live attendance. While this outcome is not so clear in the simple tabular displays, the 

logistic regression coefficients linking urban residence to arts participation 

are consistently higher for live attendance in both survey periods. 

Men are less likely to participate in the arts than are women. This 

hypothesis is premised on greater early exposure to the arts through lessons 

and other opportunities for personal involvement for girls as compared to 

boys.2 To the extent that this is the case, and to the extent that such exposure 

is instrumental in forming tastes and preferences, men are less likely to have 

developed such taste. The results confirm this hypothesis for all art forms 

except jazz. 

Whites are more likely to participate in the arts than are other racial 

groups. This hypothesis arises from the understanding that much of the art 

and culture of the United States has European roots that may not be 

immediately accessible to minority cultures. Accordingly, one would expect 

nonwhite participation to be lower. The results are generally consistent with 

this hypothesis, the exceptions being greater black participation in jazz and 

occasionally greater participation by respondents of Asian heritage. 

Conclusions 

The data generally support every hypothesis. Among the policy implications 

supported by the findings are the following: 

Some television channels can be dedicated to arts programming. This is 

similar to radio stations adopting a format, which means that, for example, 

televised opera--live or prerecorded---could be available to viewers 24 hours 

a day. The advent of cable access to literally hundreds of channels can 

facilitate the development of dedicated programming. This supply factor 

may well be an important explanation for the higher radio participation in 
4 I Turning On and Tuning In 

jazz and classical music, compared with television participation in those art 

forms. 

Arts organizations may explore greater use of videotapes--music videos for 

the cultured. Just as many symphony orchestras have found CDs to be a 

source of revenue and exposure, the development of integrated audio-video 

stereophonic systems may offer opportunities for videotape marketing. 

Educators can further enhance exposure to the arts at all levels. Arts 

education may have been at least a partial victim of the educational fads of 

the last several years, including elimination of required college courses in 

the 1970s. The threatened diminution of our society’s cultural core may 

justify restoration and expansion of such courses. Many arts organizations 

already collaborate with local school systems to offer arts exposure, and this 

process could be expanded. The arts could also be directly involved in the 

adoption of new learning technology, including distance learning via television, computer linkages, and CD-ROMS. 
Overview, Background, 

and Hypotheses 

H istorically, people who wanted to experience the performing or visual arts 

were largely dependent upon geographic proximity. It was necessary to 

attend the theater or the opera or to visit an art museum or gallery. Such 

participation was therefore limited to those who resided in or visited urban areas, 

or who benefited from a visit by a touring company. Since most of the 

population before the 20th century was rural, the opportunities for such artistic 

experiences were severely limited. The advent of recorded and broadcast media, 

however, altered the accessibility of artistic participation, although the form of 

participation was altered as well. One could, of course, argue that a televised 

concert, dramatic performance, or other arts presentation is a fundamentally 

different experience from live attendance. While no one would seriously contend that a two-dimensional, small-screen viewing of the American Ballet 

Theater is identical to live attendance, some may regard the televised version as 

a viable alternative. This is especially true for those who enjoy dance but who 

have no easy access to performing venues. 

This monograph examines and interprets survey data related to participation 

in the arts via the media. The data derive from 1982 and 1992 surveys of leisure 

activities and public participation in the arts, conducted by the U.S. Bureau of 

the Census and funded by the National Endowment for the Arts) Respondents 

were queried about their participation in seven "core," or "benchmark," arts 

activities via electronic media, including both broadcast and recorded media. 

The broadcast media are radio and television, and their recorded counterparts 

include compact discs (CDs), cassette tapes, vinyl recordings, and videotapes. 

(See Appendix A for the 1992 Survey of Public Participation in the Arts.) 

This monograph gives special attention to the factors that distinguish those 

survey respondents who participate only through the media and those for whom 

the media constitute a complementary means of participation. And although 

the survey questions changed from 1982 to 1992 (for example, "dance" replaced 

the narrower category of "ballet") and technology has evolved (neither VCRs 

nor CDs were widely used in the earlier period), the monograph also discusses 

changes in participation over time. 

The emphasis here is upon each medium as a means of transmitting art rather 

than as an art form in itself. Under certain circumstances, of course, the media 

can become "plastic art": television screens and radio broadcasts have been used, 
6 I Turning On and Tuning In 

for example, in dance performances and music concerts. But here the references 

are quite specific: jazz, classical music, opera, musical plays and operettas 

(musicals hereafter), theater (plays), dance and ballet (dance, usually), and 

museums and the visual arts (art), as conveyed by media. 

As a means of transmitting art, the broadcast media are perhaps especially 

influential in cultivatingthe taste for art as well.4 Although the evidence to date 

is inconclusive, the media may play a significant role in creating arts markets. 

The challenge facing the media in this latter regard is apparent from the fact 

that neither broadcast nor cable television offers significant arts programming, 

having yielded most such offerings to the Public Broadcasting System (PBS).5 

Media Arts as Economic Goods 

In most markets, the forces of supply and demand interact to bring about 

a reasonably efficient allocation of goods and services. Demand reflects the 

willingness and ability of consumers to purchase the good in question. The 

willingness to purchase reflects tastes and preferences, which are indicated to a 

large extent by such demographic characteristics as education, age, gender, race, 

and other taste-determining variables. Ability to purchase is typically indicated 

by household income. Likewise, supply reflects the willingness and ability of a 

seller to make the good available and is largely determined by the costs of 

production. Since the focus here is on the arts participant, those elements that 

influence demand will bear closest scrutiny. 

Matters are complicated somewhat by the fact that all of the media considered in this monograph entail one or another type of market failure, which 

means that the forces of supply and demand encounter some sort of interference. 

One of the primary examples in the arts generally is the existence of collective 

benefits, whereby society as a whole gains some benefits in excess of those 

accruing to the actual purchaser of a good or service. For example, a person who 

purchases and wears a pair of shoes enjoys the benefits of doing so; few if any 

benefits accrue to other individuals. But if enough individuals purchase season 

tickets to the opera, the local community may be enriched in ways that exceed 

the benefits to ticket purchasers.6 

Other types of market failure are of more immediate interest, however. The 

person who refuses to pay the price for a pair of shoes will not ordinarily be able 

to acquire the shoes. He or she is excluded from acquiring and subsequently 

enjoying the goods in question. This exclusion principle applies not only in the 

shoes example, but to any other purely private goods as well. The broadcast 

media are, however, very different. Once an individual or a household has 

purchased a receiving unit, any subsequent broadcasts can be received at no 
Overview, Background, and Hypotheses 7 

additional charge. Short of employing some sort of scrambling and unscrambling devices, the broadcaster is unable to exclude anyone from receiving the 

broadcasts. This suggests that household income, as a measure of ability to pay, 

may not be so important in determining who participates in the arts via 

broadcast media. The same is true of cable television, albeit perhaps to a lesser 

extent. Most channels are available in a variety of packages for a corresponding 

variety of monthly fees. Except for "pay-per-view" programming, all programs 

in the selected channel package are available at no additional user charge. Again, 

income may not be an important determinant of participation. 

Live performances and recordings have elements of both private goods and 

public goods. In the case of live performances, those who refuse to purchase a 

ticket can be excluded, assuming the performance venue has the means of 

physical exclusion. On the other hand, such performances entail nonrival 

consumption, at least up to the capacity of the performing space. Not only does 

one person’s participation not detract from that of another, their mutual 

attendance may, in fact, enhance each other’s experience; for example, the sound 

in most concert halls improves when seats are filled. 

Although listening to a recording entails nonrival consumption (numerous 

individuals can, after all, simultaneously listen to a CD on a stereo system), the 

actual purchase of the CD adheres to the exclusion principle. If someone 

purchases a specific CD, no one else can purchase that one, although, of course, 

precise replicas are likely available at the same price. Nevertheless it is the 

existence of a price that is the key, and both a live performance admission fee 

and a CD price mean that ability to pay--income--may be a more significant 

determinant of participation than in the broadcast media. 

"Supply" Factors 

Market sales data typically portray a market outcome influenced by both 

supply and demand forces. This would certainly be the case for CDs or 

videotapes. This is not so obviously the case for the broadcast media, where 

supply and demand do not interact in the usual fashion.7 Nonetheless, the data 

discussed below indicate the general availability of selected media alternatives. 

Television 

Portraying one measure of the supply of televised arts, Table 1 indicates the 

distribution of cultural programming on public television from 1974 through 

1992. Although the term culturalis not defined precisely, it very likely extends 

beyond the benchmark arts discussed here to embrace literature, motion 
 

 

8 I Turning On and Tuning In 

TABLE 1.	 Public Television Programming (Percentages of 

Broadcast Hours) 

Program 

Content 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 

General 

News and 

public affairsa 12.6 11.9 11.0 12.2 12.4 14.1 16.4 16.3 17.6 17.4 

Information 

and skills 15.9 19.9 23.6 22.8 24.5 25.5 29.5 31.7 31.5 28.7 

Cultural 17.9 20.9 22.1 21.9 22.6 20.1 20.5 17.9 19.1 17.5 

General children 

and youthb 10.7 10.0 8.7 8.9 7.5 7.9 6.5 5.8 6.0 1 4.6 

"Sesame Street" 21.2 17.8 16.1 15.5 14.8 14.8 11.4 11.7 11.2 1t~0 

Other general 4.4 3.8 5.3 5.5 4.8 5.5 1.6 1.2 0.9 0.9 

Instructional c 

Children 

and youth 15.2 15.2 13.7 13.7 12.9 12.4 8.7 

Adult 1.9 1.4 1.2 1.0 1.4 0.6 -­ -­ -­ 2.9 

Note: Figures do not add up to 100 due to rounding. 1974 and 1976 are calendar 

years; 1978 to 1990 are fiscal years; 1988 through 1992 surveys used October 

through September seasons. From 1988 through 1992, only broadcasters in the 50 

U.S. states were surveyed. 

a. From 1986 through 1992, the News and Public Affairs category included "Business 

or Consumer." 

b. Not including "Sesame Street," which is reported separately. 

c. After 1974, some general audience programs with instructional applications were

double counted if aired during school hours when school was in session. 

Source: Unpublished data provided by Janice Jones, media research analyst, 

Corporation for Public Broadcasting 

pictures, and popular culture. The rise that took place in the early 1980s in the 

percentage of broadcast hours devoted to cultural programming had diminished 

by the early 1990s. The 1992 percentage of 17.5, in fact, was the lowest of all 

the years covered. To be sure, some of the children and youth programming 

may include cultural aspects, and that may be a particularly propitious inclusion, 

to the extent that media exposure helps shape tastes. But it is clear, based on the 

data in Table 1, that cultural programming directed specifically to adults, that 

is, arts via television, has been waning. 
 

Overview, Background, and Hypotheses I 9 

Radio 

TABLE 2. Number of 

Similarly, Table 2 offers some informa- U.S. Radio Stations 

tion on the availability of the benchmark Offering Various arts via radio. Lacking the visual aspect of Formats, 1992 television, radio, of course, presents only 

the audible arts: jazz, classical music, opera, Total 

Format Stations and musicals. Clearly, far more stations 

offer rock, country, and other musical for- Adult contemporary 2,288 

mats than either classical or jazz.	 Beautiful music 271 

Top-40 767 

Recordings Country 2,651

MOR 528 

News 596 Table 3 displays trends in unit ship- Oldies 1,031 ments of recorded music from 1983 to Religious 1,144 

1993. The change in technology over that Rock 584 

period is apparent in the appearance and Talk 388

Classical 442 rapid expansion of compact discs (CDs) Jazz	 367 and music videos and the near demise of 

Note: Table data cover only the long-playing vinyl albums (LP/EP) and those stations providing format singles. Unit shipments of CDs grew at an information. 

average annual rate of 90.2 percent, while	 Source: Broadcasting and Cable 

CD singles, introduced somewhat later, Yearbook, 1993

expanded at a 34.3 percent annual pace. 

Shipments of cassettes peaked in 1988 

and declined thereafter, for an average growth rate over the entire period of only 

3.7 percent. The declines in shipments of long-playing and single vinyl recordTABLE 3.	 Manufacturers’ Shipments of Recorded Music
 

(Millions of Units)
 

Item 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 

CD 0.8 5.8 22.8 53.0 102.1 149.7 207.2 286.5 333.3 407.5 495.4 

CD
 

single NA NA NA NA NA 1.6 -0.1 1.1 5.7 7.3 7.0
 

Cassette 236.8 332.0 339.1 344.5 410.0 450.1 446.2 442.2 360.1 366.4 339.5
 

LP/EP 209.6 204.8 167.0 125.2 107.0 72.4 34.6 11.7 4.8 2.3 1.2
 

Single 124.6 131.5 120.7 93.9 82.0 65.6 36.6 27.6 22.0 19.8 15.1
 

Music
 

video NA NA NA NA NA NA 6.1 9.2 8.1 7.6 11.0 

Note: Figures refer to net number of units after returns.
 

Source: Recording Industry Association of America
 
10 I Turning On and Tuning In 

ings were at average annual rates of-40.3 and -19.0 percent, respectively. 

Compared with CDs, music video shipments grew at a relatively modest average 

annual pace of 15.9 percent. 

The relative importance of two of the benchmark arts on recordings is 

indicated by the percentage of U.S. dollar sales accounted for by jazz and classical 

music. As Table 4 shows, rock music sales are by far the largest category, with 

country and pop a distant second and third, respectively. Classical and jazz are 

much further down the list. Both show a decline over the period covered, 

although the classical pattern is mixed and the jazz trend may reflect the 1991 

appearance of the "Urban Contemporary" category. 

Factors Influencing Arts Participation: Hypotheses 

Before the data presentations and statistical analyses of Parts II and III of 

this monograph, it is appropriate to consider some of the factors expected to 

influence arts participation. These give rise to the hypotheses that provide a 

framework or focus for the analyses. 

The Impact of Place 

The existence of economies of agglomeration in the art and culture industry 

now seems well established.8 Such economies occur when firms are able to share 

one or more common productive factors in a given geographic region. For 

example, domestic automobile firms historically chose to locate in or near 

Detroit because they could share a trained labor force, transportation infrastructure, and access to raw materials. Similarly, radio and television programming 

TABLE 4. Sales of Recorded Music by Genre (Percentage of 

U.S. Dollar Value) 

Genre 1989 1990 1991 1992 1993 

Rock 42.9 37.4 36.3 33.2 32.6 

Country 6.8 

Pop 14.4 

Urban contemporary NA 

Rap NA 

Classical 4.3 

8.8 

13.6 

NA 

NA 

4.1 

12.5 

11.7 

9.3 

8.9 

3.9 

16.5 

11.4 

8.8 

7.9 

4.4 

17.5 

11.7 

9.9 

7.8 

4.0 

Jazz 5.7 5.2 4.3 4.0 3.3 

Source: Recording Industry Association of America, 1993 Consumer Profile 
Overview, Background, and Hypotheses I 11 

were drawn to New York City and to Hollywood because of those locations’ 

respective talent pools generated by Broadway and the motion picture industry. 

Another factor causing the arts to play a disproportionately large role in 

places with larger populations is the existence of threshold market sizes. Whereas 

a small community could scarcely support a symphony orchestra or a major art 

museum, most major metropolitan areas are able to support both, and additional 

cultural organizations as well. 

Accordingly, one might expect that residents of urban regions would 

generally exhibit a greater likelihood of attending the live arts if for no other 

reason than because of greater availability. The data in Table 5 demonstrate that 

pattern. It is not so obvious that urban location is as conducive to participation 

via the media. Indeed, one could hypothesize in either direction: (1) urban 

location, which facilitates live attendance, facilitates development of a taste for 

the arts, which can also be partially 

satisfied by media participation; or 

(2) rural residents, denied ready ac-	 TABLE 5. Live Arts 

Participation Rates by Place, cess to live arts attendance, compensate through heavier media 1992 (Percentages of Adult 

participation. Population) 

One might reasonably assume Percentage that media participation is not so Art Form Urban Rural 

constrained as live participation.
 

Television and radio signals reach Jazz 12.2 6.3
 

Classical music 13.8 9.1 into the hinterlands, and recorded Opera	 3.7 2.1 music is widely available. One need Musicals 19.2 12.8 

not reside in a major metropolitan Plays 15.3 8.5 

Dance 7.6 5.9 area to tune in to public radio or Art museum 29.8 18.5 television or to purchase a CD. Yet, 

as we shall see in subsequent chapters, media participation is also greater in urban areas than in rural areas. For 

example, participation through television is greater in urban than in rural areas 

for all the benchmark arts, although the relative proportions differ somewhat. 

Age 

Culture, it is said, is an acquired taste, and acquisition of taste takes time. 

It would follow then that participation would increase with age. The adult 

population has been classified into four groupings for the purposes of analysis 

in this monograph: young adults (18 through 29), "30-somethings" (30 through 

44), middle-age (45 through 64), and "retired" (65 and above). These groupings 

are not entirely arbitrary. The youngest range from traditional college age to 
12 I Turning On and Tuning In 

those who, although in their late 20s, are still in the early stages of their adult 

lives. The 30-somethings, a category that actually extends into the mid-40s, 

have had opportunities to become established in their chosen lifestyles, to incur 

the obligations of adulthood, and to have made a career move or two. The 

middle-age range encompasses a variety of life experiences. The retired group, 

many of whom may not be retired at all, are experiencing the culmination of 

life’s experiences. 

Education 

One way we acquire a taste for culture and the arts is exposure through 

education. It has been argued that appreciation of the more complex arts 

requires investment in "consumption skills," that is, learning to understand, say, 

opera.9 Elementary and secondary school curricula typically offer art and music 

classes, and most colleges offer--and many require--art or music appreciation 

courses. Accordingly, we would reasonably expect participation to rise as 

education level rises. 

For purposes of subsequent analyses, reported years of education have been 

aggregated into four groups: (1) none (respondents indicated zero years of 

education); (2) elementary (education did not proceed beyond grades 1 through 

8); (3) high school (grades 9 through 12); and (4) college (including college and 

postgraduate education). 

Income 

The most obvious means by which income would impact arts participation 

would be ability to pay. Clearly, persons with higher incomes are more likely to 

be able to afford to attend a performing arts activity, to visit a museum, or to 

purchase a CD.1° They are also more likely to purchase one or more television 

sets and radios; but in this latter case, once the device is purchased, the 

incremental costs of viewing or listening to the arts are likely to be very close to 

zero, especially for broadcasts or the more widely available cable channels. 

As the data in Table 6 clearly indicate, both live and media participation 

rise with income. The difference is unlikely to be attributable to television access; 

in 1992, 93.7 percent of persons in households with incomes of less than 

$10,000 watched television, as did 95.2 percent of those in households with 

incomes between $10,000 and $20,000.11 Interestingly enough, radio listening 

rises significantly with income category, from 77.4 percent of those individuals 

in the lowest income category to 91.6 percent of those in the highest.12 But 

given the low prices of the simplest radios it seems unlikely that this reflects 

ability to pay. It would follow that the relationship between household income 
Overview, Background, and Hypotheses 13 

TABLE 6. Arts Participation Rates by Income Group, 1992 

(Percentages of Adult Population) 

Income Level 

Art Form/Medium Poverty Low Moderate High 

Jazz 

Live 5.2 8.1 12.4 22.1
 

Television 12.5 17.2 19.5 27.9
 

Radio 18.8 24.3 31.9 44.4
 

Recorded 11.4 16.6 23.9 37.5
 

Classical music 

Live 5.8 9.3 14.4 28.6
 

Television 15.2 19.5 23.2 38.1
 

Radio 19.8 24.7 34.9 53.4
 

Recorded 12.7 17.7 27.8 45.2
 

Opera 

Live 1.8 1.7 3.3 12.2
 

Television 7.7 9.0 11.4 18.0
 

Radio 5.4 6.3 9.6 17.9
 

Recorded 3.1 3.8 7.9 16.0
 

Musicals 

Live 7.6 12.6 20.2 42.3
 

Television 9.1 11.9 13.2 18.7
 

Radio 2.7 2.9 3.6 6.4
 

Recorded 3.0 3.8 6.3 13.1
 

Plays 

Live 6.8 9.9 15.2 31.8
 

Television 10.0 12.2 16.8 24.7
 

Radio 2.4 2.3 3.1 4.2
 

Dance 

Live 4.6 6.3 8.2 9.5 

Television 14.2 17.0 17.3 25.0 

Art 

Live 13.4 20.6 31.6 49.8 

Television 21.8 27.4 33.0 44.1 

and broadcast media participation reflects influences of taste rather than purchasing power. 

For analytical purposes, the several reported income bands were aggregated 

into four groups. These have been characterized as (1) "poverty," the lowest 

group (which does not necessarily correspond to census definitions of poverty 
14 I Turning On and Tuning In 

level); (2) "low"; (3) "moderate," which may be regarded as "middle class"; and 

(4) "high." Because of changes in both price levels and income groupings, the 

four groups are not comparable between the two time periods. 

Gender 

No obvious or intrinsic reason leads one to expect differential participation 

rates between men and women. Yet the differences are well known: women 

participate in the arts at higher rates than men. Perhaps this is rooted in early 

acculturation processes, when boys were often channeled into sports to the 

exclusion of arts. 

Race 

As with gender, there is no obvious source of race-based differentials in arts 

participation. Accounting for other factors that are correlated with race, such as 

income and education, may not eliminate racial differences. Racial or ethnic 

groups that are not European in origin may not be strongly attracted to such 

art forms as symphonic music and traditional opera, which are firmly rooted in 

Western artistic traditions. Minority groups may feel excluded from "mainstream" arts. The racial groupings of the survey are collapsed into white, black 

(African American), Asian, and Indian (including all Native Americans). Respondents of Hispanic origin are identified separately and do not identify 

themselves in only one of the racial groups. 
Participation Patterns and 

Changes, 1982-1992 

This part describes participation patterns in the arts via media, with particular 

focus on the roles of selected population demographic characteristics as 

suggested by the hypotheses of Part I. Tables and figures accompanying the text 

help to illustrate audience patterns and trends. The first section offers an 

overview of public participation for 1992, the most recent survey period. The 

second section contains more detailed participation data, and is organized by 

benchmark arts activity, beginning with jazz. The participation patterns are 

examined and discussed, including variations over time. The final section 

summarizes the findings. 

Overview of Public Participation, 1992 

Table 7 summarizes public participation data for each of the benchmark 

activities and each of the media alternatives for 1992. The last column of the 

table includes live participation for comparison purposes. With the exception 

of videocassette viewing, media participation tends to exceed live participation 

across the board. Musicals and plays, however, with their significant visual 

components, do not attract larger audio media audiences in the way that the 

other benchmark activities do. These data reflect the fact that the household 

penetration of television enables quick, easy, and relatively low cost access to 

televised arts. Participation by radio is higher for jazz and classical music, but 

television participation is higher for the performing arts--opera, musicals, and 

plays--with a notable visual component. 

The levels ofvideocassette participation attest to the novelty of this medium 

as a means of arts participation. These comparatively modest rates suggest 

further analysis to be of limited benefit, but the data provide at least a baseline 

for future comparisons. 

Participation Patterns 

The following subsections examine participation rates for various demographic factors for each of the benchmark arts for the years 1982 and 1992. 

Each subsection includes a comprehensive table depicting participation rates by 
16 I Turning On and Tuning In 

TABLE 7.	 Rates of Public Participation in the Arts via Media,
 

1992 (Percentages of Adult Population)
 

Art Form Television Video Radio Recordings Performance 

Jazz 17.9 1.0 28.2 20.6 10.6
 

Classical music 21.9 1.2 30.8 23.8 12.5
 

Opera 10.7 0.5 8.7 6.9 3.3
 

Musicals 12.5 1.8 3.5 5.7 17.5
 

Plays 14.8 1.3 2.8 NA 13.5
 

Dance 17.1 0.8 NA NA 7.1
 

Art 30.1 NA NA NA 26.7
 

the variables already indicated: urban versus rural, gender, education, age, race, 

and income. The tables offer a summary of participation rates in each year as 

well as a comparison of rates over time. In addition to the tables, charts and 

associated tables offer a quick overview of participation rates and changes over 

time and by medium for age, education, and racial groups. Income is not 

accorded a separate chart since the data are not comparable over time. Those 

variables--location and gender--that take on only two values also do not merit 

separate charts. The tables and charts do not include the relatively minuscule 

"none" group of the education variable. 

Two statistical tests were applied to each component of the tables: a Pearson 

chi-square test of independence and a ])hi-coefficient, which indicates strength of 

association. In every instance, the Pearson test indicates that the variables (e.g., 

participation by race, participation by income, etc.) are not independent of each 

other--that is, the observed patterns are not simply random events. Furthermore, the phi-coefficient indicates in every case that the associations are 

statistically significant. A major shortcoming of this approach--measuring 

association by two variables at a time--is that it could be misleading. For 

example, an apparent association between participation and income may actually reflect an association between participation and education, which is strongly 

correlated with income. This limits the inferences that can be drawn from the 

tests. Part III draws upon statistical techniques that control for the separate 

effects of variables that are themselves correlated. 

Jazz 

As indicated in Table 8, overall jazz participation via media is higher than 

live participation in both 1982 and 1992. Television viewing and listening to 

recordings show little change over the decade, while radio listening rose by 
 

Participation Patterns and Changes, 1982-1992 I 17 

TABLE 8.	 Jazz Participation Rates by Variable, 1982 and
 

1992 (Percentages of Adult Population)
 

Live Television Radio Recording 

Variable 1982 1992 1982 1992 1982 1992 1982 1992 

Total 9.6 10.6 18.0 17.9 18.1 28.2 20.2 20.6 

Location
 

Urban 11.0 12.2 20.3 19.9 20.8 31.5 23.5 23.5
 

Rural 6.5 6.3 12.6 12.7 11.8 19.4 12.1 12.7
 

Gender
 

Male 10.3
 11.9 19.6 19.4 20.5 30.9 21.3 22.6 

Female 9.0 9.4 16.7 16.5 16.0 25.7 19.2 18.7 

Education
 

Elementary 1.3 0.8 4.5 6.7 6.2 9.4 4.7 4.6
 

High school 6.1 4.9 15.2 12.8 15.1 19.6 16.0 12.5
 

College 17.0 18.4 25.9 25.3 25.6 40.5 30.5 31.8
 

Age
 

Young adult 17.0 12.4 21.0 14.8 27.4 30.1 29.5 23.2
 

30-something 9.7 12.9 19.0 20.1 17.9 34.5 20.4 25.5
 

Middle age 6.0 9.7 19.1 19.6 15.3 26.0 17.6 18.4
 

Retired 1.8 4.8 9.1 15.1 6.0 15.9 6.6 10.1
 

Race
 

White 8.9 10.0 16.7 16.7 15.8 26.0 18.2 18.8
 

Black 15.5 16.1 28.1 27.8 35.9 45.4 36.5 35.5
 Other 8.3 6.5 21.7 14.4 23.4 25.1 20.3 15.1
 

Incomea
 

Poverty 7.6 5.2 12.2 12.5 16.9 18.8 13.7 11.4
 

Low 8.8 8.1 17.9 17.2 18.0 24.3 20.4 16.6 

Moderate 11.8 12.4 21.6 19.5 19.0 31.9 24.2 23.9 High 16.7 22.1 26.0 27.9 19.6 44.4 30.2 37.5 

aGroupings not comparable between periods 

slightly more than 10 percentage points. Participation by all modes is higher in 

urban than in rural areas, again with little change over time except for radio. 

Jazz is the only benchmark art with greater male and black participation rates. 

Many jazz artists are black, and much of jazz is rooted in the African American 

cultural experience. 

As hypothesized, participation rises with education and income, but, somewhat surprisingly, falls with age. Jazz seems to be a young persons’ art form. 

Some patterns of change over time are noteworthy. Except for radio, media 

participation by the high school group decreased noticeably over time. Among 

the age groupings, participation rose over time except among young adults. 

Although this group’s radio listening rose, other forms of media participation 

by young adults declined, suggesting that the jazz audience is aging. 
 

18 I Turning On and Tuning In 

FIGURE 1. Jazz Participation Rates by Age, 

1982 and 1992 (Percent) 

 ̄ Young Adult [] 30-something [] Middle Age [] Retired

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

TABLE 9. ChangeinJazz Participation Rates by Age,
 

1982-1992
 

Age Group Live Television Radio Recordings 

Young adult -4.6 -6.2 2.7 -6.3 

30-something 3.2 1.1 16.6 5.1 

Middle age 3.7 0.5 10.7 0.8 

Retired 3.0 6.0 9.9 3.5 

Note: Numbers indicate increase or decrease in percentage points. 
 

 

Participation Patterns and Changes, 1982-1992 I 19 

FIGURE 2.	 Jazz Participation Rates by Education, 

1982 and 1992 (Percent) 

 ̄ Elementary [] High School  ̄ College

50 

40 

1982 1992 1982 1992 1982 1992 1982 1992 

Live Television Radio Recordings 

TABLE 10. Change in Jazz Participation Rates by Education, 

1982-1992 

Educationa Live Television Radio Recordings 

Elementary -0.5 2.2 3.2 -0.1 

High school -1.2 -2.4 4.5 -3.5 

College 1.4 -0.6 14.9 1.3 

Note: Numbers indicate increase or decrease in percentage points. 

a"None" not included 
 

 

20 I Turning On and Tuning In 

FIGURE 3. Jazz Participation Rates by Race, 

1982 and 1992 (Percent) 

[] Black [] White [] Other 

1982 1992 1982 1992 1982 1992 1982 1992 

Live Television Radio Recordings 

TABLE 11. Change in Jazz Participation Rates by Race, 

1982-1992 

Race Live Television Radio Recordings 

White 1.1 0.0 10.2 0.6 

Black 0.6 -0.3 9.5 -1.0 

Other -1.8 -7.3 1.7 -5.2 

Note: Numbers indicate increase or decrease in percentage points. 
 

Participation Patterns and Changes, 1982-1992 I 21 

Classical Music 

As indicated in Table 12, participation in classical music via media exceeds 

live participation. Live and television participation have fallen slightly over time, 

while radio increased substantially and recordings a modest amount. The rise 

in radio participation is true for all of the demographic groupings. Participation 

is higher among urban and female respondents, but male participation rates rose 

over the decade at least slightly in three of the four categories. As expected, 

participation rises with education, age (though most categories show a lower 

level of participation among the "retired" age group), and income. White 

participation is higher than black, while the "other" category shows a mixed 

pattern. 

TABLE 12. Classical Music Participation Rates by Variable,
 

1982 and 1992 (Percentages of Adult Population)
 

Live Television Radio Recordings 

Variable 1982 1992 1982 1992 1982 1992 1982 1992 

Total 13.0 12.5 24.7 21.9 19.9 30.8 22.1 23.8 

Location
 

Urban 14.7 13.8 26.5 23.6 21.5 33.0 23.1 25.7
 

Rural 9.3 9.1 20.4 17.3 16.2 24.8 19.8 18.9
 

Gender
 

Male 11.3 11.5 23.3 20.3 20.5 30.7 21.2 23.1
 

Female
 14.6 13.4 25.9 23.3 19.4 30.9 22.9 24.5 

Education
 

Elementary 1.7 1.9 10.1 9.8 8.3 11.8 6.2 5.8
 High school 6.6 5.8 19.6 15.8 13.0 19.6 14.5 13.2
 College 25.2 21.4 36.1 30.5 32.6 46.0 37.1 38.0
 

Age 

Young adult 11.5 9.9 17.2 14.0 16.5 24.3 19.8 22.0 

30-something 15.3 11.8 25.3 19.7 23.4 32.9 25.6 25.6 

Middle age 13.8 16.1 33.2 27.1 22.7 36.5 25.7 26.5 

Retired 10.2 11.8 23.3 29.2 15.5 26.6 14.2 18.5 

Race
 

White 13.9 13.2 25.6 22.5 20,2 32.1 22.9 25.2
 

Black 6.7 6.9 15.9 16.1 15.4 19.6 13.2 12.6
 

Other 9.4 12.8 30.9 25.3 29.2 36.4 31.4 25.9 

Incomea
 

Poverty 8.2 5.8 15.1 15.2 13.4 19.8 12.8 12.7
 

Low 10.5 9.3 25.1 19.5 18.0 24.7 21.4 17.7 

Moderate 18.3 14.4 29.8 23.2 25.3 34.9 27.7 27.8 High 30.1 28.6 47.6 38.1 40.0 53.4 38.9 45.2 

aGroupings not comparable between periods 
 

 

22 [ Turning On and Tuning In 

FIGURE 4. Classical Music Participation Rates by Age, 

1982 and 1992 (Percent) 

 ̄ Young Adult [] 30-something [] Middle Age [] Retired

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

TABLE 13.	 Change in Classical Music Participation Rates by
 

Age, 1982-1992
 

Age Group Live Television Radio Recordings 

Young adult -1.6 -3.2 7.8 2.2 

30-something -3.5 -5.6 9.5 0.0 

Middle age 2.3 -6.1 13.8 0.8 

Retired 1.6 5.9 11.1 4.3 

Note: Numbers indicate increase or decrease in percentage points. 
 

 

301 

Participation Patterns and Changes, 1982-1992 I 23
 

FIGURE 5. Classical Music Participation Rates by Education, 

1982 and 1992 (Percent) 

[] Elementary [] High School [] College 

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

TABLE 14. Change in Classical Music Participation Rates by
 

Education, 1982-1992
 

Educationa Live Television Radio Recordings 

Elementary 0.2 -0.3 3.5 -0.4 

High school -0.8 -3.8 6.6 -1.3 

College -3.8 -5.6 13.4 0.9 

Note: Numbers indicate increase or decrease in percentage points. 

a"None" not included 
 

 

24 I Turning On and Tuning In 

FIGURE 6. Classical Music Participation Rates by Race, 

1982 and 1992 (Percent) 

Black [] White [] Other  ̄ 

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

Table 15.	 Change in Classical Music Participation Rates by
 

Race, 1982-1992
 

Race	 Live Television Radio Recordings 

White -0.7 -3.1 11.9 2.3 

Black 0.2 0.2 4.2 -0.6 

Other 3.4 -5.6 7.2 -5.5 

Note: Numbers indicate increase or decrease in percentage points. 
Participation Patterns and Changes, 1982-1992 I 25 

For the most part, live and television participation fell over the decade, even 

for the college-educated group, suggesting that education is not so strong a 

determinant of tastes as it once might have been. These categories of participation also declined for the younger age groups, an indicator that the classical 

music audience is aging and not replenishing itself. 

The dramatic increase in radio participation deserves further mention. The 

wide reach of radio stations devoted exclusively to classical music and the growth 

of both National Public Radio and Public Radio International mean that anyone 

with a radio has access to classical music virtually any time of day. This is not 

true of television. As discussed in Part I, few broadcast or cable networks other 

than public television offer classical music, and public television devotes only 

some 17 percent of its programming to cultural events. Interestingly, this 

popularity of radio participation has not carried over to recordings. Perhaps the 

sound quality available on compact discs is offset by the relatively high price of 

CD players, including automobile stereo systems. 

Opera 

In 1992 opera ranked lowest among the benchmark arts for live and 

television participation, and it was a distant third in both radio and recordings. 

As shown in Table 16, participation rates were higher in both 1982 and 1992 

for urban than for rural respondents and for female than for male respondents. 

Interestingly, television participation exceeded participation rates for live performances and the other media. This may reflect the visual nature of opera. 

Viewers can easily consult television listings to learn when a performance is 

scheduled, which is not so true of radio. 

Participation increases with education, age (except for the "retired" group), 

and income. Except for radio, participation by the high school and collegeeducated groups has not increased over the decade. 

Live and radio participation in general rose over the decade. It is interesting 

to note that black participation rose for live performances and all media except 

recordings. Indeed, black participation even rose for television, which declined 

for nearly every other demographic grouping. 
 

 

26 I Turning On and Tuning In 

TABLE 16. Opera Participation Rates by Variable, 1982 and 

1992 (Percentages of Adult Population) 

Live Television Radio Recordings 

Variable 1982 1992 1982 1992 1982 1992 1982 1992 

Total 3.0 3.3 12.0 10.7 7.1 8.7 7.5 6.9 

Location 

Urban 3.7 3.7 13.4 12.0 7.9 9.4 8.3 7.8 

Rural 1.5 2.1 8.7 7.4 5.2 6.6 5.4 4.7 

Gender 

Male 2.7 3.1 10.5 10.0 7.2 8.4 7.1 6.6 

Female 3.3 3.5 13.4 11.4 7.0 8.9 7.7 7.3 

Education 

Elementary 0.5 0.6 4.3 4.9 3.8 3.6 2.8 2.1 

High school 1.6 1.3 9.7 7.0 4.1 4.9 5.4 3.4 

College 5.8 5.8 17.6 15.7 11.9 13.6 11.7 11.4 

Age 

Young adult 2.3 2.5 6.2 5.7 4.9 4.0 3.4 4.3 

30-something 3.2 3.3 11.7 9.2 5.9 7.4 7.7 6.3 

Middle age 3.7 4.1 17.9 14.7 10.3 12.7 11.7 9.9 

Retired 2.9 3.1 13.5 14.8 7.7 11.5 7.2 7.2 

Race 

White 3.2 3.4 12.1 10.7 7.2 9.0 7.9 7.3 

Black 1.3 1.8 9.3 10.4 5.3 6.0 3.9 3.7 

Other 3.0 5.3 20.1 12.3 12.0 8.3 8.3 9.4 

Incomea 

Poverty 1.7 1.8 7.5 7.7 5.1 5.4 3.8 3.1 

Low 2.0 1.7 11.6 9.0 6.1 6.3 7.1 4.5 

Moderate 4.1 3.3 15.3 11.4 8.1 9.6 9.2 7.9 

High 10.0 12.2 24.4 18.0 15.5 17.9 13.5 16.0 

aGroupings not comparable between periods 
 

 

Participation Patterns and Changes, 1982-1992 I 27
 

FIGURE 7. Opera Participation Rates by Age, 

1982 and 1992 (Percent) 

 ̄ Young Adult [] 30-something  ̄ Middle Age [] Retired

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

TABLE 1 7. Change in Opera Participation Rates by Age,
 

1982-1992
 

Age Group Live Television Radio Recordings 

Young adult 0.2 -0.5 -0.9 0.9 

30-something 0.1 -2.5 1.5 -1.4 

Middle age 0.4 -3.2 2.4 -1.8 

Retired 0.2 1.3 3.8 0.0 

Note: Numbers indicate increase or decrease in percentage points. 
 

 

28 I Turning On and Tuning In 

FIGURE 8. Opera Participation Rates by Education, 

1982 and 1992 (Percent) 

[] Elementary [] High School [] College 

20 

0 

1982 1992 1982 1992 1982 1992 1982 1992 

Live Television Radio Recordings 

TABLE 18.	 Change in Opera Participation Rates by 

Education, 1982-1992 

Educationa Live Television Radio Recordings 

Elementary 0.1 0.6 -0.2 -0.7 

High school -0.3 -2.7 0.8 -2.0 

College 0.0 -1.9 1.7 -0.3 

Note: Numbers indicate increase or decrease in percentage points. 

a"None" not included 
 

 

Participation Patterns and Changes, 1982-1992 I 29
 

FIGURE 9. Opera Participation Rates by Race, 

1982 and 1992 (Percent) 

 ̄ Black [] White  ̄ Other 

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

TABLE 19. Change in Opera Participation Rates by Race,
 

1982-1992
 

Race Live Television Radio Recordings 

White 0.2 -1.4 1.8 -0.6 

Black 0.5 1.1 0.7 -0.2 

Other 2.3 -7.8 -3.7 1.1 

Note: Numbers indicate increase or decrease in percentage points. 
 

 

30 I Turning On and Tuning In 

Musicals 

Table 20 indicates that, with few exceptions, live and media participation 

rates fell from 1982 to 1992. Live and television participation far exceed 

participation via both radio and recordings, due undoubtedly to the visual 

nature of musicals. Urban participation exceeds rural, and female participation 

generally exceeds male. Participation rises with education, age (except for the 

"retired" group), and income. 

The rather dramatic fall in television participation probably reflects a 

supply-side phenomenon, which exacerbated the overall decline. Participation 

in musicals via media declined for all age groups except the retired, for high 

school and college groups, and generally for all racial groups. 

TABLE 20. Musical Participation Rates by Variable, 1982 and
 

1992 (Percentages of Adult Population)
 

Live Television Radio Recordings 

Variable 1982 1992 1982 1992 1982 1992 1982 1992 

Total 18.6 17.4 20.4 12.5 4.3 3.5 8.4 5.7 

Location
 

Urban 21.2 19.2 22.9 13.6 5.1 3.8 9.9 6.5
 

Rural 13.1 12.8 14.3 9.7 2.6 2.6 4.7 3.5
 

Gender 

Male 16.6 15.1 18.8 11.4 4.6 3.4 7.2 5.3 

Female 20.5 19.6 21.7 13.6 4.1 3.6 9.3 6.0 

Education
 

Elementary 4.1 3.1 9.0 6.7 1.1 2.4 1.9 2.1
 

High school 11.5 10.4 15.7 9.4 2.8 1.9 4.4 2.4
 

College 32.9 27.5 30.3 17.0 7.3 5.4 15.6 9.8
 

Age


Young adult 17.6 15.3 18.1 7.4 3.6 2.0 7.0 4.8
 

30-something 22.1 18.0 20.7 11.4 4.2 3.1 9.4 5.9
 

Middle age 20.0 21.0 23.2 15.6 5.9 4.6 11.5 7.2
 

Retired 12.0 13.6 19.1 17.2 3.5 4.7 3.8 4.1
 

Race
 

White 19.8
 18.1 20.7 12.7 4.2 3.6 9.1 6.0 

Black 10.0 14.1 17.4 11.3 4.4 2.5 1.9 2.9 

Other 13.1 11.7 19.8 12.9 8.1 5.1 10.2 7.3 

Incomea
 

Poverty 9.2 7.6 12.9 9.1 2.7 2.7 4.2 3.0
 

Low 15.6 12.6 19.8 11.9 3.7 2.9 6.7 3.8
 

Moderate 28.0 20.2 26.3 13.2 4.5 3.6 12.6 6.3
 

High 43.4 42.3 35.6 18.7 11.3 6.4 20.6 13.1
 

aGroupings not comparable between periods 
 

 

 

Participation Patterns and Changes, 1982-1992 I 31
 

FIGURE 10. Musical Participation Rates by Age, 

1982 and 1992 (Percent) 

 ̄ Young Adult [] 30-something  ̄ Middle Age [] Retired

1982 1992 1982 1992 1982 1992 1982 1992
 

Live Television Radio Recordings 

TABLE 21. Change in Musical Participation Rates by Age,
 

1982-1992
 

Age Group Live Television Radio Recordings 

Young adult -2.4 -10.7 -1.6 -2.2 

30-someth i ng -4.1 -9.3 -1.1 -3.5 

Middle age 1.0 -7.6 -1.3 -4.3 

Retired 1.6 -1.9 1.2 0.3 

Note: Numbers indicate increase or decrease in percentage points. 
 

 

32 I Turning On and Tuning In 

FIGURE 11. Musical Participation Rates by Education, 

1982 and 1992 (Percent) 

[] Elementary [] High School [] College 

35 

30£ 

25£ 

20£ 

15£ 

10£ 

5­

0 

1982 1992 1982 1992 1982 1992 1982 1992 

Live Television Radio Recordings 

TABLE 22.	 Change in Musical Participation Rates by 

Education, 1982-1992 

Educationa Live Television Radio Recordings 

Elementary 

High school 

-1.0 

-1.1 

-2.3 

-6.3 

1.3 

-0.9 

0.2 

-2.0 

Col lege -5.4 -1 3.3 -1.9 -5.8 

Note: Numbers indicate increase or decrease in percentage points. 

a"None" not included 
 

Participation Patterns and Changes, 1982-1992 I 33 

FIGURE 12. Musical Participation Rates by Race, 

1982 and 1992 (Percent) 

 ̄ Black [] White [] Other 

1982 1992 1982 1992 1982 1992 1982 1992 

Live Television Radio Recordings 

TABLE 23. Change in Musical Participation Rates by Race, 

1982-1992 

Race Live Television Radio Recordings 

White -1.7 -8.0 -0.6 -3.1 

Black 4.1 -6.1 -1.9 1.0 

Other -1.4 -6.9 -3.0 -2.9 

Note: Numbers indicate increase or decrease in percentage points. 
34 I Turning On and Tuning In 

Theater (Plays) 

Perhaps the most dramatic pair of numbers in Table 24 is the one that shows 

the total decline in the viewing of plays on television, from a rate of 25.9 percent 

in 1982 to 14.8 percent in 1992. The decline is consistent over all demographic 

groups and to some extent reflects the reduced availability of theater per se on 

television and the stiff competition from other dramatic offerings on cable 

television. 

Participation rises with education, age (except for the "retired" group), and 

income. Although participation by whites is generally higher than participation 

TABLE 24. Theater (Plays) Participation Rates by Variable,
 

1982 and 1992 (Percentages of Adult Population)
 

Live Television Radio 

Variable 1982 1992 1982 1992 1982 1992 

Total 11.9 13.5 25.9 14.8 3.8 2.8 

Location 

Urban 13.5 15.3 28.4 16.4 4.3 3.1 

Rural 8.5 8.5 20.0 10.6 2.6 2.0 

Gender
 

Male 10.8 12.3 25.2 14.0 3.7 3.1
 

Female 12.9 14.6 26.6 15.6 3.9 2.6
 

Education 

Elementary 1.7 1.8 7.2 6.4 0.7 1.5 

High school 6.1 7.0 20.1 11.0 2.9 1.8 

College 23.0 22.4 39.5 20.4 6.0 4.2 

Age
 

Young adult 11.1 12.5 25.3 8.7 5.3 2.0
 

30-something 14.3 13.5 27.2 13.6 3.3 3.4
 

Middle age 12.5 16.2 28.4 19.5 3.6 3.0
 

Retired 8.2 10.6 20.3 18.6 2.4 2.5
 

Race 

White 12.8 13.7 27.0 15.2 4.0 2.6 

Black 5.8 12.2 18.2 12.7 2.7 4.1 

Other 7.9 10.5 21.3 12.1 2.2 3.7 

Incomea 

Poverty 6.1 6.8 16.0 10.0 3.8 2.4 

Low 9.5 9.9 25.0 12.2 3.8 2.3 

Moderate 17.8 15.2 33.5 16.8 4.6 3.1 

High 33.1 31.8 34.0 24.7 2.1 4.2 

aGroupings not comparable between periods 
Participation Patterns and Changes, 1982-1992 I 35
 

FIGURE 13. Theater (Plays) Participation Rates by Age, 

1982 and 1992 (Percent) 

[[] Young Adult [] 30-something [] Middle Age [] Retired 

1982 1992 1982 1992 1982 1992
 

Live Television Radio 

TABLE 25. Change in Theater (Plays) Participation Rates by
 

Age, 1982-1992
 

Age Group Live Television Radio 

Young adult 1.4 -16.6 -3.3 

30-something -0.8 -13.6 0.1 

Middle age 3.7 -8.9 -0.6 

Retired 2.4 -1.7 0.1 

Note: Numbers indicate increase or decrease in percentage points. 
36 I Turning On and Tuning In 

FIGURE 14. Theater (Plays) Participation Rates by Education, 

1982 and 1992 (Percent) 

 ̄ Elementary [] High School [] College

50 , 

40 I
 

30 I
 

1982 1992 1982 1992 1982 1992
 

Live Television Radio 

TABLE 26. Change in Theater (Plays) Participation Rates by
 

Education, 1982-1992
 

Educationa Live Television Radio 

Elementary 0.1 -0.8 0.8 

High school 0.9 -9.1 -1.1 

College -0.6 -1 9.1 -1.8 

Note: Numbers indicate increase or decrease in percentage points. 

a"None" not included 
Participation Patterns and Changes, 1982-1992 [ 37 

FIGURE 15. Theater (Plays) Participation Rates by Race, 

1982 and 1992 (Percent) 

 ̄ Black [] White  ̄ Other 

|! 

1982 1992 1982 1992 1982 1992
 

Live Television Radio 

TABLE 27. Change in Theater (Plays) Participation Rates by
 

Race, 1982-1992
 

Race Live Television Radio 

White 0.9 -11.8 -1.4 

Black 6.4 -5.5 1.4 

Other 2.6 -9.2 1.5 

Note: Numbers indicate increase or decrease in percentage points. 
38 I Turning On and Tuning In 

by other groups, black attendance at live performances and participation via 

radio rose from 1982 to 1992. Furthermore, the decline in black participation 

via television was not so pronounced as declines in this category overall. It is 

tempting to attribute this to the growth of black theater, the development of 

black acting talent, and the success of such playwrights as August Wilson. 

Ballet/Dance 

The 1982 survey respondents were asked about participation in ballet, 

excluding such other dance forms as modern, jazz, Eastern, and so forth. This 

was partially rectified in the 1992 survey, when a question regarding live 

participation in dance, broadly defined, was added. Unfortunately, that means 

that while live ballet participation can be compared over time, media participation cannot be strictly compared over time, nor can media participation be 

strictly compared with live participation for 1992. Nevertheless, some generalizations may be possible. 

In both years, participation rises with education and income, as shown in 

Table 28. Live participation is slightly higher within the two younger age groups, 

while participation by television tends to peak in the middle-age group. 

Over the decade, overall ballet participation rose slightly, and participation 

within most individual groupings rose as well. Not surprisingly, participation 

in dance, more broadly defined, was higher than participation in just ballet in 

1992. The only anomaly was in the highest income grouping, where ballet 

participation exceeded dance participation. Interestingly, nonwhite live participation in dance exceeds white participation in 1992, suggesting that the broader 

category captures ethnic exposure that is obscured by a focus on ballet. Media 

participation rates in dance in 1992 are very similar across the racial groupings 

depicted. Dance Theater of Harlem and the Alvin Alley Company are among 

the best-known examples of primarily black performing groups, and other black 

choreographers, such as Bill T. Jones, have become very popular. One would 

presume that these companies and artists have found an audience. 
 

Participation Patterns and Changes, 1982-1992 I 39 

TABLE 28. Ballet/Dance Participation Rates by Variable, 

1982 and 1992 (Percentages of Adult Population) 

Live Televisiona 

Variable 1982 Ballet 1992 Ballet 1992 Dance 1982 1992 

Total 4.2 4.6 7.1 16.3 17.2 

Location 

Urban 4.9 5.4 7.6 17.7 18.5 

Rural 2.6 2.6 5.9 13.1 13.7 

Gender 

Male 2.7 3.6 6.7 12.1 14.8 

Female 5.6 5.6 7.5 20.1 19.4 

Education 

Elementary 0.4 0.7 2.5 7.6 11.0 

High school 2.0 2.0 4.3 11.6 13.1 

College 8.4 8.1 10.9 25.4 22.8 

Age 

Young adult 4.1 4.9 7.3 12.7 12.6 

30-something 5.7 5.0 7.8 17.3 16.5 

Middle age 3.7 4.9 7.2 19.8 20.3 

Retired 2.5 3.2 5.4 15.4 20.3 

Race 

White 4.5 4.9 7.0 16.8 17.2 

Black 1.8 2.6 7.3 10.3 16.5 

Other 3.4 5.8 9.9 26.3 18.8 

Incomeb 

Poverty 2.2 2.6 4.6 10.8 14.2 

Low 3.5 2.5 6.3 15.3 1 7.0 

Moderate 5.9 5.5 8.2 21.4 17.3 

High 10.7 12.3 9.5 28.8 25.0 

aData are not strictly comparable over time. 

bGroupings are not comparable between periods. 
40 I Turning On and Tuning In 

FIGURE 16. Ballet/Dance Participation Rates by Age, 

1982 and 1992 (Percent) 

[, Young Adult [] 30-something [] Middle Age [] Retired 

151 

101 

1982 Ballet 1992 Ballet 1992 Dance 1982 1992 

Live Television 

TABLE 29. Change in Ballet/Dance Participation Rates by 

Age, 1982-1992a 

Live Televisiona 

Age Group Ballet Only Ballet/Dancea (Ballet/Dance) 

Young adult 0.8 3.2 -0.1 

30-something -0.7 2.1 -0.8 

Middle age 1.2 3.5 0.5 

Retired 0.7 2.9 4.9 

Note: Numbers indicate increase or decrease in percentage points.

aData are not strictly comparable over time. 
Participation Patterns and Changes, 1982-1992 I 41 

FIGURE 17. Ballet/Dance Participation Rates by Education, 

1982 and 1992 (Percent) 

 ̄ Elementary [] High School College  ̄ 

30 

1982 Ballet 1992 Ballet 1992 Dance 1982 1992 

Live Televisi~ 

Table 30. Change in Ballet/Dance Participation Rates by 

Education, 1982-1992a 

Live Televisiona 

Educationb Ballet Dancea (Dance Only) 

Elementary 0.3 2.1 3.4 

High school 0.0 2.3 1.5 

College -0.3 2.5 -2.6 

Note: Numbers indicate increase or decrease in percentage points.
 

aData are not strictly comparable over time.
 

b"None" is not included.
 
 

42 I Turning On and Tuning In 

FIGURE 18. Ballet/Dance Participation Rates by Race, 

1982 and 1992 (Percent) 

 ̄ Black [] White [] Other

1982 Ballet 1992 Ballet 1992 Dance 1982 1992 

Live Televisio~ 

TABLE 31. Change in Ballet/Dance Participation Rates by 

Race, 1982-1992 

Live Televisiona 

Race Ballet Only Ballet/Dancea (Ballet/Dance) 

White 0.4 2.5 0.4 

Black 0.8 5.5 6.2 

Other 2.4 6.5 -7.5 

Note: Numbers indicate increase or decrease in percentage points. 

aData are not strictly comparable over time. 
Participation Patterns and Changes, 1982-1992 I 43 

Art 

In contrast to the preceding performing arts data and discussion, both 

attendance at art museums and participation via television (watching programs 

about art, artists, or art museums and galleries) have risen over time for virtually 

every demographic category (see Table 32). Participation rates are high and 

getting higher. Even male and female participation rates are nearly on a par. 

TABLE 32. Art Participation Rates by Variable, 1982 and 

1992 (Percentages of Adult Population) 

Live Television 

Variable 1982 1992 1982 1992 

Total 22.1 26.7 22.8 30.1 

Location 

Urban 

Rural 

24.6 

16.8 

29.8 

18.5 

24.7 

18.4 

31.2 

27.3 

Gender 

Male 

Female 

21.0 

23.1 

26.4 

26.9 

23.1 

22.6 

30.1 

30.1 

Education 

Elementary 

High school 

College 

2.5 

13.5 

40.0 

3.8 

14.4 

43.6 

4.6 

18.5 

34.0 

13.3 

23.3 

40.2 

Age 

Young adult 

30-something 

Middle age 

Retired 

24.3 

26.9 

20.4 

12.3 

29.1 

29.6 

27.3 

16.3 

22.0 

24.5 

25.7 

16.5 

26.8 

31.7 

34.0 

25.1 

Race 

White 

Black 

Other 

23.2 

12.3 

27.5 

27.6 

19.0 

28.4 

23.2 

19.4 

24.6 

31.3 

23.3 

21.5 

Incomea 

Poverty 

Low 

Moderate 

High 

12.8 

19.6 

30.7 

47.2 

13.4 

20.6 

31.6 

49.8 

14.4 

20.9 

32.8 

42.9 

21.8 

27.4 

33.0 

44.1 

aGroupings not comparable between periods 
44 I Turning On and Tuning In 

FIGURE 19. Art Participation Rates by Age, 

1982 and 1992 (Percent) 

I[] Young Adult [] 30-something [] Middle Age [] Retired 

40 , 

35 I 

1982 1992 1982 1992 

Live Television 

TABLE 33. Change in Art Participation Rates by Age, 

1982-1992 

Age Group Live Television 

Young adult 4.8 4.8 

30-something 2.7 7.2 

Middle age 6.9 8.3 

Retired 4.0 8.6 

Note: Numbers indicate increase in percentage points. 
Participation Patterns and Changes, 1982-1992 I 45 

FIGURE 20. Art Participation Rates by Education, 

1982 and 1992 (Percent) 

Elementary [] High School College  ̄  ̄ 

50 ~ 

4O 

3O 

2O 

lc 

1982 1992 1982 1992 

Live Television 

TABLE 34. Change in Art Participation Rates by Education, 

1982-1992 

Educationa Live Television 

Elementary 1.3 8.7 

High school 0.9 4.8 

College 3.6 6.2 

Note: Numbers indicate increase in percentage points. 

a"None" is not included. 
46 I Turning On and Tuning In  ̄

FIGURE 21. Art Participation Rates by Race,
 

1982 and 1992 (Percent)
 

[] Black [] White [] Other 

35 

30 

25 

1982 1992 1982 1992 

Live Television 

TABLE 35. Change in Art Participation Rates by Race, 

1982-1992 

Race Live Television 

White 4.4 8.1 

Black 6.7 3.9 

Other 0.9 -3.1 

Note: Numbers indicate increase or decrease in percentage points. 
Participation Patterns and Changes, 1982-1992 I 47 

Participation rates rise with education and income, while participation by 

age peaks in the 30-something to middle-age range. 

Summary and Conclusions 

The findings in this chapter lend credence to a number of conclusions. 

Participation in all art forms and media tend to rise with income, education, 

and age. Media participation rates, although subject to the same general 

influences, are by and large higher than live attendance rates, probably reflecting 

the lower costs of participating from, say, one’s living room. Except for jazz, 

female and white participation rates exceed the alternatives, while urban participation uniformly exceeds rural. 

The measures of association, which suggest that observed relationships are 

not simply random, leave some questions unanswered. It is not clear, for 

example, whether the high association between education and participation is 

due to well-developed tastes for art and culture, or due to the higher incomes-­

and ability to pay--of those with higher educations. Part III resolves this 

difficulty. 
Multivariate 

Statistical Results 

Among the questions posed--and answered--in this part are the following: 

 ̄ What is the impact of any one variable on arts participation via media, 

controlling for all other influences? As indicated in the last chapter, failure 

to control for possible simultaneous influences could lead to erroneous 

inferences. 

 ̄ 

 ̄ 

Do multivariate methods further indicate that patterns of participation via 

media differ significantly from those for live participation? 

Have multivariate results altered significantly from 1982 to 19927 

Multivariate statistical techniques are most appropriate to address questions 

such as these. Such techniques generate estimates of the parameters, or relationships, among a number of variables simultaneously.13 The specific technique 

used here is logistic regression, which deals with categorical response variables.14 

An example of a categorical response variable is gender, where a respondent can 

be either male or female, i.e., fall into one category or the other. This contrasts 

with more nearly continuous variables, such as household income, which can 

range in value from zero to millions of dollars or higher. But even these latter 

can be grouped into categories for statistical purposes, as has been done in this 

document. Statistical results, literal interpretations, and inferences are indicated 

in the sections that follow. For a more technical discussion of the techniques, 

including indicators of statistical significance, see Appendix B. 

The estimating equation for multiple regression takes the general form 

where Pi is the live (media) participation measure for activity i (opera, for 

example); Pj is the participation measure for a corresponding media (live) 

activity fi G is a geographic identifier (e.g., urban); and D is a vector of 

demographic characteristics, including those of particular interest for this 

project (income, education, etc.). A positive sign for the estimated coefficient 

of Pj indicates complementarity, while a negative sign would indicate the two 

are substitutes.15 

Separate regressions for each of the survey periods will support further 
Multivariate Statistical Results 149 

analyses of changes over time.16 A review of general patterns will offer some 

indications as to whether participation patterns have altered over time. 

Logistic Models 

Logistic regression estimates the probability of an event occurring, for 

example, of an individual attending a live performance or participating via some 

media form. The logistic model can be written in terms of the "log of the odds," 

which is called a logit." 

Prob(evenO log ( Prob(no event).) = Bo + B1X1 +... + B~n 

An equivalent expression is 

1 Prob (event) = 1 + e-(B° + BIX1 ...) 

which we can use to construct an illustrative example. Borrowing some values 

from the third column of Table 37, we seek to determine the probability that 

a 30-something black male with moderate income and a high school education 

would view jazz on television in the survey period. The calculation is 

Prob (jazzon TV) - 1 - .3253
 

1 + e-(-3"5851 + .4623(1) + .1407(1) + .3419(1) + 1.1449(1) - .1172(1) + .8830(1))
 

which means that there is about a one-third, or one out of three, chance that 

the person described above would have watched jazz on television during the 

survey period. In contrast, the corresponding probability for an otherwise 

similar white respondent is slightly less than 25 percent. 

A positive value of Bi increases the log of the odds, while a negative value 

decreases the log of the odds. Put less precisely but more simply, a positive 

coefficient indicates that the variable increases the probability of participation, 

while a negative coefficient decreases the probability. Furthermore, as the 

absolute value of a coefficient increases, the impact of that variable likewise 

increases. For example, a higher value of the coefficient of one age group 

indicator relative to another indicates that someone in the first age group is more 

likely to participate. 
50 I Turning On and Tuning In 

Overall Logistic Regression Results 

Table 36 lists and briefly defines the variables included in the logistic 

regressions--those variables that may influence consumer tastes or consumer 

willingness to pay with respect to each of the benchmark arts. Such variables 

include demographic descriptors of respondents as well as characteristics of their 

locations. Gender, race, and education levels are among the variables that may 

be taken to indicate tastes, while income reflects both tastes and the ability to  ̄  ̄  ̄ 17 .... pay forarts paruclpauon. The third column in Table 36, Reference, simply 

TABLE 36. Variables, Definitions, and References 

Variable 

Urban 

Male 

Low income 

Moderate 

income 

High income 

High school 

College 

30-something 

Middle age 

Retired 

Black 

Asian 

Indian 

Hispanic 

Live 

Television 

Radio 

Recording 

Brief Description 

Resides in urban area 

Self-explanatory 

Household income range just 

above poverty 

Household income range below 

the highest 

Household income over $75,000 

(1982) or $100,000 (1992) 

Between 9 and 12 years of 

education 

More than 12 years of education 

Age between 30 and 44 

Age between 45 and 64 

Age 65 or greater 

Self-explanatory 

All Asian 

American Indian, Eskimo, or Aleut 

Of Hispanic origin 

Participant via live performance 

of art form in question 

Participant via television in art 

form in question 

Participant via radio in art form 

in question 

Participant via audio recording 

in art form in question 

Reference 

Not urban 

Female 

Poverty income 

Poverty income 

Poverty income 

Elementary 

Elementary 

Young adult (18-29) 

Young adult 

Young adult 

White 

White 

White 

Not Hispanic 

Not live 

Not television 

participant 

Not radio 

participant 

Not recording

participant 
Multivariate Statistical Results I 51 

identifies the variable category against which the categories in the first column 

are compared to determine the coefficients. 

One might assume, further informed by the results reported in Part II, the 

following: urban respondents would be more likely to take advantage of live 

participation simply because of the greater likelihood of availability; those with 

higher education levels may have developed tastes more consistent with complex 

preferences; older respondents would have more time to develop complex tastes 

(or to move from less complex to more complex music). The expected impact 

of race would for the most part be less clear, although African Americans may 

display a disproportionate interest in jazz, traditionally a black art form. 

Ordinarily, individuals with higher income levels would participate more 

because of ability to pay; certainly this might be especially true in the case of 

live performances or purchase of recordings, both of which entail an explicit 

price or user charge. But both television (broadcast as well as many cable) and 

radio are known as "collective goods," wherein after some initial outlay (purchase of a receiving set, installation of cable access), subsequent viewing entails 

no explicit user charge. In these instances, income may not be quite so important 

a determinant. With those not too unreasonable expectations, we move to the 

statistical results. 

Significance of individual coefficients is based on the Wald statistic, which 

permits a test of whether a coefficient is 0, i.e., has no influence. 18 If the test is 

significant at, say, the 5 percent level, this means that there is only a 5 percent 

chance of the observed outcome occurring randomly. Put another way, there is 

a 95 percent chance of a nonrandom relationship between the variables. 

Several tests or indicators of overall significance of models as specified are 

reported in the following tables.19 These include the likelihood test (-2 log 

likelihood), which tests how well the model classifies the data in comparison to 

a "perfect" model. A model that classifies especially well would be described as 

not significantly different from the perfect model. As it happens, all of the results 

reported here do differ significantly from the perfect model. This means that 

many factors other than those accounted for in this study influence arts 

participation. 

A second test, the model chi-square, indicates whether the included variables 

as a group are significantly different from zero. Without exception, this test 

indicates that the included variables are significant. Finally, the third indicator, 

classification percentage, reveals the overall classification accuracy of the models. 

A value of 83.6, for example, means that 83.6 percent of the respondents are 

correctly classified as participants or nonparticipants by the model. The values 

for this indicator for most of the models reported here are generally in the 80s 

and 90s. 
52 I Turning On and Tuning In 

Jazz 

Tables 37 and 38 contain the results of logistic regressions for live and media 

participation in jazz for 1982 and 1992, respectively. As indicated by the 

summary statistics, the overall influence of the included variables is statistically 

significant. 

TABLE 37. Logistic Regression, Jazz Participation, 1982 

Independent 

Variable Live Television Radio Recording 

Urban .4576*** .4623** .4563*** .6214"** 

Male .0224 .1407 .2854*** .0289 

Low income - .0894 .2511 * - .1413 .3373*** 

Moderate income .0908 .3419"* - .1559 .4715*** 

High income 

High school 

College 

30-something 

Middle age 

Retired 

Black 

.4871 *** 

1.0946***’a 

2.1159***’a 

- .6907***’a 

-1.0330***’a 

-1.8895***’a 

.7179*** 

.4562** 

1.1449*** 

1.7933***’a 

- .1172 

.0518a 

- .4462*** 

.8830*** 

- .1129 

.8926*** 

1.5900*** 

- .4750***’a 

- .5473***’a 

-1.3526***’a 

1.2195*** 

.7456*** 

1.1475"** 

1.9566*** 

- .4961 ***,a 

- .4811 *** 

-1.2431 ***,a 

1.2675***’a 

Indian - .15301 *** .2177 .2814 - .2216 

Constant -3.6688*** -3.5851 *** -2.8000*** -3.4061 *** 

-2 Log likelihood 

Model chi-square 

Classification 

8706.671 b 

1134.959*** 

3158.659b 

215.488*** 

3041.379b 

323.466*** 

3173.020b 

405.486*** 

percentage 90.51 82.74 83.03 80.88 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

~Significantly different from 1992 coefficient at 5 percent level Significantly different from the "perfect" model 

Live Participation 

Several factors stand out in the equations for live attendance. The first is 

that an urban location enhances the likelihood of attendance, in part surely due 

to convenience. Urban areas are simply more likely to offer opportunities for 

live attendance. Men are more likely to participate than women, and this 

tendency became more pronounced in 1992. Income, as measured here, seems 

to be a significant factor; each of the included groups participate significantly 

more than the reference (poverty level) group. This is especially true in 1992, 
Multivariate Statistical Results I 53 

TABLE 38. Logistic Regression, Jazz Participation, 1992 

Independent 

Variable Live Television Radio Recording 

Urban .4569*** .3552*** .4165*** .4611 *** 

Male .1278** .1478*** .1748*** .1490*** 

Low income 

Moderate income 

High income 

High school 

College 

30-something 

Middle age 

Retired 

Black 

.3718*** 

.4791 *** 

.8732*** 

1.5803***’a 

2.8647***’a 

- .1529*’a 

- .4083***’a 

- .8181 ***,a 

.6677*** 

.2782*** 

.2298***’b 

.4892***’b 

.7304*** 

1.5432***’a’b 

.3343***’b 

.4290***’a’b 

.4231 ***,a,b 

.8035*** 

.2346*** 

.3615*** 

.7131 *** 

.6453***’b 

1.5518***’b 

.1379**’a’b 

- .1507**’a’b 

- .4484***’a’b 

.9604***’b 

.3445*** 

.5386*** 

1.0112*** 

.8146"** 

1.8546***’b 

- .0302a’b 

- .3084*** 

- .661 7***’a 

.9787***’a’b 

Asian - .8751"** - .2665b - .1982b - .4839*** 

Indian 

Hispanic 

- .0628 

- .4710"** 

.0694 

.0306b - .1917 .1042b .1783 - .1335b 

Constant -5.0870*** -3.5984*** -2.7788*** -3.5469*** 

-2 Log likelihood 

Model chi-square 

Classification 

6784.577c 

844.977*** 

10211.246c 

601.602*** 

12351.924c 

1199.478*** 

10095.600c 

1233.858"** 

percentage 89.72 82.13 73.02 80.37 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from 1992 coefficient at 5 percent level 

bSignificantly different from corresponding "live" coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

but this may be an artifact of the income groups chosen for the various 

categories. The likelihood of attendance increases with education; both the high 

school and college groups are more likely to attend than those in the reference 

(elementary) group, with the college coefficient larger than the high school 

coefficient. The education coefficients rose significantly from 1982 to 1992, 

suggesting education’s increased importance as a factor in attendance at jazz 

concerts. 

Attendance at jazz performances also seems to be a young person’s entertainment. Attendance is less likely among those in older age groups, with the 

negative coefficient progressively rising from the 30-somethings to the retirees. 

Interestingly, age declined in importance, as indicated by size of coefficient, 

from 1982 to 1992. Race indicators are mixed; black respondents participate 

significantly more than whites; Asians participate significantly less; and Hispanics participate less than non-Hispanics, the majority of whom are white. 
54 I Turnin8 On and Tunin8 In 

Television 

Participation in jazz via television is also higher in urban areas than in rural 

areas; gender, not significant in 1982, is significant a decade later; and higher 

incomes increase participation. In 1992, the income coefficients for television 

participation are much lower than for live participation, indicating that higher 

incomes are more likely to influence attendance at a performance than they are 

to influence television viewing of jazz. Another rather stark contrast is the 

positive and significant impact of higher age on television participation in 1992. 

One might suppose on this basis that the taste for jazz rises with age, but that 

this is in part offset by the reduced willingness to travel to live venues. The results 

also support the prior finding that modes of participation are complements as 

opposed to substitutes. Black respondents are more likely to participate via 

television than are whites, but other racial categories are insignificant. 

Radio 

Participation via radio reflects some similar influences: urban residents are 

more likely to listen to jazz than are nonurban residents; males are more likely 

to listen than are females. The role of income on participation via radio is 

insignificant in 1982, but participation clearly rises with income level in 1992. 

Education contributes strongly to participation in both time periods. The age 

measures show a mixed pattern; participation declines with age in 1982 but does 

so only for the two older groups in 1992. The 30-somethings are slightly more 

likely to participate than the young adults in the latter period. 

Recordings 

Although jazz recordings are ubiquitously available--that is, not limited to 

urban areas--urban respondents are more likely than nonurban respondents to 

participate via this means. High-income groups are more likely to participate 

by this means as well, reflecting the fact that recordings are not a collective good. 

Participation also generally rises with education but decreases with age, similar 

to the trends for live participation. Black respondents are more likely than whites 

to participate via recordings, while other race variables show a mixed response. 

Jazz Summary 

The results for jazz participation are generally consistent with earlier findings. Participation is higher for younger, black, urban males with higher incomes 

and education than for other groups. Income is not so important for the 

collective goods (television and radio) as for the more nearly private goods 

(recordings). 
Multivariate Statistical Results I 55 

Classical Music 

Tables 39 and 40 show the logistic regression results for classical music 

participation. As indicated by the summary statistics, the set of included 

variables is significant in both time periods. 

Live Participation 

Attendance at live classical music performances is higher in urban areas and 

among females. It rises with income, education, and age, and is generally lower 

for nonwhites. The urban and male coefficients have declined in absolute value 

over time, as have the education measures. The age coefficients have risen 

in absolute value, however, indicating an aging of the audience for live 

performances. 

TABLE 39. Logistic Regression, Classical Music Participation, 

1982 

Independent 

Variable Live Television Radio Recording 

Urban 

Male 

.4643***’a 

- .5046***’a .3973*** - .2592*** 

.3619*** 

- .0952 

.1806* 

- .2559*** 

Low income - .0345 .4604*** .1037 .2267** 

Moderate income .2528*** .4584*** .2409* .2829** 

High income 

High school 

College 

30-something 

Middle age 

Retired 

.7160*** 

1.4159*** 

2.9238***’a 

.3045***’a 

.4371 *** 

.4976*** 

.8977*** 

.8842*** 

1.8330*** 

.3819*** 

1.1195*** 

.9576***’a 

.6429*** 

.4059** 

1.6040*** 

.4624*** 

.6633*** 

.4449*** 

.4345** 

.8024*** 

2.1356*** 

.3201 ***,a 

.6046***’a 

.1168 

Black - .5752*** - .3212"* - .1419’a - .4815’** 

Indian 

Constant 

- .7764*** 

-4.4824*** 

.2825 

-3.4511 *** 

.2186 

-3.1031 *** 

.1494 

-3.1406*** 

-2 Log likelihood 10596.901b 3744.989b 3298.713b 3400.933b 

Model chi-square 

Classification 

1619.738*** 379.726*** 299.813*** 392.946*** 

percentage 86.91 75.87 80.51 78.67 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1992 coefficient at 5 percent level bSignificantly different from the "perfect" model 
56 I Turning On and Tuning In 

TABLE 40. Logistic Regression, Classical Music Participation, 

1992 

Independent Variable Live Television Radio Recording 

Urban 

Male 

.2971 ***,a 

- .3224***’a .2810"** - .2105"** 

.2500*** 

- .1316***’b .2403*** - .1904***’b 

Low income 

Moderate income 

High income 

.3312*** 

.5969*** 

1.0581 *** 

.2462*** 

.3496***’b 

.7460***’b 

.0896 

.3104***’b 

.7073***’b 

.2387*** 

.5637*** 

1.0005*** 

High school 

College 

30-something 

Middle age 

Retired 

Black 

1.0906*** 

2.4932***’a 

.0711 a 

.5792*** 

.6897*** 

- .5042*** 

.8481 *** 

1.6813***’b 

.3541 ***,b 

.8815***’b 

1.3195***’a’b 

- .1816**’b 

.6299*** 

1.7815***’b 

.3784,**,b 

.6507*** 

.5091 *** 

- .5413***’a 

.8935*** 

2.1262*** .0674a 

.2171 ***,a,b 

.1599**’b 

- .7512"** 

Asian - .1443 .2017 .0577­ .0289 

Indian - .1252 .5377* .2599 - .1578 

Hispanic - .4664*** .0031b - .03623’b - .1618 

Constant -4.6564*** -3.5044*** -2.6868*** -3.2770*** 

-2 Log likelihood 7711.036c 11351.607c 12877.276c 10871.908*** 

Model chi-square 1019.939*** 893.472*** 1368.775*** 1357.308*** 

Classification 

percentage 87.39 77.50 70.52 76.33 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1982 coefficient at 5 percent level 

bSignificantly different from corresponding "live" coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

Television 

Television participation patterns are generally similar to those for live 

participation. The urban coefficient is lower in both time periods than in the 

corresponding equations for live participation (and falls from 1982 to 1992), 

reflecting the fact that television signals are not restricted to urban areas. Men 

are not so unlikely to watch classical music on television as they are to attend a 

live performance. The income variables are not so influential as compared with 

live participation in 1992, reflecting the public-goods nature of television..Age 

patterns are similar across periods except for the retired group, where a significantly higher value in 1992 may reflect an aging audience. 
Multivariate Statistical Results I 57 

Radio 

Participation by radio is quite similar to participation by television. Income 

coefficients are lower than those in corresponding equations for live and 

television participation, a result consistent with lower user costs of radio. Urban 

residence, while significant in both periods, has become less important over 

time, although the difference is not significant. Radio participation peaks in the 

middle-age group. Black participation relative to white fell over the decade, 

suggesting that this art form is not addressing the tastes of blacks via this 

medium. 

Recordings 

Participation in classical music via recordings shows familiar patterns, with 

the likely participant being urban, female, higher income, better educated, 

white, and somewhat older--except for the retired group. Few significant 

changes have occurred over time, the exceptions being smaller age coefficients. 

Classical Music Summary 

Overall, the urban and gender factors have diminished over the period from 

1982 to 1992. Attendance at live performances increases with income, education, and age; participation via television, radio, and recordings shows generally 

similar patterns. Of special note is the relatively small negative constant term 

for the 1992 radio equation. This means that the base level of participation in 

classical music via radio is higher than in 1982 and is also higher than live and 

other media participation rates. 

Opera 

Tables 41 and 42 contain the logistic regression results for opera. 

Live Participation 

With the exception of the urban coefficient, which fell by half from 1982 

to 1992, opera participation patterns are generally stable over time. Males do 

not participate as much as females; participation rises with income, education, 

and age; and nonwhites do not participate as much as whites. The lower urban 

coefiqcient in 1992 suggests that an urban setting is not so powerful in affecting 

relative participation as it once was. 
58 I Turning On and Tuning In 

TABLE 41. Logistic Regression, Opera Participation, 1982 

Independent 

Variable Live Television Radio Recording 

Urban .8199***’a .5297*** .3452** .5273*** 

Male - .4112"** - .3002*** - .0110 - .1810 

Low income - .0448 .4595*** .1242 .4381 ** 

Moderate income .2946* .5560*** .1482 .4137" 

High income 1.0805*** .7678*** .5067* .5005 

High school 1.1090*** 1.0070*** .1440 .6265** 

College 

30-something 

Middle age 

2.4182*** 

.2861 ** 

.6486*** 

1.8099*** 

.6698*** 

1.4242*** 

1.3479*** 

.2109 

.9901 *** 

1.6312"** 

.8986***,a 

1.5850***’a 

Retired .8679*** 1.4908*** .9451 ***,a 1.2958*** 

Black - .6815"** - .1275 - .2651 - .3314 

Indian - .6340* .5532* .5493 .1399 

Constant -6.2451 *** -4.8419*** -4.2640*** -5.2711 *** 

-2 Log likelihood 3745.317b 2494.523b 1675.963b 1727.608b 

Model chi-square 430.128"** 247.983*** 125.651"** 159.043"** 

Classification 

percentage 97.05 87.62 93.25 92.84 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1992 coefficient at 5 percent level

bSignificantly different from the "perfect" model 

Television 

Participation in opera via television is, by and large, similar to live participation. The age coefficients for television are significantly higher than those for 

live participation. This indicates that, controlling for the other influences, older 

groups are much more active participants than the young adults, whose television tastes may run in other directions. Television participation does not change 

significantly over time. 

Radio 

The major distinction in opera participation via radio is that the income 

variables are not so significant, reflecting perhaps the greater relative accessibility 

of radio broadcasting. The age coefficients are higher than those for live 

attendance, indicating that young adults likely have alternative radio listening 

habits. 
Multivariate Statistical Results I 59 

TABLE 42. Logistic Regression, Opera Participation, 1992 

Independent 

Variable Live Television Radio Recording 

Urban .4093***’a .3744*** .2144** .2558*** 

Male - .2195"* - .1998"** - .1415"* - .2315"** 

Low income .0283 .0924 - .0028 .2105" 

Moderate income 

High income 

.3441 * 

1.3420*** 

.2080** 

.3800***’b .2986*** .6434***’b .6083*** 

1.0155"** 

High school .6250 .7228*** .6804*** .6558** 

College 

30-something 

Middle age 

Retired 

Black 

Asian 

1.8462*** 

.1067 

.5217*** 

.6598*** 

- .5346** 

.3332 

1.6444*** 

.4603*** 

1.1165***’b 

1.4182***’b 

.0599b 

.0002 

1.7754*** 

.6052***’b 

1.3589***’b 

1.6100***’a’b 

- .1999 

- .3013b 

1.7693*** 

.2905**,a 

.8990"**,a,b 

.9703*** 

- .5127"** 

.2734 

Indian 

Hispanic 

,2954 

- .2668 

.7045* 

.3448***’b .0210 .141 7 

- .3933 

.0983 

Constant -5.5861 *** -4.4598*** -4.8690*** -4.971 7*** 

-2 Log likelihood 3064.574c 7402.027c 6256.631c 5205.818"** 

Model chi-square 315.855*** 521.259*** 589.950*** 469.359*** 

Classification 

percentage 96.65 89.09 91.18 93.00 

***Significance greater than .01 

**Significance greater than .05

*Significance greater than .10 

aSignificantly different from corresponding 1982 coefficient at 5 percent level 

bSignificantly different from corresponding "live" coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

Recordings 

The higher user cost of recordings accounts for the higher coefficient values 

for the income variables, compared with other media alternatives. Otherwise, 

participation patterns as reflected in coefficient signs and magnitudes are similar 

to those for other forms of opera participation. The 30-something and middleage coefficients are significantly smaller in 1992, indicating a reduced influence 

of aging relative to the young adults. 

Opera Summary 

Opera participation patterns are very similar to those for classical music. 

Participation rises with age, income, and education for both live and media 

alternatives. The urban coefficients fell from 1982 to 1992, suggesting that 

proximity may have declined in importance over the decade. Income is not so 
60 I Turning On and Tuning In 

important for the broadcast (television and radio) media as it is for live and 

recorded media. 

Musicals 

Tables 43 and 44 display the results of the logistic regressions for musical 

participation. 

Live Participation 

Attendance at musicals is higher in urban areas and among females. Attendance also rises with income, education, and age up to the retired years, when 

it falls offa bit. One major distinction between 1982 and 1992 is that in 1992 

blacks are less likely to stay away compared with whites. 

TABLE 43. Logistic Regression, Musical Participation, 1982 

Independent 

Variable 

Urban 

Male 

Low income 

Moderate income 

High income 

High school 

College

30-someth i ng 

Middle age 

Retired 

Black 

Indian 

Constant 

-2 Log likelihood 

Model chi-square 

Classification 

percentage 

Live 

.5928***’a 

- .4882*** 

.3745*** 

.8308*** 

1.3870*** 

.8800*** 

2.0884*** 

.1832***’a 

.3112*** 

.1892** - .5642***’a 

- .9396*** 

-3.7177*** 

13172.162b 

1987.318*** 

81.37 

Television 

.5941 ***,a 

- .2722*** 

.4576*** 

.6654*** 

.9291 *** 

.5881 *** 

1.4188*** 

.1019a 

.4846***’a 

.6165***’a 

.0081 

- .1681 

-3.2848*** 

3464.157b 

244.974*** 

79.37 

Radio Recording 

.5132** .7276*** 

.0633 - .5135"** 

.2311 .1 731 

.1757 .5564*** 

.8872** .7904*** 

1.0183** .6911 * 

1.9627*** 2.0047*** 

.0932 .3195* 

.7480*** .8087*** 

.7293** .0067 

.2656 -1.3796*** 

.7062* - .6464 

-5.6813*** -4.6338*** 

1130.026b 1847.202b 

77.233*** 259.908*** 

96.09 91.58 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1992 coefficient at 5 percent level 

bSignificantly different from the "perfect" model 
Multivariate Statistical Results I 61 

TABLE 44. Logistic Regression, Musical Participation, 1992 

Independent 

Variable Live Television Radio Recording 

Urban .3355***’a .2678***’a .1805b .5005***’b 

Male - .4570*** - .1832***’b - .1513b - .2693***’b 

Low income .4733*** .1715*’b .0153b .0446b 

Moderate income 

High income 

High school 

.8235*** 

1.5603*** 

.9202*** 

.1943**’b 

.3258***’b 

.6334*** 

.0993b 

.3082b 

.4395b 

.2728*’b 

.6438***’b 

.2658b 

College 

30-something 

Middle age 

1.8835*** 

- .0032a 

.3085*** 

1.3496*** 

.3853***’a’b 

.8722***’a’b 

1.5587*** 

.4395**b 

.9808***b 

1.6190*** 

.1556b 

.4583*** 

Retired 

Black 

.2206** 

- .1238a 

1.2461 ***,a,b 

- .0318 

1.2471 ***b 

- .1991 

.1966 

- .6784***’b 

Asian - .8654*** - .1198b .5136*’b .2115b 

Indian .1063 .9059***’b .1791 - .0524 

Hispanic - .5397*** - .0526b .4279**’b - .1995b 

Constant -3.7749*** -3.7960*** -5.2673*** -4.5590*** 

-2 Log likelihood 9634.895c 8422.515c 3288.470c 4518.503c 

Model chi-square 1108.812*** 421.855*** 182.875*** 407.621 *** 

Classification 

percentage 82.15 87.07 96.52 94.30 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1982 coefficient at 5 percent level 

bSignificantly different from corresponding "live" coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

Television 

Of special interest in television participation for musicals are the smaller 

coefficients for income, compared with those for live participation, and the 

apparent aging of the audience, as indicated by the higher age coefficient for 

retired persons in 1992. 

Radio 

Radio participation offers no surprises beyond the result that male participation is not significantly different from female participation. Income is generally insignificant in both time periods, and black participation is not 

significantly different from white. 
62 I Turning On and Tuning In 

Recordings 

Participation via recordings shows little change over time. In 1992, several 

coefficients--especially those for income--are quite different from those for 

live participation. This is a bit surprising, as both forms of participation entail 

explicit user charges. 

Musical Summary 

Overall, patterns of participation in musicals are familiar ones. The urban 

and male coefficients have declined over time. The base levels of participation 

via radio and recordings, as indicated by their large negative constants, were 

lower than those for live and television participation. 

Theater (Plays) 

Results of the logistic regressions for participation in theater are displayed 

in Tables 45 and 46. 

Live Participation 

Results for both 1982 and 1992 show patterns similar to those noted for 

the other benchmark arts--higher rates of participation among urban dwellers 

and females, and rates rising with increased income, education, and age, except 

for a slight drop among retired persons. A notable exception to the familiar 

pattern, however, occurs with black participation. In 1992 the rate of participation among blacks is not significantly different from that of whites. This 

perhaps reflects greater availability of drama that speaks to the black experience, 

including the works of such contemporary black playwrights as August Wilson, 

among others. 

Television 

The major divergence from the 1982 participation patterns in the case of 

theater on television is the 1992 results for age, where the coefficients are much 

higher than those for live participation. This likely reflects the continuing 

development over the decade of alternative viewing habits of young adults. 

Radio 

Income is not a significant influence on participation in drama via radio in 

either 1982 or 1992, but the influence of increased age is higher and significant 
Multivariate Statistical Results I 63 

TABLE 45. Logistic Regression, Theater (Plays) Participation, 

1982 

Independent 

Variable Live Television Radio 

Urban .4408*** .5247*** .5298** 

Male - .4199"** - .2156"** - .1241 

Low income .1206 .3667*** - .3207 

Moderate income .4980*** .5699*** - .2707 

High income 1.1940*** 1.1999*** -1.4546** 

High school 

College 

30-something 

Middle age 

Retired 

1.291 7*** 

2.7063"** 

.2120***’a 

.3289*** 

.2865*** 

.9908*** 

1.9496***’a 

.0093a 

.3643**’a 

.2648*’a 

.8621 * 

1.7326*** 

- .3907*’a 

- .0746a 

- .5899*,a 

Black - .5964***’a - .2590* - .3027a 

Indian - .8909*** - .4638 - .4995 

Constant -4.5275*** -3.1719*** -4.2419*** 

-2 Log likelihood 10049.071 b 3818.382b 1178.053b 

Model chi-square 1541.749*** 380.843*** 60.209*** 

Classification percentage 87.89 75.04 95.94 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1992 coefficient at 5 percent level

bSignificantly different from the "perfect" model 

in 1992. The 1992 rate of participation by blacks is significantly higher than 

that of whites. 

Theater Summary 

The theater results are all consistent with the stated hypotheses: participation generally is greater among females and urban dwellers, and in most cases 

it increases with income, education, and age. Age coefficients increased in value 

and became more generally significant between 1982 and 1992, suggesting a 

wider gap in behaviors between young adults and older groups. Also notable is 

the insignificant difference in rates of live participation by blacks and whites in 

1992, and blacks’ higher rate of participation via radio in that year. 
64 I Turning On and Tuning In 

TABLE 46. Logistic Regression, Theater (Plays) Participation, 

1992 

Independent Variable Live Television Radio 

Urban 

Male 

Low income 

Moderate income 

High income 

High school 

College 

30-something 

Middle age 

Retired 

Black 

Asian 

.4254*** 

- .3347*** 

.2182"** 

.4590*** 

1.0827*** 

1.2816*** 

2.4997*** 

- .0477a 

.2803*** 

.2643*** 

- .0135a 

- .9241 *** 

.3915*** 

- .1551"**’b 

.1058 

.3785*** 

.5572***’b 

.7519*** 

1.4245***’a’b 

.4263***’a’b 

.9894***’a’b 

1.21 75***’a’b 

- .0986 

- .3571 ,,b 

.2336b 

.1462b 

- .2479b 

- .1328b 

- .1283b 

.6565**’b 

1.5099***’b 

.4818***’a’b 

.4824***’a’b 

.5598***’a’b 

.4732***’a’b 

.3412b 

Indian 

Hispanic 

.4047 

- .2849** 

.2758 

.1031b 

.3126 .4784,,,b 

Constant -4.4736*** -3.9266*** -5.2953*** 

-2 Log likelihood 8119.192c 9300.952c 2753.414c 

Model chi-square 925.738*** 570.747*** 85.180*** 

Classification percentage 86.66 84.59 97.29 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1982 coefficient at 5 percent level 

bSignificantly different from corresponding "live" coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

Dance 

Tables 47 and 48 show the results of the logistic regressions for ballet and 

dance. As stated earlier, the 1982 survey included questions pertaining only to 

ballet, while the 1992 survey added questions on dance more broadly defined. 

Furthermore, the 1992 media participation questions pertained only to dance. 

While this permits a comparison of live ballet attendance over time, neither 

dance over time nor media participation can be compared, because of differences 

in definitions. 

Live Participation 

Of special note is the generally insignificant impact of age on live attendance 

for both ballet in 1982 and dance in 1992, suggesting that older groups do not 

differ markedly from the young adult group in their attendance rates. Age was 
Multivariate Statistical Results I 65 

TABLE 47. Logistic Regression, Ballet Participation, 1982 

Independent Variable Live Television 

Urban 

Male 

.5359*** 

-1.0136***’a .3610"** - .7816*** 

Low income .1403 .2897** 

Moderate income .3637*** .5012*** 

High income .8291 *** .5650** 

High school 1.2474*** .4280** 

College 

30-something 

2.6958*** 

.2876***’a 1.4651 *** 

.3807*** 

Middle age .0814 .7981 *** 

Retired .0813 .7977*** 

Black - .7651"**’a - .3077 

Indian - .6083** .3966 

Constant -5.4316*** -3.1942*** 

-2 Log Likelihood 4917.686c 3004.546c 

Model chi-square 664.556*** 276.695*** 

Classification percentage 95.69 83.46 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1992 coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

significant for live ballet in 1992, but the coefficients are small, indicating that 

impacts on probabilities are slight. Age was a significant determinant of media 

(television) participation in ballet in 1982 and 1992, peaking with the middle 

age group in the earlier year and with the retired group in the latter year. 

By 1992, the negative coefficient of black participation in live ballet declined 

significantly, consistent with earlier observations regarding growing popularity 

of primarily black ballet companies. Also in 1992, participation by Indian 

respondents in live dance was significantly higher than that by whites, perhaps 

reflecting the existence of dance as an indigenous art form among Native 

Americans. This would not have been revealed by 1982 questions pertaining 

only to ballet. 

Television 

In contrast to live participation in dance forms, age is a significant determinant of television participation. Older respondents are considerably more likely 

to participate via television than are 30-somethings. Again, this may reflect the 
66 I Turning On and Tuning In 

TABLE 48. Logistic Regression, Dance Participation, 1992 

Independent Variable 

Urban 

Male 

Low income 

Moderate income 

High income 

High school 

College 

30-something 

Middle age 

Retired 

Black 

Asian 

Indian 

Hispanic 

Constant 

-2 Log Likelihood 

Model chi-square 

Live Ballet 

.4938*** 

- .5709***’a 

- .1680*** 

.3535*** 

.9302*** 

1.1300*** 

2.3871 *** 

- .0052***’a 

.0583*** 

.0697*** 

- .1719***’a 

-1.5828*** 

- .6469*** 

.0130*** 

-3.9524*** 

5.74E07c 

5.76E07"** 

Classification percentage 95.38 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

Live Dance 

.1786* 

- .2142"** 

.2754** 

.4004*** 

.3574** 

.4595** 

1.3781 *** 

.0065 

.1004 

.1060 

.2039 

- .0346 

1.3626*** 

.1919 

-3.9524*** 

5674.11 7c 

237.472*** 

92.87 

Television 

.2439*** 

- .3708*** 

.1494" 

.1028b 

.3372*** 

.4880*** 

1.1758*** 

.2952***’b 

.6908***’b 

.8359***’b 

.0724 

.1270 

.1207b 

.4507*** 

-2.9960*** 

10251.272c 

417.945*** 

82.40 

aSignificantly different from corresponding 1982 coefficient at 5 percent level


bSignificantly different from corresponding "live" coefficient at 5 percent level
 

bSignificantly different from the "perfect" model
 

differentiated viewing habits of young adults. In neither year was race a 

significant determinant of television participation in ballet and dance. 

Art 

Tables 49 and 50 contain the results of the logistic regressions for art 

participation in 1982 and 1992, respectively. 

Live participation 

From 1982 to 1992, coefficients of the education variables diminished in 

value. In both years, older age groups are less likely to participate than are young 

adults. 
Multivariate Statistical Results I 67 

TABLE 49. Logistic Regression, Art Participation, 1982 

Independent Variable Live 

Urban 

Male 

Low income 

Moderate income 

High income 

High school 

College 

30-something

Middle age 

Retired 

Black 

Indian 

Constant 

-2 Log Likelihood 

Model chi-square 

.4533*** - .3153***’a 

.1174* 

.3980*** 

.9513*** 

1.4741 ***,a 

2.8006***’a 

.0791 

- .0566 

- .1813**’a 

- .6015***’a 

- .0837
 

-3.6478***
 

14320.459b 

2277.911 *** 

Classification percentage 78.01 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

Television 

.3240*** 

- .0852 

.2123* 

.6451 *** 

.9208***’a 

1.5315***’a 

2.2505*** 

.0576 

.3828*** 

.2899** 

.0733a 

- .0351 

-3.6384 

3657.835b 

297.159*** 

76.80 

aSignificantly different from corresponding 1992 coefficient at 5 percent level
 

bSignificantly different from the "perfect" model
 

Television 

As for live participation, coefficients of the education variables declined 

between 1982 and 1992. Male participation is not significantly different from 

female participation via this medium, and age variables for television show 

somewhat more significance than those for live participation in both periods. 

Summary 

The results of the logistic regressions generally confirm the findings reported 

in Part II, even when controlling for other influences. Except for jazz, participation rises with age, income, and education for all art forms and all media, 

thereby confirming the proffered hypotheses. Other noteworthy findings include the following: 

 ̄	 Education coefficients generally are lower for media participation than for 

live participation. This suggests that media are something of an equalizer, 
68 I Turning On and Tuning In 

 ̄ 

 ̄ 

 ̄ 

 ̄ 

TABLE 50. Logistic Regression, Art Participation, 1992 

Independent Variable Live Television 

Urban .4496*** .1210**’b 

Male 

Low income 

Moderate income 

High income 

High school 

Col lege 

30-something 

Middle age 

Retired 

Black 

Asian 

- .1590***’a 

.4274*** 

.6864*** 

1.0195*** 

1.0449***’a 

2.3690***’a 

- .1280"* 

- .1172* 

- .3566***’a 

- .3945***’a 

- .2123 

- .0664 

.1442**’b 

.1886***’b 

.3863***’b 

.7598***’a 

1.4654***’a’b 

.1632***’b 

.3171 ***,b 

.1246***’b 

- .4058***’a 

- .6519***’b 

Indian .2506 .1965 

Hispanic - .3741"** - .1868"* 

Constant -3.3717*** -2.2076*** 

-2 Log likelihood 

Model chi-square 

Classification percentage 

11514.743c 

1758.139*** 

74.06 

13461.816c 

646.599*** 

69.54 

***Significance greater than .01 

**Significance greater than .05 

*Significance greater than .10 

aSignificantly different from corresponding 1982 coefficient at 5 percent level bSignificantly different from corresponding "live" coefficient at 5 percent level 

CSignificantly different from the "perfect" model 

diminishing the distinctions in participation patterns by education 

groupings. 

Similarly, income coefficients are lower for the media equations than for 

live participation. This indicates that the media also diminish distinctions 

in participation by income group. 

The urban coefficient is lower for media participation than for live participation. Although the differences are not significant, the nearly uniform 

pattern indicates that location is not so important for media participation. 

The age coefficients generally are larger for media participation than for live 

participation, indicating that older groups have relatively greater access to 

the arts via media as compared with live attendance. 

While the income and education coefficients generally declined between 

1982 and 1992, indicating a relative decline in participation distinctions, 

age coefficients rose, further indicating an aging audience. 
Multivariate Statistical Results I 69 

Although the explanatory variables, both singly and in concert, are significant and generally have the expected signs, the overall equations lack persuasive 

explanatory power. Apparently numerous additional factors---or simply a great 

deal of randomness--influence participation in the arts, both live and via media. 

In summary, the media seem to be ensuring greater relative access to the arts for 

various demographic groups. 
The Cross Effects of Media 

and Live Participation 

What is the nature of the cross effects of live and media participation? Are 

the media complements to live participation in the arts, or are they 

substitutes? This part of the monograph offers a partial answer, and the future 

research agenda points to a fuller answer yet to come. 

The tables in the following sections contain the percentages of respondents 

by column and by row. The top number in each cell is the percentage of those 

who gave the ra~ response and also gave the column response. The bottom 

number in each cell is the percentage of those who gave the calurnn response 

who also gave the ro~ response. For example, in Table 52, the first entry under 

television, No, is 85.6. This is the percentage of respondents who did not 

participate in live jazz who also did not participate in televised jazz in 1982. The 

second number, 94.0, is the percentage of those who did not participate in 

televised jazz who also did not participate in live jazz. 

Table 51 shows hypothetical tabular entries for each of two cases. In the 

first instance, "Medium X," 100 percent of those who do not participate via the 

medium also do not attend live performances (the "northwest" quadrant), while 

100 percent of those who do participate via the medium also attend live 

performances (the "southeast quadrant"). The same is true of those who attend 

live performances; they all participate by media. In this case, the two types of 

participation are perfect complements. 

TABLE 51. Hypothetical Table Entries 

Perfect Complements Perfect Substitutes 

Medium X Medium Y 

Live No Yes No Yes 

No 100.0 0.0 0.0 100.0 

100.0 0.0 0.0 100.0 

Yes 0.0 100.0 100.0 0.0 

0.0 100.0 100.0 0.0 

70 
The Cross Effects of Media and Live Participation I 71 

For "Medium Y," the opposite is true. None of those who participate via 

the medium attend live performances, while none of those who attend live 

performances participate via the medium. Here, the medium and live performances are perfect substitutes. 

The reality is not this simple. 

Jazz 

In general, Tables 52 and 53 indicate that those who did not attend a jazz 

performance were unlikely to participate in a televised, radio, or recorded 

performance in either 1982 or 1992. Nor were those who did not participate 

by media likely to attend live performances. 

In 1982, 51.1 percent of respondents who attended a live jazz performance 

also viewed a performance on television. This percentage had fallen to 43.8 in 

1992. By the same token, 28.3 percent who saw jazz on television in 1982 also 

attended a live performance, but this had fallen to 25.9 percent in 1992. Overall, 

then, we could state that those who attend live jazz are more likely to watch jazz 

on television than the converse. In contrast, the percentage of those viewing jazz 

on television, but not attending a live performance, rose from 71.7 percent in 

1982 to 74.1 percent in 1992, indicating that televised jazz may have become 

a more significant substitute for live attendance over the decade. 

Participation by radio showed much the same pattern. Over 58 percent of 

those who attended a live performance also listened to jazz on the radio in 1982, 

and this percentage rose to more than 75 percent in 1992. However, the 

percentage of those who listened to jazz on the radio but did not attend a live 

performance rose from 67.7 percent to 71.5 percent. 

Finally, the percentage who attended live jazz and also listened to a recorded 

performance rose from 65.5 percent to 67.9 percent over the decade, while the 

TABLE 52. Jazz Cross-Participation, 1982 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 85.6 

94.0 

14.4 

71.7 

86.4 

94.9 

13.6 

67.7 

84.9 

95.6 

15.1 

67.2 

Yes 48.9 

6.0 

51.1 

28.3 

41.8 

5.1 

58.2 

32.3 

34.5 

4.4 

65.5 

32.8 
 

72 I Turning On and Tuning In 

TABLE 53. Jazz Cross-Participation, 1992 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 85.2 14.8 77.5 22.5 85.1 14.9 

92.7 74.1 96.4 71.5 95.7 64.6 

Yes 56.2 43.8 24.3 75.7 32.1 67.9 

7.3 25.9 3.6 28.5 4.3 35.4 

percentage who listened to a jazz recording and also attended a live performance 

also rose, from 32.8 to 35.4. 

Overall, the pattern indicates the media provide access for those who choose 

not to, or are unable to, attend a live performance. Approximately two-thirds 

to three-fourths of those who indicate media participation in jazz do not attend 

live performances. 

Classical Music 

From 1982 to 1992, the percentage of respondents who attended a classical 

music concert and also viewed classical music on television dropped precipitously, from 62.3 to 51.7 percent, as shown in Tables 54 and 55. As indicated 

earlier, this trend may well reflect reduced television broadcasting of classical 

music. The percentage who watched classical music on television and also 

attended a live performance remained essentially unchanged at just over 29 

percent. 

TABLE 54. Classical Music Cross-Participation, 1982 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 80.3 19.7 84.8 15.2 83.7 16.3 

94.1 70.5 93.5 67.3 94.8 65.1 

Yes 37.7 62.3 44.4 55.6 34.4 65.6 

5.9 29.5 6.5 32.7 5.2 34.9 
 

The Cross Effects of Media and Live Participation I 73 

TABLE 55. Classical Music Cross-Participation, 1992 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 82.4 1 7.6 75.3 24.7 81.9 18.1 

92.3 70.6 95.2 70.3 93.8 66.2 

Yes 48.3 51.7 26.6 73.4 36.8 63.2 

7.7 29.4 4.8 29.7 6.2 33.8 

Radio and live performance showed a very different pattern. The percentage 

who attended and also listened on radio rose from 55.6 percent to 73.4 percent 

over the decade, while the percentage of those who listened and also attended 

fell slightly, from 32.7 to 29.7 percent. It seems very likely that this shift reflects 

the nearly ubiquitous availability of classical music on radio by 1992. 

Finally, the percentage of those who attended live performances and also 

listened to recorded performances fell from 65.6 percent to 63.2 percent. This 

occurred despite the greater sound fidelity afforded by compact discs, widely 

available in 1992. One can only hazard the guess that relatively higher prices of 

CDs discouraged potential purchasers/listeners. 

Opera 

The pattern of cross-participation in opera is quite similar to that for classical 

music. As shown in Tables 56 and 57, in 1982, well over half of those who 

attended live performances also watched opera on television; but by 1992 this 

TABLE 56. Opera Cross-Participation, 1982 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 89.0 11.0 93.8 6.2 93.4 6.6 

98.8 89.6 98.7 85.0 98.6 86.2 

Yes 45.2 54.8 53.8 46.2 54.9 45.1 

1.2 10.4 1.3 15.0 1.4 13.8 
74 I Turning On and Tuning In 

TABLE 57. Opera Cross-Participation, 1992 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 90.2 9.8 92.7 7.5 94.2 5.8 

97.7 88.6 97.9 84.0 97.9 80.2 

Yes 62.3 37.7 57.7 42.3 58.2 41.8 

2.3 11.4 2.1 16.0 2.1 19.8 

percentage had fallen to 37.7 percent, probably reflecting reduced availability 

of televised opera. The percentage of those who watched on television and also 

attended live opera performances remained low, around 11 percent. It may well 

be that a taste for opera, as indicated by television participation, is not sufficient 

to overcome relatively high ticket prices. 

The percentage of attenders of live performances who listened to opera on 

radio fell a bit, from 46.2 to 42.3 percent. Perhaps the fact that less than half 

of the performance attenders listen on the radio reflects the visual nature of 

opera, a dimension that is lost on radio. 

Finally, the percentage of attenders of live performances who listened to a 

recorded performance fell from 45.1 percent to 41.8 percent, consistent with 

the expected impact of higher-priced CDs. (There may also be an aversion 

among opera aficionados to CD technology, although this remains conjectural.) 

Interestingly, the percentage of those who listened to a recording and ’also 

attended a live performance, while remaining low overall, rose from 13.8 to 

19.8 percent. Since live performances did not get less expensive over the decade, 

this may reflect the larger number of opera companies in 1992, as well as greater 

audiences for existing companies.2° 

Musicals 

The percentage of respondents who attended live musical performances and 

also watched on television fell substantially--from 43.8 to 24.7 percent--over 

the decade, as shown in Tables 58 and 59. This very likely reflects a decline in 

the availability of televised musicals during that period. The reason for the 

decline--not so stark---in the percentage of television viewers of musicals who 

also attended live performances is not so clear. 

Very few--between 8 and 9 percent in both survey periods--of those who 
The Cross Effects of Media and Live Participation I 75 

TABLE 58. Musical Cross-Participation, 1982 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 85.1 14.9 96.7 3.3 95.0 5.0 

86.7 59.5 82.0 62.3 84.1 48.2 

Yes 56.2 43.8 91.4 8.6 77.1 22.9 

13.3 40.5 18.0 37.7 15.9 51.8 

TABLE 59. Musical Cross-Participation, 1992 

Television Radio Recording 

Live No Yes No Yes No Yes 

No 90.0 10.0 97.6 2.4 96.9 3.1 

85.1 65.8 83.5 58.0 84.7 44.6 

Yes 75.3 24.7 91.6 8.4 82.1 1 7.9 

14.9 34.2 16.5 42.0 15.3 55.4 

attended a live musical performance also listened on radio, probably because the 

medium does not lend itself well to this art form. Memorable and listenable 

songs are interspersed with spoken dialogue. Furthermore, the visual aspects of 

musicals are lost to the radio listener. Of those who do choose to listen to 

musicals on the radio, however, the percentage who attend live performances 

rose over the decade, from 37.7 to 42 percent. While this may reflect growth 

of new performing venues and the resurgence of Broadway touring companies, 

these phenomena did not show up in the television figures. 

The decline in the percentage of attenders at live performances who also 

listened to recorded performances (from 22.9 percent in 1982 to 17.9 percent 

in 1992) may reflect both the increased prices of CDs and the failure of 

recordings to convey adequately the visual aspects of musicals. 

Theater (Plays) 

Among the media, only television lends itself well to theater participation. 

Even so, among those who attended live performances, the percentage who also 
76 I Turning On and Tuning In 

TABLE 60. Theater (Plays) Cross-Participation, 1982 

Television Radio 

Live No Yes No Yes 

No 78.1 

93.6 

21.9 

75.3 

97.0 

89.6 

3.0 

68.9 

Yes 42.6 

6.4 

57.4 

24.7 

89.4 

10.4 

10.6 

31.1 

TABLE 61. Theater (Plays) Cross-Participation, 1992 

Television Radio 

Live No Yes No Yes 

No 88.0 12.0 97.9 2.1 

89.4 70.0 87.1 65.7 

Yes 66.9 33.1 92.8 7.2 

10.6 30.0 12.9 34.3 

viewed plays on television fell from 57.4 percent in 1982 to 33.1 percent in 

1992, as shown in Tables 60 and 61. Once again we may speculate that this is 

due to reduced availability on broadcast television. On the other hand, those 

who do watch drama on television were more likely to attend live performances 

in 1992 than in 1982. 

Attenders of live theater performances are not very likely to listen to plays 

on the radio. In 1982, only 10.6 percent did so, and this fell to 7.2 percent in 

1992. But the percentage of those who do listen to radio broadcasts andalso 

attend live performances rose from 31.1 to 34.3 percent. 

Ballet/Dance 

Changes over the decade in ballet and dance participation must be interpreted in light of the fact that the dance forms reported here are not strictly 

comparable. Given that caveat, it is notable that while 57 percent of those who 

attended a live ballet performance in 1982 also viewed a televised performance, 
The Cross Effects of Media and Live Participation I 77 

TABLE 62. Ballet Cross- TABLE 63. Dance CrossParticipation, 1982 Participation, 1992 

Television Television 

Live No Yes Live No Yes 

No 85.4 14.6 No 84.6 15.4 

97.9 85.6 94.9 83.2 

Yes 43.0 57.0 Yes 59.5 40.5 

2.1 14.4 5.1 16.8 

only 40.5 percent did so with respect to dance, more broadly defined, in 1992 

(see Tables 62 and 63). In both time periods, the vast majority of those who 

did watch ballet or dance on television did not attend a live performance. 

Art 

As indicated in Tables 64 and 65, the proportion of those who attended an 

art museum and also saw a televised program on art rose from just under half 

in 1982 to just over half 10 years later. Likewise, the proportion of those who 

watched a program and also visited a museum rose. Among all the art forms, 

this is the sole instance of increased cross-participation in both directions. 

TABLE 64. Art Cross- TABLE 65. Art CrossParticipation, 1982 Participation, 1992 

Television Television 

Live No Yes Live No Yes 

No 84.1 15.9 No 78.0 21.5 

85.0 54.4 82.3 52.7 

Yes 52.8 47.2 Yes 46.3 53.2 

15.0 45.6 17.7 47.3 
78 I Turning On and Tuning In 

Summary and Conclusions 

The statistics related to cross-participation in the arts via media alternatives 

and live attendance indicate that those who shunned live attendance also 

shunned media participation and vice versa; but very often, a majority of those 

who participated by media did notattend live performances or showings. A more 

positive slant is that respondents who did not attend live performances or 

showings did participate by media. This further suggests that the media constitute a more-or-less readily available alternative to live attendance. While in many 

cases this percentage declined over the 1 O-year period between surveys, we can 

only speculate that media participation may have encouraged greater attendance 

at the arts. 
Summary and 

Conclusions 

This monograph examines patterns of public participation in seven core, or 

"benchmark," arts via selected electronic media: television, radio, and 

recordings. More specifically, it examines the demographic determinants of 

participation via media and how the demographics may differ between live and 

media participation. Testable hypotheses derived from the theory of consumer 

demand were tested with data from the 1982 and 1992 Surveys of Public 

Participation in the Arts. 

This part of the monograph reviews the hypotheses and findings, ventures 

some policy implications, and issues the standard call for further research. After 

all, any exploration of this nature should uncover new questions even as it strives 

to answer existing ones. 

Major Findings 

The results of the statistical analysis are consistent with the hypotheses and 

with previously existing evidence that arts participation increases with age. This 

is true of media participation as well as live participation. While this means that 

an aging population will, other things being equal, enhance arts participation, 

it also bodes less well for the future, when the smaller, post-baby boom 

generation is in the ascendancy. Even if participation rates remain high, the 

numbers may decline and imperil arts providers. 

The results reported here also confirm numerous prior analyses of the impact 

of education. A more educated populace is more "arts friendly," and rates for 

both live and media participation rise with education. 

Arts participation also rises as income increases. But of special note here is 

that participation via media--especially the broadcast media--is not so income 

dependent. This reflects the likelihood that additional out-of-pocket costs of 

listening to the radio or viewing television are negligible, so that broadcast arts 

are accessible to those without high incomes. 

While urban residents are more likely than rural residents to participate in 

the arts via media as well as to attend live performances, the difference is not so 

strong for media participation. This suggests that the media provide relatively 

greater access to the arts for nonurban residents. 

79 
80 I Turning On and Tuning In 

Other demographic variables, including race and gender of respondent, 

were employed here primarily for control purposes. Findings confirm that 

whites are more likely to participate than nonwhites, and women more than 

men, except in the case of jazz. 

Policy Implications 

With the increasing availability of cable and direct satellite access television, 

literally hundreds of channels will be available to viewers. Some of these could 

surely be dedicated to the arts, and even to specific art forms: the opera channel, 

the symphony channel, the Schubert channel, the post-modern dance channel, 

and so forth. This will promote both variety and access. 

Since education exposure seems to be consistent with development of taste 

for the arts, educators and educational institutions at all levels may take 

advantage of both live and media access to the arts and develop arts curricula 

that incorporate instructional technology. 

Special arts events--"The Three Tenors," for example--represent opportunities for "blockbuster" broadcasts and subsequent audio and video recordings.21 Improving technology and increasing competition continue to drive 

down the prices of such recordings, making them available to potential buyers 

with limited incomes. 

The rapid development of distance learning techniques and instructional 

technologies offer opportunities for arts programming to reach audiences via 

the Internet, CD-ROM, interactive television, and means as yet unforeseen. 

One can imagine, for example, a CD-ROM that plays a symphony, portrays 

the orchestra, and tracks the score simultaneously, allowing the viewer to 

suspend the performance at any time for an interactive help session or to access 

expert commentary. Public seed monies may be useful to support such 

innovations. 

Future Research 

Many additional questions remain. What, for example, might be the cross 

effects revealed by a simultaneous logit model, whereby live and media participation are hypothesized to affect each other? How sensitive are these results to 

the choice of educational, income, and age groupings? 

What information might be gained from more frequent surveys as well as 

more specific geographic breakdowns of data? It is easy to imagine that annual 

or biannual data for, say, a metropolitan area would provide feedback on the 
Summary and Conclusions I 81 

effect of pricing policies on participation, the role of changes in amount or 

structure of subsidies, the impact of new technologies, and similar timedependent changes. 

Even as the data gleaned from these surveys continue to undergo scrutiny, 

planning and implementation of successive efforts should be underway. The 

arts and arts policy are too important to be left to interpolation and other forms 

of informed guesswork. 
 

 

 

 

 

Appendix A: 

1992 Survey of Public Participation 

in the Arts 

INTRODUCTION - Now I have some questions about your leisure activities. The Bureau of the 

Census is collecting this information for the National Endowment for the Arts. The survey is 

authorized by Title 20, United States Code, section 954 and Title 13, United States Code, section

8. Your participation in this interview is voluntary and there are no penalties for not answering 

some or all of the questions. (If PERSONAL INTERVIEW, hand respondent the Privacy Act Statement, 

SPPA-13.) ~ 

1. The following questions are about YOUR activities during the LAST 12 months-­

between 1, 19 __, and

., 19 __. 

With the exception of elementary or high 

school performances, did YOU go to a live jazz performance during the LAST 12 

MONTHS? 

~ 0[~No 

Yes - About how many times did you do 

this during the LAST 12 MONTHS? 

~[~ Number of times 

2. (With the exception of elementary or high

school performances,) Did you go to a live 

classical music performance such as symphony, chamber, or choral music 

during the LAST 12 MONTHS? 

~ 0~-INo 

Yes - About how many times did you do 

this during the LAST 12 MONTHS? 

Number of times 

3. (With the exception of elementary or high school performances,) Did you go to a live 

opera during the LAST 12 MONTHS? 

5. (With the exception of elementary or high school performances,} Did you go to a live

performance of a non-musical stage play 

during the LAST 12 MONTHS? 

~ OI-I NO
 

Yes - About how many times did you do 

this during the LAST 12 MONTHS? 

~ 

Number of times 

6.	 (With the exception of elementary or high

school performances,) Did you go to a live

ballet performance during the LAST 12 

MONTHS? 

o[No 

Yes - About how many times did you do 

this during the LAST 12 MONTHS? 

~ 

Number of times 

7.	 (With the exception of elementary or high

school performances,) Did you go to a live

dance performance other than ballet, such

as modern, folk, or tap during the LAST 12

MONTHS? 

~ 0[]No

Yes - About how many times did you do this during the LAST 12 MONTHS? 

I I [ [ 

~ Number of times 

~ 0[~No 	 8. (During the LAST 12 MONTHS,) Did you 

Yes - About how many times did you do 

this during the LAST 12 MONTHS? 

~ Number of times 

4. (With the exception of elementary or high 

school performances,) Did you go to a live

musical stage play or an operetta during

the LAST 12 MONTHS? 

~ 0[]NoYes - About how many times did you do 

this during the LAST 12 MONTHS? 

Number of times 

visit an ART museum or gallery? 

~ 0[]N0 

Yes - About how many times did you do this during the LAST 12 MONTHS? 

~ Number of times 

9. (During the LAST 12 MONTHS,) Did you 

visit an ART fair or festival, or a CRAFT fair

or festival? 

~ 0[No 

Yes -About how many times did you do 

this during the LAST 12 MONTHS? 

~ Number of times 

82 
1992 Survey of Public Participation in the Arts I 83 

10.	 (During the LAST 12 MONTHS,) Did you

visit an historic park or monument, or 

tour buildings, or neighborhoods for their

historic or design value? 

~ o[~No 

Yes - About how many times did you do 

this during the LAST 12 MONTHS? 

~ Number of times 

11.	 With the exception of books required for


work or school, did you read any books


during the LAST 12 MONTHS?
 

Yes - About how many books did you read during the LAST 12 MONTHS? 

~ Number of books 

12.	 (During the LAST 12 MONTHS,) Did you read any -

Read answer categories 

a. Plays? ~ ~]No 2~]Yes 

b. Poetry? [-~ I~]No 2F3Yes 

c. Novels or short stories? ~ ~[~No 21--]Yes 

13.	 (During the LAST 12 MONTHS,) Did you


listen to ­

a. A reading of poetry, 

either live or recorded? ~ llaNo 2[~Yes 

b. A reading of novels or
 books either live or
 

recorded?
 ~ I~]No 2[~Yes 

14a.(During the LAST 12 MONTHS,) Did you
 watch a jazz performance on television or


a video (VCR) tape?
 

~[~No - Skip to item 14c 

Yes - Was that on TV, VCR, or both? 

3[~VCR
 

4 [] Both
 

b. About how many times did you do this in


the LAST 12 MONTHS?
 

Number of times 

c. (During the LAST 12 MONTHS,) Did you


listen to jazz on radio?
 

o2~ ~[~No 

2~]Yes 

d. (During the LAST 12 MONTHS,) Did you


listen to jazz records, tapes, or compact


discs? 

~ ,E~No 

2~]Yes 

15a.(During the LAST 12 MONTHS,) Did you watch a classical music performance on 

television or a video (VCR) tape? 

~]No - Skip to item 15c 

Yes - Was that on TV, VCR, or both? 

~[~TV 

3~]VCR 

4 [] Both 

b. About how many times did you do this (in

the LAST 12 MONTHS}? 

~ Number of times 

c. (During the LAST 12 MONTHS,) Did you

listen to classical music on radio? 

d. (During the LAST 12 MONTHS,) Did you

listen to classical music records, tapes or 

compact discs? 

o3_~d ,DNo
 

2E3Yes
 

16a.(During the LAST 12 MONTHS,) Did you watch an opera on television or a video

(VCR) tape? 

~FqNo- Skip to item 16c 

Yes - Was that on TV, VCR, or both? 

2[-]TV
 

~-]VCR
 

4r~Both
 

b. About how many times did you do this (in

the LAST 12 MONTHS)? 

~ Number of times 

c. (During the LAST 12 MONTHS,) D d you

listen to opera music on radio? 

d. (During the LAST 12 MONTHS,) D d you

listen to opera music records, tapes, or 

compact discs? 

~ ~r~No
 

2E~Yes
 

17a.With the exception of movies, did you watch a musical stage play or an operetta 

on television or a video (VCR) tape during the LAST 12 MONTHS? 

o’~ l~]No- Skip to item 17c 

Yes - Was that on TV, VCR, or both? 

2{~TV
 

3[]VCR
 

4~]8oth
 

b.About how many times did you do this (in

the LAST 12 MONTHS)? 

~ Number of times 

c. (During the LAST 12 MONTHS,) D d you 

listen to a musical stage play or an operetta

on radio? 

~--~ 

~[~Yes 

d. (During the LAST 12 MONTHS,) Did you

listen to a musical stage play or an operetta

on records, tapes, or compact discs? 

~ ~r~No 

2~]Yes 
84 I Turning On and Tuning In 

18a.With the exception of movies, situation comedies, or TV sertes did you watch a

non-musica( stage play on television or a video

(VCR) tape during the LAST 12 MONTHS? 

~rqNo - Skip to item 18c 

Yes - Was that on TV, VCR, or both?

2FqTV 

3r’qVCR 

4[]Both
 

b.About how many times did you do this (in the

LAST 12 MONTHS)? 

Number of times 

c. (During the LAST 12 MONTHS,) Did you listen 

to a radio performance of a non-musical stage play? 

~ ~No
 

2r~Yes
 

19a.With the exception of music videos, did you watch on television or a video (VCR) tape

dance such as ballet, modern, folk, or tap

during the LAST 12 MONTHS? 

~ [] NO - Skip to item 20a 

Yes - Was that on TV, VCR, or both?

2[-qTV 

3t-]VCR 

4 [] Both 

b. About how many times did you do this (in


the LAST 12 MONTHS)?
 

Number of times 

20a.(During the LAST 12 MONTHS,) Did you watch 

a program about artists, art works, or art

museums on television or a video (VCR) tape? 

~rqNo - Skip to item 21a 

Yes -Was that on TV, VCR, or both? 

3r-lVCR
 

4 [] Both
 

b. About how many times did you do this (in

the LAST 12 MONTHS)? 

Number of times 

21a.l’m going to read a list of events that some
 people like to attend. If you could go to any of


these events as often as you wanted, which
 

ones would you go to MORE OFTEN than you

do now? I’ll read the list. Go to -

Mark (X) all that apply. 

ll~Jazz music performances 

2[]Classical music performances
 

~ [] Operas
 

4[] Musical plays or operettas
 

~!’-INon-musical plays
 

6 [] Ballet performances
 

7[]Dance performances other than ballet 

8[]Art museums or galleries 

9rqNone of these - Skip to item 22a 

If only one is chosen, skip to item 22a.
 

If more than one is chosen, ask ­

b. Which of these would you like to do most? 

[_~ Category number 

ooF-]No one thing most 

22a.The following questions are about your
 participation in other leisure activities.
 

Approximately how many hours of television 

do you watch on an average day? 

Number of hours 

b. During the LAST 12 MONTHS, did YOU go 

out to the movies? 

~ , ̄No 

2[]Yes 

c, With the exception of youth sports, did you

go to any amateur or professional sports

events during the LAST 12 MONTHS? 

~ ~[]No 

2[]Yes 

d. During the LAST 12 MONTHS, did you go to

an amusement or.theme park, a carnival, or 

a similar place of entertainment? 

~ ,[]No~r’-IYes 

e.	 During the LAST 12 MONTHS, did you jog,

lift weights, walk, or participate in any other

exercise program? 

~ 1 [~] No 

21"-1Yes 

f.	 During the LAST 12 MONTHS, did you

participate in any sports activity, such as

softball, basketball, golf, bowling, skiing, or 

tennis? 

~ ,[]No
 

21--lYes
 

g. Did you participate in any outdoor activities, 

such as camping, hiking, or canoeing during

the LAST 12 MONTHS? 

~ ~[]No
 

2[]Yes
 

h. Did you do volunteer or charity work during

the LAST 12 MONTHS? 

~ ~[~No 

~[]Yes 

Did you make repairs or improvements on

your own home during the LAST 12

MONTHS? 

~[]No 

2[]Yes 

Did you work with indoor plants or do any 

gardening for pleasure during the LAST 12

MONTHS? 

23a.(During the LAST 12 MONTHS,) Did you work with pottery, ceramics, jewelry, or do any

leathsrwork or metalwork? 

~’~ 1F]No- Skip to item 24a
 

2J-rYes
 

b. Did you publicly display any of your works? 

~ ,[]No
 

2FIYes
 
1992 Survey of Public Participation in the Arts I 85 

24a.(During the LAST 12 MONTHS,) Did you do any weaving, crocheting, quilting, 

needlepoint, or sewing? 

1 [] No - Skip to item 25a 

2[]Yes 

b. Did you publicly display any of your works? 

~ ~[]No
 

21-3 Yes
 

25a.(During the LAST 12 MONTHS,) Did you
 make photographs, movies, or video tapes
 

as an artistic activity?
 

~[-]No - Skip to item 26a 

;[]Yes 

b. Did you publicly display any of your works? 

~ ,[]No
 

2[]Yes
 

26a.(During the LAST 12 MONTHS,) Did you do
 

any painting, drawing, sculpture, or


printmaking activities?
 

d~No- Skip to item 27a 

2F~Yes 

b. Did you publicly display any of your works? 

2[]Yes 

27a.With the exception of work or school, did you do any creative writing such as stories, poems,

or plays during the LAST 12 MONTHS? 

~	 ~[~No - Skip to item 28a
 

2[]Yes
 

b. Were any of your writings published? 

~ ~No
 

2~Yes
 

28a.Did you write or compose any music during
 the LAST 12 MONTHS?
 

~ [] No - Skip to item 29a 

~l--lYes 

b. Was your musical composition played in a

public performance or rehearsed for a public

performance? 

~ ~r~No
 

2~-IYes
 

29a.Do you own any original pieces of art, such
 as paintings, drawings, sculpture, prints, or


lithographs?
 

~-INo - Skip to item 30a 

2t-/Yes 

b.Did you purchase or acquire any of these

pieces during the LAST 12 MONTHS? 

~ ~[]No
 

~l~Yes
 

30a.During the LAST 12 MONTHS, did you
 perform or rehearse any jazz music?
 

~	 ~ []No - Skip to item 31a 

~[]Yes 

30b.Did you play any jazz in a public performance or rehearse for a public performance? 

~ ~[]No
 

2[]Yes
 

31a.During the LAST 12 MONTHS, did you play
 any classical music?
 

~	 ~ [] No - Skip to item 32a
 

21-]Yes
 

b.Did you play classical music in a public


performance or rehearse for a public


performance?
 

2[~Yes 

32a.During the LAST 12 MONTHS, did you sing any music from an opera? 

o8~] ~ []No - Skip to item 33a 

2r-]Yes 

b. Did you sing in a public opera performance

or rehearse for a public performance? 

~ ~]No
 

2[~Yes
 

33a.During the LAST 12 MONTHS, did you sing
 music from a musical play or operetta?
 

I[-INo I Skip to item 33c 

2~Yes 

b. Did you sing in a public performance of a

musical play or operetta or rehearse for a

public performance? 

~No 

2[]Yes 

During the LAST 12 MONTHS, did you sing in

a public performance with a chorale, choir, 

or glee club or other type of vocal group, or rehearse for a public performance? 

1E3No
 

2[]Yes
 

(During the LAST 12 MONTHS,) Did you act in a

public performance of a non-musical play or

rehearse for a public performance? 

35a.(During the LAST 12 MONTHS,) Did you dance any ballet? 

,r-lNo - Skip to item 36a 

2r-lYes 

b. Did you dance ballet in a public performance

or rehearse for a public performance? 

~ , r-] No
 

2r~Yes
 

36a.(During the LAST 12 MONTHS,) Did you do any 

dancing other than ballet such as modern, folk.

or tap? 

~-~ ~r-3No- Skip to item 37a 

2[~Yes 

b.Did you dance modern, folk, or tap in a
 

public performance?
 

~ ,~No 

21~ Yes 
86 I Turning On and Tuning In 

37a. I’m going to read a list of some types of
 

music. As I read the list, tell me which of


these types of music you like to listen to? 

Mark (X) all that apply. 

~	 ~[]Classical/Chamber music 

2 [] Opera 

3 [] Operetta/Broadway musicals/Show tunes 

4[~ Jazz
 

5 [] Reggae ~
 (Reg g~y’) 

~[]Rap music 

~ 7[]Soul 8~-]Blues/Rhythm and blues
 

9 [] Latin/Spanish/Salsa
 

10[~ Big band
 ~ ~[]Parade/Marching band 

~2 []Country-western 

~ ~3 [] Bluegrass 

~4~ Rock 

~]The music of a particular Ethnic/ 

National tradition 

~s~Contemporary folk music ~ ,7[]Mood/Easy listening 

,~l-INew age music 

~ ,sl~Choral/Glee club

-,’k- 20 [] Hymns/Gospel 

~r~All 

221-’1None/Don’t like to listen to music - Skip to item 38a 

b. If only one category is marked in 37a, enter code in

37b without asking. Which of these do you like 

best?

~ [-~1 Category number 

0o[’-] No one type best 

38a.Have you EVER taken lessons or classes in
 

music - either voice training or playing an


instrument?
 

,[]No - Skip to item 39a
 

2J-]Yes
 

b. Did you take these lessons when you were -

Read categories. (Do not read category 4 if

respondent is under 25 years old,) 

Mark (X) all that apply. 

~	 ~[]Less than 12 years old
 

2~]12-17 years old
 

3[]18-24 years old
 

~[]25 or older 

Refer to item 38b 

Is box 1 or 2 marked in item 38b? 

I-~No - Skip to Check Item B 

[~Yes - Ask item 38c 

38c.Were these lessons or classes offered by the
 elementary or high school you were


attending or did you take these lessons
 

elsewhere? 

~	 ~ [] Elementary/high school
 

~ [] Elsewhere
 

3 [] Both
 

Refer to item 38b 

If box 4 is marked in item 38b, ASK item 38d. 

If not - Is box 2 or 3 marked in item 38b AND 

the respondent is under 25 years old? 

[] No - Skip to item 39a 

r-]Yes - Ask item 38d 

38d.Did you take any of these lessons or
 classes in the past year?
 

,[]No
 

~l~Yes
 

FORM SPPA-2 ~4 9 92) 

39a. (Have you EVER taken lessons or

classes) in visual arts such as sculpture, 

painting, print making, photography, or

film making? 

~	 ~ I~No - Skip to item 40a 

~1"3 Yes 

b. Did you take these lessons when you were - Read categories. (Do not read category 4 if respondent is under 25 years old.) 

Mark (X) all that apply. 

~	 :~Less than 12 years old
 

2[~12-17 years old
 

31~ 18-24 years old
 

~[~25 or older 

Refer to item 39b 

Is box 1 or 2 marked in item 39b? 

[] No - Skip to Check Item D 

r~Yes - Ask item 39c 

39c.Were these lessons or classes offered by the elementary or high school you were 

attending or did you take these lessons

elsewhere? 

~	 ~ []Elementary/high school
 

2 [] Elsewhere
 

3 [] Both
 

Refer to item 39b
 

tf box 4 is marked in item 39b, ASK item 39d.
 

If not-Is box 2 or 3 marked in item 39b AND
 

the respondent is under 25 years old?
 

[] No - Skip to item 40a
 

[]Yes - Ask item 39d
 

39d.Did you take any of these lessons or classes
 in the past year?
 

40a. (Have you EVER taken lessons or classes) in
 

acting or theater?
 

~	 ~ [] NO - Skip to item 4 la
 

2~Yes
 

b. Did you take these lessons when you were - Read categories, (Do not read category 4 if respondent is under 25 years old.)

Mark/X) all that apply. 

~	 ~ [] Less than 12 years old
 

2[]12-17 years old
 

31-~ 18-24 years old
 

~1-]25 or older
 

Refer to item 40b 

Is box 1 or 2 marked in item 40b? 

[] No - Skip to Check Item F 

[]Yes - Ask item 40c 

40c. Were these lessons or classes offered by the
 

elementary or high school you were


attending or did you take these lessons


elsewhere?
 

~	 , [] Elementary/high school
 

2 [] Elsewhere
 

3 [] Both
 

Page 
1992 Survey of Public Participation in the Arts I 87 

Refer to item 40b 

If box 4 is marked in item 40b, ASK item 40d. 

If not - Is box 2 or 3 marked in item 40b AND 

the respondent is under 25 years old? -­

i-’] No - Skip to item 41a 

[]Yes - Ask item 40d 

40d.Did you take any of these lessons or classes in the past year? 

~ ~[qNo
 

2[]Yes
 

41a.(Have you EVER taken lessons or classes) in 

ballet? 

~	 ~ [] No - Skip to item 42a
 

2[~Yes
 

h. Did you take these lessons when you were -

Read categories. (Do not read category 4 if respondent is under 25 years o/d.) 

Mark (X) a// that app/y. 

~	 1 [] Less than 12 years old
 

2[] 12-17 years old
 

3[] 18-24 years old
 

4 [] 25 or older
 

Refer to item 41b 

Is box 1 or 2 marked in item 41b? 

[]No - Skip to Check Item H 

l--lYes - Ask item 41c 

41 c. Were these lessons or classes offered by the 

elementary or high school you were

attending or did you take these lessons

elsewhere? 

~	 ~ [] Elementary/high school
 

2 [] Elsewhere
 

3 [] Both
 

Refer to item 41b
 

If box 4 is marked in item 41b, ASK item 41d.
 

If not- Is box 2 or 3 marked in item 41b AND
 

the respondent is under 25 years old?
 

[] No - Skip to item 42a
 

[--IYes - Ask item 41d
 

41d. Did you take any of these lessons or classes


in the past year?
 

~ lr~No 

~[]Yes 

42a.(Have you EVER taken lessons or classes) in
 

dance, other than ballet such as modern, folk
 or tap? 

~	 ~ [] No - Skip to item 43a 2rq Yes 

b.Did you take these lessons when you were -

Read categories. (Do not read category 4 if respondent is under 25 years old.)

Mark (X) all that apply, 

~ ~ [] Less than 12 years old 

~÷,,- 2r~12-17 years old
 

31-318-24 years old
 

4r~25 or older
 

Refer to item 42b 

Is box 1 or 2 marked in item 42b? 

[]No - Skip to Check Item J 

[]Yes - Ask item 42c 

Page 6 

42c. Were these lessons or classes offered by the 

elementary or high school you were

attending or did you take these lessons

elsewhere? 

~	 ~[]Elementary/high school
 

2 [] Elsewhere
 

3 [] Both
 

Refer to item 42b 

If box 4 is marked in item 42b, ASK item 42d. 

If not - Is box 2 or 3 marked in item 42b AND 

the respondent is under 25 years old? 

[] No - Skip to item 43a 

I-’]Yes - Ask item 42d 

42d.Did you take any of these lessons or classes 

in the past year? 

,[]No
 

2F3Yes
 

43a.Have you EVER taken lessons or classes in
 

creative writing?
 

~	 ~ [] NO - Skip to item 44a
 

2[]Yes
 

b. Did you take these lessons when you were -

Read categories. (Do not read category 4 if respondent is under 25 years old,) 

Mark (X) all that apply. 

~	 ~ [] Less than 12 years old 

2[]12-17 years old
 

31~18-24 years old
 

4[]25 or older
 

Refer to item 43b 

Is box 1 or 2 marked in item 43b? 

[] No - Skip to Check Item L 

[]Yes - Ask item 43c 

43c.Were these lessons or classes offered by the elementary or high school you were

attending or did you take these lessons 

elsewhere? 

~[] Elementary/high school
 

2[] Elsewhere
 

3[] Both
 

Refer to item 43b 

If box 4 is marked in item 43b, ASK item 43d. 

If not - is box 2 or 3 marked in item 43b AND 

the respondent is under 25 years old? 

[] No - Skip to item 44a 

[]Yes - Ask item 43d 

43d.Did you take any of these lessons or classes
 in the past year?
 

~]Yes 

44a.(Have you EVER taken a class) in art
 

appreciation or art history?
 

~[]No - Skip to item 45a
 

2[]Yes
 

b.Did you take this class when you were -

Read categories. (Do not read category 4 if respondent is under 25 years old.)

Mark (X) a/I that apply. 

~	 ~[]Less than 12 years old 

2[]12-17 years old
 

3 [] 18-24 years old
 

~[]25 or older
 
88 I Turning On and Tuning In 

Refer to item 44b 

Is box 1 or 2 marked in item 44b? 

[] No - Skip to Check Item N 

[]Yes - Ask item 44c 

44c.Was this class offered by the elementary or
 

high school you were attending or did you


take this class elsewhere?
 

~	 1[]Elementary/high school 

2 [] Elsewhere 

3 [] Both 

Refer to item 44b 

If box 4 is marked in item 44b, ASK item 44d. 

If not - Is box 2 or 3 marked in item 44b AN~D the respondent is under 25 years old? 

[]No - Skip to item 45a 

[]Yes - Ask item 44d 

44d.Did you take any of these lessons or classes
 

in the past year?
 

45a.(Have you EVER taken a class) in music
 appreciation?
 

~	 1 r~No - Skip to item 46a 

2r~Yes 

b.Did you take this class when you were -

Read categories. (Do not read category 4 if 

respondent is under 25 years old.)

Mark (X) all that apply. 

1[]Less than 12 years old
 

2012-17 years old
 

3[] 18-24 years old
 

41~25 or older 

Refer to item 45b 

Is box 1 or 2 marked in item 45b? 

[] No - Skip to Check Item P 

r~Yes - Ask item 45c 

Notes 

45c.Was this class offered by the elementary or
 

high school you were attending or did you


take this class elsewhere?
 

1[] Elementary/high school
 

2[] Elsewhere
 

3[] Both
 

Refer to item 45b 

If box 4 is marked in item 45b, ASK item 45d. 

If not - Is box 2 or 3 marked in item 45b AN._._~D 

the respondent is under 25 years old? 

[]No - Skip to item 46a 

[]Yes - Ask item 45d 

45d.Did you take this class in the past year? 

20Yes 

46a. What is the highest grade (or year) of regular


school your FATHER completed?
 

~3"~Ol[]7th grade or less 

o2[]Sth grade
 

o3[] 9th-1 lth grades
 

o4[] 12th grade
 

os[]College (did not complete)
 

o6[]Completed college (4+ years)
 

oT[]Post graduate degree (M.A., Ph.D., M.D., J.D., etc.
 

o80 Don’t know
 

b. What is the highest grade (or year) of regular

school your MOTHER completed? 

~ 0~ []7th grade or less 

o2[]8th grade
 

o3[]9th-1 lth grades
 

o4 [] 12th grade
 

os[]College (did not complete)
 

o6[]Completed college (4+ years)
 

OT[]Post graduate degree (M.A., Ph.D., MD., J.D., etc. 

o~ [] Don’t know 

Is this the LAST household member to be 

interviewed? 

~]No - Go back to the NCS-1 and interview the 

next eligible NCS household member 

OYes - END INTERVIEW 

Page 
Appendix B: 

Technical Discussion 

of Logistic Regression 

L ogistic regression is useful in explaining why an event occurs or in predicting 

whether or not an event will occur, e.g. whether or not a person watches 

televised symphony concerts. The response alternatives in this case are "yes" or 

"no." The usual multiple regression model is written in linear form as 

In such a case, the dependent variable, Y, is ordinarily a continuous variable, 

and certain additional conditions must be met to have fullest confidence in the 

utility of the model.22 

When the dependent variable takes only two values, as is often the case in 

survey data, the linear regression model fails, and an alternative model is 

required.23 The logistic regression model is one such alternative, and it can be 

written as 

Prob (event) ­ l+e~ 

or 

1 Prob (event) ­ l+e-z 

where Zis the linear combination 

z= 130 + ~31x~ + 132x2 +... + 13~n 

for n explanatory variables. 

An alternative and equivalent expression is 

Prob (event) 

log ( Prob (no event)) = Z 

89
 
90 I Turning On and Tuning In 

which is the log of the odds. The dependent variable, Z, may be attendance at 

a classical music concert, with a "yes" response coded as 1 and "no" as 0. One 

explanatoryvariable, sayX1, may be gender, with "male" coded as 1 and "female" 

as 0, and another, say X2, may be household income, measured in dollars. A 

positive value of 91 would indicate higher attendance by males than females, 

and a positive value of 92 would indicate higher participation by higher income 

families, as compared with lower income families. In logistic regression, the 

model parameters 90) are estimated using the maximum-likelihood method. 

For large sample sizes, the test that a coefficient is 0 (i.e., that an explanatory 

variable has no influence) is based on the Wald statistic, which has a chi-square 

distribution.24 The goodness of fit of the model can be assessed by a variety of 

indicators. Those used in this monograph are the log-likelihood, which compares the statistical results to a "perfect" model, the model chi-square, which 

tests the hypothesis that the included variables jointly are significant, and the 

percent of cases correctly classified by the model. 
Notes
 

1. The three commonly recognized types of market failure are monopoly power, 

positive or negative "externalities" (e.g., pollution), and collective goods (e.g., 

national defense). Broadcasting media are an example of the last of these; the arts 

in general are said to have characteristics of positive externalities. For a more 

complete discussion, see James Heilbrun and Charles M. Gray, The Economics of 

Art and Culture (New York: Cambridge University Press, 1993), especially chapter 11. 

2. See Jack Faucett and Associates, Arts Participation in America: 1982-1992, National Endowment for the Arts Research Division Report #27, 1993, Appendix 

C.4. 

3. A third, intermediate survey was conducted in 1985. Preliminary analyses of that 

data indicate that they offer insufficient new information to merit analysis. The 

trend patterns are inferior to those offered by the 1982 results, and the 1992 survey 

offers a superior account of current patterns. All three are included in Arts 

Participation in America: 1982-1992, Research Division Report #27, National 

Endowment for the Arts (October 1993). 

4. See the discussion in James Heilbrun and Charles M. Gray, The Economics of Art 

and Gulture: An American Perspective (Cambridge: Cambridge University Press, 

1993), chapter 16. 

5. For a lively and entertaining account of the early history of cultural programming 

on commercial television, see Brian G. Rose, Television and the Performing Arts 

(Westport, CT: Greenwood Press, 1986). For an account of programming supported by the National Endowment for the Arts, see NEA, TheArts on Television, 

197~-1990, compiled by Rebeccah Krafft (Washington, DC: U.S. Government 

Printing Office, 1991). 

6. For a more extensive discussion of these points, see James Heilbrun and Charles 

M. Gray, The Economics of Art and Culture: An American Perspective (Cambridge: 

Cambridge University Press, 1993), pp. 199-216, and the citations therein. 

7. In the broadcast case, we can think of a supply curve that is horizontal ("perfectly 

elastic") at a zero price. 

8. For a general discussion, see James Heilbrun and Charles M. Gray, The Economics 

of Art and Culture: An American Perspective (Cambridge: Cambridge University 

Press, 1993), pp. 302-306. Two studies by James Heilbrun offer additional 

insights. See his "Growth and Geographic Distribution of the Arts in the U.S.," in 

Douglas V. Shaw et al., eds., Artists and Cultural Consumers (Akron: Association 

for Cultural Economics, 1987), pp. 24-36, and "The Distribution of Arts Activity 

Among U.S. Metropolitan Areas," in Douglas V. Shaw et al., eds., Cultural 

Economics, 88: An American Perspective (Akron: Association for Cultural Economics, 1989), pp. 33-40. 

91
 
92 I Turning On and Tuning In 

9. This is due largely to Tibor Scitovsky, The Joyless Economy (Oxford University 

Press, 1976), ch. 11, "Our Disdain for Culture," pp. 224-247. 

10.	 We should note that the survey instrument asks about "listening" to a recording, 

not "buying" one. Yet someonemust have purchased a CD or other sound recording, 

and it seems reasonable to assume that the respondent may, in fact, have been the 

purchaser. Hence we treat listening as roughly synonymous with purchasing for 

purposes of hypothesis development. 

11. U.S. Bureau of the Census, StatisticalAbstract ofthe United States: 1993 (Washington, DC: U.S. Government Printing Office, 1993), Table 901, p. 561.
 

12. Ibid. 

13. A technical discussion of econometric techniques, including regression, is far 

beyond the scope of this monograph. The interested reader can pursue any of a 

number of elementary treatments, including Peter Kennedy, A Guide to Econometrics, 3rd. ed. (Cambridge, MA: MIT Press, 1993). A brief exposition of the 

technique used here is included in Appendix B. 

14. Perhaps the classic reference is G. S. Maddala, Limited-Dependent and Qualitative
 

Variables in Econometrics (Cambridge: Cambridge University Press, 1983). See also
 

Marija J. Norusis, SPSS Advanced Statistics User’s Guide (Chicago: SPSS Inc.,
 

1990), pp. 45-69.
 

15. Technically, substitutability and complementarity would be indicated by the signs 

of estimated cross-price elasticity of participation. The data do not support such 

determination in this case. 

16.	 Ideally, tests of equality of coefficients would inform hypotheses pertaining to 

changes in behavior and/or structure over time. Such tests would not be wholly 

applicable in this instance because of changes in the survey instrument (e.g., 

"dance," more broadly defined, replacing "ballet") and variable measures (e.g., 

incomparability of income groupings due to inflation and category changes). 

17. As has been suggested earlier, inclusion of media participation indicators as 

explanatory variables in the live participation equation, and vice versa, would yield 

information on cross-participation. Unfortunately, such inclusion also creates 

econometric difficulties, the correction of which requires simultaneous estimation 

techniques. Accordingly, what is reported in the tables that follow are the simpler 

results. A more technical treatment of this issue, beyond the scope of this monograph, will be forthcoming as a research note. 

18. For a more complete description of the Wald statistic, see Marija J. Norusis, SPSS
 

Advanced Statistics User’s Guide (Chicago: SPSS Inc., 1990), p. 48.
 

19. For a more complete description of these tests and indicators, see Ibid., pp. 50-53. 

20. See Joni Maya Cherbo and Monnie Peters, American Participation in Opera and
 

Musical Theater--1992, National Endowment for the Arts Research Division
 

Report #32.
 

21. TheblockbusterphenomenonisdiscussedinJames HeilbrunandCharlesM. Gray, 

The Economics of Art and Culture (New York: Cambridge University Press, 1992), 

pp. 185-187. 

22. See any standard econometrics textbook, e.g. Robert S. Pinduyck and Daniel L.
 

Rubinfeld, Econometric Models and Economic Forecasts, 3rd ed. (New York:
 

McGraw-Hill, Inc., 1991).
 
Notes I 93 

23.	 Ibid., ch. 10, "Models of Qualitative Choice." 

24.	 For a more complete discussion, see Marija J. Norusis, SPSS Advanced Statistics 

User’s Guide (Chicago: SPSS, Inc., 1990), especially pp. 48-51. 
Bibliography 

Arts and Cultural Programs on Radio and Television. Research Division Report 

#4. Washington, DC: National Endowment for the Arts, 1977. 

TheArts on Television, 1976-1990. Compiled by Rebeccah Krafft. Washington,
 

DC: National Endowment for the Arts, 1991.
 

Beck, Kirsten. Cultivating the Wasteland. New York: American Council for the 

Arts, 1983. 

Cornwell, Terri Lynn. Democracy and the Arts: The Role of Participation. New 

York: Praeger, 1990. 

Heilbrun, James, and Charles M. Gray. The Economics of Art and Culture: An 

American Perspective. New York: Cambridge University Press, 1993. 

Jack Faucett Associates. Arts Participation in America: 1982-1992. Compiled 

by John P. Robinson. Research Division Report #27. Washington, DC: 

National Endowment for the Arts, 1993. 

Kubey, Robert, and Mihaly Csikszentmihalyi. Television and the Quality of Life: 

How 1⁄2"ewing Shapes Everyday Experience. Hillsdale, NJ: Lawrence Erlbaum 

Associates, 1990. 

Lynes, Russell. The Lively Audience. New York: Harper and Row, 1985. 

Maddala, G. S. Limited-Dependent and Qualitative Variables in Econometrics. 

Cambridge: Cambridge University Press, 1983. 

Rose, Brian G. Television andthe Performing Arts. New York: Greenwood Press,
 

1986.
 

Waterman, David. "Arts and Cultural Programming on Cable Television: 

Economic Analysis of the U.S. Experience," in Economic Efficiency and the 

Pe~armingArts. Edited by Nancy K. Grant et al. Akron, OH: Association 

for Cultural Economics, 1987. 

94 
About the Author 

Charles M. Gray is Professor of Economics in the Graduate School of 

Business at the University of St. Thomas (Minnesota). In addition to 

numerous articles and book chapters on various aspects of the economics of the 

arts, he has authored (with James Heilbrun) The Economics of Art and Culture: 

An American Perspective (Cambridge University Press, 1993). He is an active 

member of the Association for Cultural Economics, International. He has 

chaired the board of a small dance company and regularly consults and conducts 

management training seminars for nonprofit organizations. 
Other Reports on the 1992 SPPA 

The following publications report on various aspects of the 1992 Survey of 

Public Participation in the Arts. Information regarding availability may be 

obtained by writing to the National Endowment for the Arts, Research Division, 

1100 Pennsylvania Avenue, NW, Washington, DC, 20506. 

Age Factors in Arts Participation, Richard A. Peterson and Darren E. Sherkat 

American Participation in Dance, Jack Lemon/Jack Faucett Associates 

American Participation in Opera and Musical Theater--1992, Joni Maya Cherbo 

and Monnie Peters 

American Participation in Theater, Chris Shrum/AMS Planning and Research 

Americans" Personal Participation in the Arts, Monnie Peters and Joni Maya 

Cherbo 

Arts Participation and Race/Ethnici~y, Jeffrey Love and Bramble C. Klipple 

Arts Participation by the Baby Boomers, Judith Huggins Balfe and Rolf 

Meyersohn 

Cross-Over Patterns in Arts Participation, Richard J. Orend and Carol Keegan 

Effects of Education and Arts Education on Americans" Participation in the Arts, 

Louis Bergonzi and Julia Smith 

Hold the Funeral March: The State of Classical Music Appreciation in the U.S., 

Nicholas Zill 

Jazz in America--Who’s Listening?, Scott DeVeaux 

Patterns of Multiple Arts Participation, Jeffrey Love 

Reading in the 1990s: Turning a Page or Closing the Books?, Nicholas Zill 

Socialization in the Arts--1992, Richard J. Orend and Carol Keegan 

96 
NATIONAL 

ENDOWMENT 

FOR~THE 

ISBN 0-929765-39-7


ARTS 

Seven Locks Press 

Carson, California 9