The Audience for 

American Art Museums 
The Audience for
 

American Art Museums
 

J. Mark Davidson Schuster 

Research Division Report # 23
 

National Endowment for the Arts
 

Seven Locks Press
 

Washington
 
 

The Audience for American Art Museums is Report #23 in a series on matters of 

interest to the arts community commissioned by the Research 

Division of the National Endowment for the Arts. 

First printed 1991 

Second printing 1992 

Library of Congress Cataloging-in-Publication Data 

Schuster, J. Mark Davidson, 1950­

The audience for American art museums / J. Mark Davidson Schuster 

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

the Arts ; 23) 

Includes bibliographical references. 

ISBN 0-929765-00~-1 

1. Art museums--United States--Visitors. I. Tire. II. Series: 

Research Division report (National Endowment for the Arts. Research 

Division) ; 23. 

N510.$3 1990 

708.13---dc20 90-20253 

CIP 

Manufactured in the United States of America 

Seven Locks Press 

Washington, D.C. 

1-800-354-5348 
Table of Contents 

Introduction: Who are the Visitors to Art Museums?
 1 

Part I: The Demographics of Participation Rates 4
 

Comparing Participation Rates: The Americans
 

Comparing Participation Rates:
 

and the Arts Studies 10
 

An International Perspective
 12
 

Participation Rates Controlling for "Third" Variables 18
 

Part II: Socialization and Art Museum Attendance
 27 

Part III: Unsatisfied Demand and Barriers to Attendance
 30
 

Unsatisfied Demand 30
 

Barriers to Attendance
 32 

Part IV: Profiles of the Museum Audience(s)
 37 

Conclusion
 46 

Notes
 47 

Appendix: Results from Three Logit Analyses
 52 

Acknowledgments
 56 

About the Author
 57 
Introduction: Who are the Visitors to Art Museums? 

Until the mid-nineteenth century most museums were founded around private collections, and access was restricted to an audience selected by the 

collector, though few went to such great lengths as Sir Ashton Lever in 1773: 

This is to inform the Publick that being tired out with the insolence 

of the common People, who I have hitherto indulged with a sight 

of my museum (at Alkrington), I am now come to the resolution 

of refusing admittance to the lower class except they come 

provided with a ticket from some Gentleman or Lady of my 

acquaintance. And I hereby authorize every friend of mine to give 

a ticket to any orderly Man to bring in eleven Persons, besides 

himself, whose behavior he must be answerable for, according to 

the directions he will receive before they are admitted. They will 

not be admitted during the time of Gentlemen and Ladies being in 

the Museum. If it happens to be inconvenient when they bring their 

ticket, they must submit to go back and come some other day, 

admittance in the morning only from eight o’clock till twelve.1 

In the late eighteenth century, people who wished to visit the British 

Museum had to present their credentials at the office and await word, 

sometimes for months, as to whether they would receive an admission ticket.2 

And it was not until 1960 that the Barnes Foundation in Philadelphia was 

forced, in exchange for its status as a tax-free institution, to open its doors to 

the general public, though admissions were still limited to 400 per week.3 

In the nineteenth century, particularly in the United States, the distinction 

between private and public museums began to fade. The motivation for 

establishing a museum became not so much the need to house a collection 

as the desire to provide an opportunity for the general edification of the 

public. 

In the last decade, with the rise of both public and private nonprofit 

funding mechanisms that take a large part of their mandate to be increasing 

the breadth of exposure of Americans to the arts, overall attendance figures 

have become increasingly important for two reasons. First, museums are 

finding that carefully documenting audience size helps them to make a more 

persuasive case to government and private funders, whether or not they 

actually consider broadening the range of their audience as one of their 

primary goals. Second, museums need the revenue that comes from increased 

attendance. 
J. Mark Davidson Schuster 

At the same time, more and more museums are becoming concerned with 

the fine-grained detail of who attends art museums and who does not. For 

these museums an understanding of their audience is a critical point of 

departure for a wide variety of management decisions. Once a museum has 

a profile of its audience, it can compare that profile with other demographic 

profiles to help answer a number of interesting policy questions. Some of the 

databases a museum might wish to use, along with the policy questions that 

might be answered by such comparisons, are summarized on the next page. 

Accordingly, this study constructs a series of profiles of the American 

audience for art museums and galleries, and outlines a number of the 

methodological issues that are involved in constructing such profiles. 

There is a longer tradition of audience studies among art museums than 

perhaps among any other type of arts institution. Evidence from a number of 

museum audience studies, along with studies from the performing arts, was 

brought together for the first time in 1977 by DiMaggio, Useem and Brown.4 

Carefully aggregating the results of these diverse studies, DiMaggio et al. 

summarized the demographic composition of the public for the arts in the 

United States: 

 ̄	 The audience for the arts was more highly educated, was of higher 

occupational status, and had a higher income than the population as 

a whole. 

 ̄ Women were slightly overrepresented in the arts audience.

 ̄ The median age of the arts audience was close to the median age of 

the population at large but varied widely from audience to audience. 

 ̄ Minorities were present in proportions smaller than their share of 

relevant metropolitan populations. 

And, with respect to the public for museums: 

 ̄	 Museum visitor populations were somewhat more representative 

of the American public than were the performing arts audiences 

surveyed. 

 ̄	 The museum surveys found smaller proportions of professionals and 

the well educated, and lower median incomes than did studies of 

performing arts audiences. 

 ̄	 The art museum visitor population was better educated, wealthier, 

older, and composed of more professionals than visitors to history, 

science, or other museums.5 
Audience Profiles as Data Bases
 

for Answering Policy Questions
 

Audience Profiles Policy Questions 

The profile of the overall audience for 

art museums as reflected in SPPA ’85 

or in similar studies. 

The profile of the overall population 

or of the population in the museum’s 

The profile of the museum’s target 

population. 

The suaff’s impression of what the 

museum’s audience profile is 

currently. 

The audience profile of other similar 

museums. 

The audience profile of other nearby 

"attractions." 

Changes in the museum’s audience 

profile over time. 

What portions of the population is the 

museum serving as compared to 

museums on average? 

What segments of the population are 

underrepresented in the museum’s 

audience? 

Is the museum serving the segments 

of the population to which it has 

targeted its activities? 

How well does the museum staff 

understand the composition of the 

current audience? 

Is the programming promoted by the 

staff meeting the needs of the actual 

audience? 

How does the museum’s experience 

compare to that of sister museums? 

Is the museum more successful or less 

successful than other museums at 

attracting particular groups to the 

museum? 

What are the other local educational 

and leisure opportunities that 

compete for the audience? 

To what extent is the museum 

attracting an audience that is different 

from the audience attracted by others? 

Is the museum competing for the 

same audience? 

How has the audience profile 

changed? 

Has it changed because of things that 

the museum has done differently or 

because of external factors? 

Has it changed in ways in which the 

museum would like its audience to 

change? 

3 
J. Mark Davidson Schuster 

These results were not terribly surprising; they reinforced widely held 

views on the composition of the arts audience. Yet, because these results are 

based on a wide variety of studies that are not inherently comparable, they 

are, at best, only suggestive of the audience profile of art museums. What 

might an extensive, careful, cross-sectional survey of the entire American 

adult population reveal about visitors to art museums? 

In this study, the Survey of Public Participation in the Arts (SPPA) is 

used to explore the composition of the audience for art museums and art 

galleries in the United States. Sponsored by the National Endowment for the 

Arts and conducted by the U.S. Bureau of the Census in collaboration with 

the University of Maryland, the SPPA is the first major attempt to collect 

coherent data on arts attendance and participation across the entire adult 

population of the United States. The SPPA was first undertaken in 1982 and 

repeated in 1985. This work relies on data from the 1985 SPPA, in which a 

probability sample of the American adult population was taken and 13,675 

adults were interviewed between January and June 1985. Because of the scale 

of this survey and the care with which it was taken, its data present an 

important opportunity to explore a variety of interesting questions concerning the participation of American adults in artistic activities. 

Part I: The Demographics of Participation Rates 

When asked if they had visited an art museum or art gallery in the twelve 

months preceeding their 1985 SPPA interview, 22 percent of the adult 

American population said that they had. Two out of every nine adults? 

This over~.ll participation rate is a convenient base of comparison for 

determining which subgroups of the population are more likely to be 

museumgoers and which are less likely. Table 1 summarizes participation 

rates across a variety of demographic variables, both in raw terms and as 

percentages. The results for these variables are discussed below. 

tCare must be taken in interpreting these numbers. First, the key attendance question grouped 

art museums and art galleries together, but there is considerable variation in the use of the 

phrase "art gallery." In some places it refers only to shops selling art works, in others to "art 

museums." If everyone who shopped in a gallery also attended a museum in the preceeding 

year, then there is likely to be little bias; if not, there is a bias whose aggregate effect is 

unknown. Second, the data are based on recollections of activities over the previous twelve 

months, recollections that might not be entirely accurate. While these caveats may limit 

one’s confidence in the absolute numbers, they do not necessarily affect relative 

demographic comparisons. 

4 
The Audience for American Art Museums 

Presenting the findings as the raw number per 1,000 adults is necessary 

because of the fundamental difference between the size of a percentage and 

the size of the population base to which the percentage is to be applied. A 

small percentage applied to a large base can still represent a large number of 

people. For example, the SPPA data show that while 58 percent of attenders 

would like to attend art museums more often, only 23 percent of non-attenders 

would like to attend. Yet, out of every 1,000 adults, 307 would like to attend 

more often and 179 of them --well over half---are currently non-attenders.6 

Income." As income rises the participation rate rises, from 11 percent of 

those with incomes between $5,000 and $10,000 to 45 percent of those with 

incomes greater than $50,000. Thus, differences in income levels are particularly helpful in explaining the relative likelihood of attendance. Comparing these figures with those per 1,000 adults, however, reveals that although 

the participation rate is highest in the highest income group, more than a third 

of the art museum audience actually comes from the $25,000-$49,999 

income group, the largest income group in the adult population. 

There is one exception to the general increase in the probability of 

attendance with increases in income: a decrease from 16 percent to 11 percent 

between the lowest and the next-lowest income categories. An important 

component of this seeming anomaly is the fact that adults who are currently 

students are disproportionately in the lowest income group, yet their attendance pattern differs markedly from the non-students in the same income 

group. However, the overall pattern is quite clear: Adults who are currently 

students are much more likely to be attenders than are other adults. 

Education." Educational level is clearly correlated with participation rate. 

The rate rises from a low of 4 percent of adults with a grade school education 

to a high of 55 percent of adults with some graduate school education, a 

difference of 51 percentage points. This difference makes education the most 

important predictive variable in this list of demographic variables. (For 

income, the corresponding difference is 29 percentage points.) However, the 

raw figures in Table 1 show that well over half the audience completed less 

than a full college education. Again, this is because of the relative size of 

these groups in the adult population. 

To understand the full effect of education on participation rates, separating students from non-students is once again important. While understandably there are very few current adult students in the first three education 

categories (grade school, some high school, and high school graduate), there 

are a number who are enrolled in college, and their participation rates are 

5 
Table 1
 

Attendance at Art Museums and Art Galleries, 1985
 

Question: During the last 12 months, did you visit an art gallery or art museum? 

Per 1,000 Adults 

Participation Number 

Rate Attending 

Number 

in Category 

Overall 

Of all adults 22% 219 1,000 

Income 

Of adults whose 

family income was 

$4,999 or less 

$5,000-$9,999 

$10,000-$14,999 

$15,000-$ 24,999 

$25,000-$49,999 

$50,000 or more 

16% 

11% 

15% 

19 % 

28% 

45% 

13 

14 

21 

47 

85 

42 

222 

82 

126 

143 

247 

308 

94 

1,000 

Education 

Of adults whose 

highest education 

level was 

Grade School 

Some High School 

High School Grad 

Some College 

Four-year College Grad 

Graduate School 

4% 

71% 

14% 

29% 

45% 

55% 

4 

8 

53 

60 

50 

45 

110 

118 

376 

203 

110 

82 

220 1,000 

Age 

Adults whose 

age was 

18-24 years 

25-34 years 

35-44 years 

45-54 years 

55-64 years 

65-74 years 

75+ years 

22% 

25% 

26% 

23% 

18% 

16% 

10% 

35 

61 

48 

30 

24 

16 

6 

220 

161 

238 

182 

132 

130 

97 

59 

1,000 

Gender 

Of adult Female 

Male 

23 % 

21% 

121 

99 

528 

472 

220 1,000 

Race 

Of adults Black 

White 

Other 

11% 

23% 

26% 

12 

203 

5 

108 

873 

19 

220 1,000 

Urbanization 

Adults who 

lived in 

SMSAt and in Central City 

SMSA but not Central City 

Area outside an SMSA 

25% 

26% 

14% 

69 

107 

44 

271 

413 

316 

220 1,000 
Region 

Of adults who 

lived in the 

Subregion 

Of adults who 

lived in 

Selected States* 

Of adults who 

lived in 

£’elected Occupations 

Of adults whose 

occupation was 

classified 

Table 1 (Continued)
 

Northeast 

Midwest 

South 

West 

New England 

Mid Atlantic 

East Northcentral 

West Northcentral 

South Atlantic 

East Southcentral 

West Southcentral 

Mountain 

Pacific 

California 

Florida 

Georgia 

Illinois 

Indiana 

Massachusetts 

Michigan 

New Jersey 

New York 

Ohio 

Pennsylvania 

Texas 

Virginia 

North Carolina 

Professional 

Managerial 

S ales/Clerical 

Craftsman 

Operatives 

Laborers 

Service Workers 

Per 1,000 Adults 

Participation Number Number 

Rate Attending in Category 

20% 42 209 

21% 53 252 

19% 64 344 

31% 60 195 

219 1,000 

2‘1% 13 54 

19% 29 155 

20% 37 182 

23 % 16 70 

19% 35 180 

11% 7 66 

23% 23 98 

28% 13 46 

32% 47 149 

220 1,000 

32% 36 114 

20% 9 46 

17% 5 29 

23% 11 48 

23% 5 22 

25% 6 24 

21% 9 43 

16% 5 31 

21% 16 75 

14% 7 50 

14% 7 49 

26% 17 64 

30% 8 27 

13% ‘1 32 

49% 44 89 

37% 32 85 

27% 64 2,10 

1‘1% 13 91 

10% 7 73 

10% 8 80 

16% 17 108 

Source." "Survey of Public Participation in the Arts," 1985.
 

Notes: The number who attended per 1,000 adults varies slightly across variables because
 

of missing values and rounding errors.
 

+SMSA stands for Standard Metropolitan Statistical Area.
 

*These are the only states for which the U.S. Bureau of the Census has prepared separate
 

tabulations.
 

7 
J. Mark Davidson Schuster 

quite high: 38 percent for students with some college education, 37 percent 

for college graduates, and a very high 67 percent for students in graduate 

school. (Tihis last participation rate is one of the highest found in this analysis. 

Yet, with the introduction of additional "third" variables, it is possible that 

this participation rate would become even higher.) As with income, once the 

students are separated out of the adult population, the participation rates by 

education for non-students differ very little from the overall distribution for 

all adults. 

Age: Participation rates are roughly constant (in the low to mid-twenty 

percent range) until age 55 when they begin to tail off. The highest participation rate, 27 percent, occurs in the 35-44 year bracket, perhaps reflecting 

increased attendance among families with children. 

Gender: Women are slightly more likely to attend than are men. Coupled 

with the fact that there are more women in the adult population than men, 

this means that among visitors to art museums, women outnumber men by a 

ratio of 6 to 5. 

Race: Whites are roughly twice as likely to have visited an art museum 

in the previous year as African-Americans. Much of this difference may be 

attributed to differences in education level or income level. On average, other 

racial and ethnic groups have a participation rate that is approximately the 

same as that of whites. 

Geographic Distribution: Adults who lived in a Standard Metropolitan 

Statistical Area (SMSA), a U.S. Census Bureau designation used here as a 

rough indicator of urbanization, had slightly higher than average participation rates whether or not they actually lived in the SMSA’s central city (e.g., 

Boston as opposed to one of its suburbs). Adults who lived outside an SMSA 

had a participation rate that was only two-thirds of the average. Roughly half 

of the audience was made up of individuals who lived in an SMSA but not 

in the central city. 

An analysis of the population by region of the country shows interesting 

variations.7 While the participation rates for the Northeast, Midwest and 

South are all roughly 20 percent, the rate in the West is 31 percent. An 

analysis by subregion shows that New England’s participation rate is somewhat higher than average, but that the Mountain and Pacific states have 

considerably higher participation rates. 

High participation rates in the West are centered in the large metropolitan 

8 
The Audience for American Art Museums 

areas. According to special Census Bureau tabulations for selected metropolitan areas, the highest metropolitan-area participation rates are all in the 

western states: 41 percent in the San Francisco Bay area, 28 percent in the 

Los Angeles area, 38 percent in other central cities in SMSAs in the West, 

and 33 percent outside of the central cities in the same SMSAs. In addition, 

Boston has a participation rate of 26 percent, Baltimore/Washington, D.C. 

26 percent, Chicago 27 percent, and cities in Texas 31 percent. 

The available data for selected states reflect the regional figures in certain 

cases a 32 percent participation rate in California and 27 percent in Massachusetts, for example. But the data also point out some less expected results 

in light of the regional aggregates: 26 percent in Texas and 31 percent in 

Virginia. One wonders if the high participation rate for Virginia is a function 

of the easy accessibility of the national museums in Washington, D.C., to the 

bulk of Virginia’s urban population. 

This, in turn, suggests an important possible explanation for the differences in participation rates for each of the geographic variables. Is the 

variation in participation better explained by the geographic distribution of 

museums than by geographic differences in the population? In other words, 

to what extent is attendance a function of the supply of museums rather than 

of the demand for museums inherent in the demographics of particular 

populations? 

Occupation: Participation rates across this variable range from a low of 

9 percent for operatives (machine operators) to a high of 49 percent for 

professionals. Both the managerial and professional categories show participation rates well above the overall average. But because both categories 

also have higher than average incomes and education levels, looking at 

occupation by itself may mask the effect of these other important variables. 

Up to this point, this analysis of the 1985 SPPA data has been a relatively 

straightforward one, based on the demographic variables that are commonly 

cited as important in analyzing audience participation in the arts and across 

which significant differences in participation rates are, in fact, observed. But 

this group of variables has a very interesting common property: they are all 

variables over which neither the individual museum nor any arts funding 

agency has any influence (except, perhaps, by actually moving the museum). 

It is difficult, for example, to imagine the museum that would be in a 

position to increase the level of formal education or income of its potential 

audience in order to increase the local participation rate. We are left with the 

impression that potential visitors are prisoners of their own demographics or 

9 
that museums are prisoners of the demographics of their potential local 

audiences.. While this may in a sense be true in the aggregate, it does not help 

the individual decisions made by potential visitors in choosing whether or 

not to attend a museum. 

To be sure, a demographic analysis will help to document that the 

audience is much larger than had been hoped or smaller than had been feared, 

or that particular segments of the population are not being reached as much 

as the museum might like. But its usefulness in suggesting how a museum 

can go about changing its audience demographics is limited. It can indicate 

if the overall demographics of the audience have changed over time, but 

attributing those changes to specific interventions is difficult. Change in 

audience composition is a slow, resistant process. A demographic analysis 

of the audience is descriptive rather than prescriptive, and one should resist 

the temptation to conclude that one knows more than one actually does about 

audience behavior and motivations when armed with these demographic 

results. 

Comparing Participation Rates: 

The Americans and the Arts Studies 

In 1973, 1975, 1980, 1984, and 1987 the National Research Center of 

the Arts, an affiliate of Louis Harris and Associates, conducted theArnericans 

and the Arts studies.8 These studies have received much visibility within the 

arts advocacy community, particularly for their high estimates of attendance 

at, and support for, artistic activities. How do their results compare with those 

from the SPPA? 

Table 2 presents a comparison of the key participation rates calculated 

in the 1985 SPPA and the 1984 Harris study. Harris reports an overall art 

museum participation rate of 58 percent, just slightly more than five adults 

in nine, which is two and a half times the 1985 SPPA participation rate. Art 

museums and the theatre are the two sectors that show the greatest discrepancy between studies: 36 percentage points in the case of museums (a 

58 percent participation rate in Harris versus 22 percent in the SPPA) and 

37 percentage points for theatre (a 60 percent participation rate in Harris 

versus 23 percent in the SPPA). Moreover, when the two studies’ participation rates are compared for each separate educational level, the discrepancies are very large at each level (27% v. 4% at the lowest reported levels). 

What accounts for these large discrepancies? 

John P. Robinson and his colleagues have carefully compared SPPA 

10 
The Audience for American Art Museums 

results with the Harris figures.9 They point to several factors that help to 

explain part of the difference: 

 ̄ The placement and wording of the questions, in the Harris survey in 

particular, may tempt respondents to give artificially high responses 

so they will not appear to be "uncultured." 

 ̄ In presenting aggregate figures, the Harris underweights the lowest 

educational groups in proportion to their true weight in the population. 

 ̄	 Harris’ use of telephone interviews with quota sampling and a lower 

response rate than the Bureau of the Census achieved in SPPA 

combine to suggest that there may have been selection biases that led 

to respondents who were simply more likely to be attenders than a 

random cross-section of the population. 

From a technical standpoint the SPPA studies are considerably more 

defensible, and, therefore, their results are to be taken more seriously. Moreover, it would be a mistake to focus too much on technique and lose sight of 

common sense. Before the Americans and the Arts series began, the art 

museum world dared not hope that it would one day discover it was already 

reaching a substantial proportion of the adult population each year. When the 

Harris studies suggested this possibility, the results were tin’st treated with 

gratified astonishment and then were gradually incorporated into the established canon of arts policy "knowledge." The SPPA data indicate that the 

initial skepticism had a lot more truth in it than arts advocates eventually came 

to believe. The 58-percent participation rate is simply too high. 

Comparing Participation Rates:

An International Perspective 

Americans seem to have the view that attendance at artistic events is 

much more ingrained in the culture of other countries, particularly in Western 

Europe, than it is in the United States. How do American art museum 

participation rates compare to those in other countries? 

Although cross-national comparison in arts policy is plagued by the wide 

variation in definitions and approaches across both countries and cultures,1° 

the variation in what is considered to be an art museum or an art gallery is 

much smaller than similar variations might be within other artistic sectors. 

Even so, important differences in both surveying procedures and definitions 

of key demographic categories must be taken into account. 

Table 3 compares participation rates from audience studies in Great 

Britain, France, Sweden, and the Canadian province of Quebec to the results 

11 
J. Mark Davidson Schuster 

Table 2
 

A Comparison of Participation Rates:
 

1985 SPPA and 1984 Harris
 

1985 SPPA 

Question: During the last 12 months did 

you visit an art gallery or an art 

museum? 

Overall 22% 

Income 

$4,999 or le:~s 16% 

$5,000-$9,999 11% 

$10,000-$14,999 15 % 

$15,000-$24,999 19% 

$25,000-$49,999 28% 

$50,000 or more 45 % 

Education 

Grade School 4% 

Some High ;School 11% 

High Schooll Grad 14% 

Some College 29% 

Four-year College Grad 45 % 

Graduate School 55% 

Age 

18-24 years 22% 

25-34 years 25% 

35-44 years 27% 

45-54 years 23% 

55-64 years 18% 

65-74 years 16% 

75+ years 10% 

Gender 

Female 23% 

Male 21% 

Race 

Black 11% 

White 23% 

Other 25% 

1984 Harris 

Question: How many times, if any, 

did you visit art museums that exhibit 

paintings, drawings, sculpture, etc., 

during the past 12 months? 

58% Overall 

Income 

43% $7,500 or less 

53 % $7,501 -$15,000 

58% $15,001-$25,000 

62% $25,001-$35,000 

67% $35,001-$50,000 

76% $50,001 or more 

Education 

27% Eighth Grade 

46% High School Grad 

70% Some College 

78% College Grad 

Age 

66% 18-29 years 

62% 30-49 years 

53% 50-64 years 

46% 65+ years 

Gender 

57% Female 

60% Male 

Race 

50% Black 

59% White 

64% Hispanic 

12 
The Audience for American Art Museums 

Table 2 (Continued) 

Urbanization Size of Place 

SMSA Central City 25% 66% Cities 

SMSA not Central City 26% 58% Suburbs 

Outside SMSA 14% 49% Town/Rural 

Sources: "Survey of Public Participation in the Arts," 1985. National Research Center of 

the Arts, Americans and the Arts, 1984. 

from the 1985 S PPA. 11 This comparison shows very similar overall participation rates among these countries, with the exception of Sweden where 

participation is slightly higher: in the United States, 22 percent for art 

museums and art galleries; in Great Britain, 29 percent for all museums and 

19 percent for art exhibitions; in France, 30 percent for all museums (net of 

historic monuments) and 21 percent for temporary art exhibitions; and in 

Quebec, 23 percent for art museums and 17 percent for other museums. In 

Sweden, on the other hand, the participation rate is 31 percent. All of these 

participation rates were measured with respect to attendance in the preceeding twelve months. Where the participation rate is somewhat higher, it 

appears that the difference can be attributed to the broader range of museums 

included in the surveys. 

The similarities across these studies are not limited to overall participation rates. With the exception of some higher participation rates in the 

Swedish study, when the participation rates are disaggregated over various 

demographic variables they remain remarkably similar across the other 

studies. This is particularly true when differences as to which museums are 

being considered are taken into account. 

In many respects the French study most resembles the SPPA surveys; it 

was commissioned to document the participation of the French population 

in a wide variety of leisure and artistic activities. The British survey is more 

akin to the Harris surveys, concerning itself with attitudes towards public 

funding of the arts and correlating those opinions with participation rates and 

demographic factors. (Because of this emphasis, the British study includes 

several variables that are not available in other studies indicating, perhaps, 

the relative politicization of arts policy questions in Great Britain: trade union 

membership, voting intention by political party, support for or opposition to 

public funding of various art forms, and whether or not the respondent had 

heard of the Arts Council of Great Britain.)lz 

13 
Table 3-A
 

A Cross-National Comparison of Participation Rates:
 

The United States and Great Britain
 

United States -- 1985 SPPA Great Britain -- 1981 MORI 

Question: D,’zring the last 12 months did Question." On another subject, which of 

you visit an art gallery or an art these have you personally been to in the 

museum? past 12 months? museum? 

Museum Art Exhibition 

Participation Participation Participation 

Rate Rate Rate 

Overall 22% 29% 19% Overall

Age Age 

18-24 years 22% 21% 17% 18-24 years 

25-34 years 25% 34% 17% 25-34 years 

35-44 years 27% 35% 21% 35-49 years 

45-54 years 23% 

55~34 years 18% 29% 20% 50~M years 

65-74 years 16% 20% 18% 65+ years 

75+ years 10% 

Gender Gender

Female 23% 27% 18% Female
 

Male 21% 31% 20% Male
 

Occupation Class
 

Professional 49% 44% 37% Upper
 

Middle Managerial 37% 39% 27% Lower Middle
 

Sales/Clerical 27% 27% 15% Skilled Manual
 

Craftsman 14% 19% 9% Semiskilled and
 

Operatives 9% Unskilled Manual
 

Laborers 10%
 

Service Workers 16%
 

Subregion Region 

New England 25% 16% 12% Scotland 

Mid Atlantic: 19% 27% 14% North 

East Northcentral 20% 30% 19% Wales/Midlands 

West Northcentral 22% 32% 20% South 

South Atlantic 19% 34% 28% Southeast 

East Southcentral 10% 

West Southcentral 23% 

Mountain 28%
 

Pacific 32%
 

Sources: "Survey of Public Participation in the Arts," 1985. Market and Opinion
 

Research International survey (quota sample of 973 adults age 18+ interviewed at 51
 

points throughout Great Britain. Class is of household head.) conducted for BBC
 

"Panorama," 26 November 1981.
 

14 
Table 3-B
 

A Cross-National Comparison of
 

Participation Rates: France
 

France Pratiques Culturelles des Fran~ais ’81 

Questions." 1) Since December ’ 80, have 2) Since December ’80 you visited a museum? have you visited a 

temporary exhibition of 

painting or sculpture 

Museum Exhibition
 

Participation Participation


Rate Rate
 

Overall 30% 21% 

Education 

No Diploma 14% 7% 

Elementary School Grad 21% 10% 

Certificate 34% 25% 

Bachelor’s Degree or more 57% 49% 

Age
 

15-19 years 40% 26%
 

20-24 years 38% 27%
 

25-39 years 34%
 29% 40-59 years 28% 18% 60-69 years 27% 15% 

70+ years 14% 9% 

Gender
 

Female
 30% 22% Male 30% 21% 

Socio-Professional Category 

Agriculture 17% 8 % Small Merchant!Artisan 32% 26% Wholesale and Industrial 49% 33% Professional and Managerial 61% 53% Middle Class 53% 40% Clerical 32% 28% 

Foreman 24% 18% Laborer or Service Worker 20% 13% 

Urbanization 

Rural 20% 13 % Less than 20,000 residents 26% 19% 20,000-1130,000 residents 28% 21% More than 100,0130 residents 33% 23% Paris 56% 50% Paris Region 47% 36% 

Source." Pratiques Culturelles des Frangais, survey (stratified quota sample of 3,984 

individuals age 15 or over) conducted by ARCmc for the French Ministry of Culture 

(Paris: Dalloz, 1982). 

15 
Table 3-C
 

A Cross-National Comparison of Participation Rates:
 

Sweden
 

Sweden Kulturstatistik 

Percentage of the population age 16-74 years that visited a museum in the previous 12 

months (1982/83) 

Museums and 

Art Exhibitions Exhibitions 

and Art Galleries (Other than Art) 

Participation Participation 

Rate Rate 

Overall 31% 45%

Education 

Pre-Secondary 20% 32% 

Secondary 31% 46% 

Post-Secondary 61% 74% 

Age 

16-24 years 25% 51% 

25-44 years 32% 51% 

45-64 years 35% 41% 

65-74 years 29% 29% 

Gender 

Female 34% 45% 

Male 28% 45% 

Socio-Economic Group 

All Workers 19% 34% 

Unskilled and Semi-Skilled Workers 19% 33% 

Skilled Workers 20% 38% 

All Salaried Employees 48% 59% 

Junior Salaried Employees 38% 47% 

Intermediate Level Salaried Employees 49% 62% 

Senior Salaried Employees 65% 75% 

All Entrepreneurs 29% 37% 

Entrepreneurs Without Employees 32% 41% 

Entrepreneurs With Employees 40% 47% 

Farmers 17% 27% 

Regions 41% 56% 

GOteborg and Malmo 35% 53% 

Other Large Cities and Towns 30% 44% 

Other Southern and Central Sweden 26% 37% 

Northern Densely Populated Areas 31% 45% 

Northern Sparsely Populated Areas 21% 30% 

Stockholm 

Source." Statistics Sweden, "Level of Living Survey 1982/83," as reported in Official 

Statistics of Sweden, Cultural Statistics." Activities, Economy and Cultural ltabits 1980­

1984 (Stockholm: Statistics Sweden, 1987), p. 340. 

16 
Table 3-D
 

ACross-National Comparison of
 

Participation Rates" Quebec
 

Quebec CROP ’83 

Percentage of the population having visited a museum at least once in 1983 

Art Museum Other Museums
 

Participation Participation
 

Rate Rate
 

Overall 23% 17% 

Education 

0-7 years 10% 7% 

8-11 years 17% 14% 

12-15 years 28% 20% 

16+ years 48% 29% 

Income (Canadian $) 

$10,000 or less 13 % 6% 

$10,000-$19,999 24 % 16% 

$20,000-$29,999 25 % 17 % 

$30,000 or more 34% 25% 

Age 

15-17 years 26% 36% 

18-24 years 23% 18% 

25-34 years 27% 16% 

35-44 years 29% 22% 

45-54 years 22% 15% 

55+ years 18% 10% 

Gender 

Female :24% 16%
 

Male
 23% 18% 

Source: Minist~re des Affaires Culturelles du Qudbec, Chiffres a L’Appui, Bulletin du 

Service de la Recherche et de la Planification, Vol. 2, No. 2, May 1984, summary of a 

public opinion poll (sample of 2,316 individuals age 15 or over) conducted by the Centre 

de Recherche sur l’Opinion Publique (CROP) in 1983. 

17 
J. Mark Davidson Schuster 

Both the British and the French surveys separated attendance at "art 

exhibitions" or "temporary exhibitions of painting or sculpture" from more 

general attendance at museums. In order to understand the stable, core 

audience Ibr art museums, it would be necessary to identify and separate out 

those individuals who only attended because of a particular exhibition, 

perhaps a well-advertised "blockbuster" show, and do not normally consider 

themselves part of the museum’s audience. However, the 1985 SPPA data 

do not allow this distinction to be made. 

While far from conclusive, all of these reports taken together suggest that, 

at least in Western countries, museums may well be serving similar segments 

of their national populations. Art galleries, art exhibitions, and art museums 

relate more readily to certain individuals than to others and, indeed, are the 

institutional creation of certain social groups. In large part this receptivity 

seems to be a function of the same demographic factors. The extensive 

Swedish social welfare state, greater citizen involvement in communal 

activity, and a higher educational level may well explain the higher participation rates in Sweden. 

This comparison does not speak, however, to the relative frequency of 

attendance. It is certainly possible that while the cross-section of the population being served is quite similar across countries, the frequency of attendance might be rather different in places where "museum going" has become 

more a part of daily life. But the limited data we have on this question suggest 

that frequency of attendance is not higher in these other countries. Against 

the SPPA mean of 3.42 visits per visitor to art museums, for example, the 

French study reports a mean of 3.113 and the Quebec study a mean of 2.11.14 

Neither the British nor the Swedish studies report any data on frequency of 

attendance. 

Participation Rates: 

Controlling for "Third" Variables 

In order to find better answers to questions about the effect of certain 

demographic variables (e.g., are the high participation rates for upper-income 

groups a function of that income level or of the fact that upper-income 

individuals also tend to be more highly educated?), it is necessary to control 

for and se, parate out the effects of other variables that might confound the 

results. This section discusses the findings of two different methods of 

controlling for these other variables: multiple classification analysis and logit 

analysis. 

18 
The Audience for American Art Museums 

Multiple Classification Analysis 

Multiple classification analysis (MCA) is a mathematical method for 

calculating the net value of variables whose behavior one is trying to 

explain--in this case attendance--for each value of possible key explanatory 

variables--such as various levels of income or education. MCA controls for 

the contribution of other explanatory variables--such as race or marital 

status--by averaging out their effects.15 Conventionally, the variable whose 

behavior one is trying to explain is called the "dependent" variable and the 

various explanatory variables are called the "independent" variables. 

In studying museum attendance patterns, MCA estimates the addtional 

effect of each independent variable on the participation rate. MCA then adds 

(or subtracts) this additional effect to (from) the participation rate to create 

an "adjusted" participation rate. This adjusted rate reflects, as much as is 

mathematically possible, the pure effect of each independent variable on the 

participation rate. In this way, for example, differences in the participation 

rate that result from differences in income alone can be isolated. 

Table 4 summarizes the results of a multiple classification analysis of 

participation rates that considered five primary independent variables--income, education, age, gender, and region--and four other independent 

variables--marital status, number of children, race, and number of hours 

worked per week. The first column reports the participation rates for the main 

independent variables when each is considered by itself (prior to MCA); the 

second column reports the adjusted participation rate for each variable once 

it has been controlled for the other variables through MCA. 

Income." When viewed in isolation, income appeared to be a useful predictor of museum attendance: participation rates ranged from 11 percent to 

45 percent. But when one controls for the influence of the other variables, 

the adjusted participation rate is roughly constant--approximately 20 percent---over the lowest five income groups, and finally jumps to 32 percent 

in the highest income group. This important result indicates that it is too 

simple to say that income is an important predictor of museum attendance; 

it is highly correlated with other variables that are better predictors, particularly education. 

Education: After adjustment, these participation rates are slightly closer 

together than before, ranging from 7 percent for those with a grade school 

education to 54 percent for those with a graduate school education. But the 

remaining 47 percentage point spread indicates that controlling for other 

variables hardly diminishes education’s ability to predict attendance. This 

result reinforces the importance of education as the key demographic predictor of attendance. 

19 
Table 4
 

Comparison of Unadjusted and Adjusted
 

Participation Rates, 1985
 

Question: During the last 12 months did you visit an art gallery or an art museum? 

Overall 

Income 

$4,999 or less 

$5,000-$9,999 

$10,000-$14,999 

$15,000-$24,999 

$25,000-$49,999 

$50,000 or more 

Education 

Grade School 

Some High School 

High School Grad 

Some College 

Four-year College Grad 

Graduate School 

Age 

18-24 years
 

25-34 years
 

35-44 5,ears
 

45-54 3,ears
 

55~:~4 years
 

65-74 years
 

75+ years
 

Gender 

Female 

Male 

Region 

Northeast
 

Midwest
 

South
 

West
 

Part|cipation 

Rate 

22% 

16% 

11% 

15 % 

19% 

28% 

45% 

4% 

8%** 

14% 

29% 

45% 

55% 

22% 

26%** 

27% 

23% 

18% 

17%** 

10% 

23% 

21% 

21%** 

21% 

19% 

31% 

MCA Adjusted*

Participation Rate 

22% 

22% 

19% 

19 % 

20% 

24% 

32% 

7% 

9% 

15 % 

28% 

43% 

54% 

23% 

25% 

24% 

21% 

20% 

21% 

14% 

24% 

20% 

21% 

21% 

21% 

28% 

Source: "Survey of Public Participation in the Arts," 1985. 

Notes: * In this example, multiple classification analysis (MCA) is used to control for 

five main independent variables--income, education, age, gender, and region--and four 

other independent variables--marital status, number of children, race, and number of 

hours worked per week. Each adjusted participation rate separates the effect of one variable by controlling for the effect of the others. 

 ̄ * These rates differ slightly from those in Table 1 because missing values necessitated 

dropping more cases from the analysis. 

2O 
The Audience for American Art Museums 

Age: After adjustment, the effect of age on attendance nearly disappears. 

The adjusted participation rates are fairly constant, from 20 to 25 percent, 

and they do not fall off until more than 75 years of age (14 percent). 

Gender: The adjusted ratio of female to male participation rates is 24:20, 

whereas it was 23:21 before adjustment. Because women live longer and tend 

to have lower educational levels than men, on average, when the effects of 

those variables are removed, it becomes clear that women are even more 

likely to attend, although the difference is not a dramatic one. 

Region: Table 4 shows that before MCA, the West had the nation’s 

highest participation rate (31 percent). But is this high rate due to inherent 

regional differences, or is it due to the fact that incomes are perhaps higher 

in these states, or that educational levels are higher, or that people in the West, 

on average, are younger? Controlling for the other independent variables 

decreases the participation rate in the West by 3 percentage points (to 28 

percent), and raises the participation rate in the South by 3 percentage points, 

to the level of the Northeast and the Midwest (21 percent). 

Of course, one cannot tell from these results alone whether the remaining 

difference (7 percentage points between the West and other regions) is due 

to some inherent "regionalness" or to some other variable that has not yet 

been included in the analysis (such as the geographic distribution of museums). In this sense, the adjusted participation rates should not be thought 

of as the "correct" rates, but as an attempt to isolate the effect of one 

explanatory variable in the context of other, specified explanatory variables. 

The distinction between the one-variable-at-a-time demographic analysis 

in the previous section and multiple classification analysis is a reflection of 

the way in which the analysis will be used. The former emphasizes prediction-what is the probability that someone who lives in the West will be an 

attender?--while the latter emphasizes explanation--How much does living 

in the West contribute, by itself, to the participation rate? How well the MCA 

explains variation in attendance levels when all independent variables are 

used simultaneously can be measured with the R2 statistic,+ which is. 147 

here, indicating that 14.7 percent of the variation in participation rates is 

explained by the independent variables. 

Logff Analysis 

While multiple classification analysis focuses on the average value of the 

dependent variable for each value of each independent variable--explaining, 

K IS a goooness of fit measure of how well a model predicts the variation in the dependent 

variable. Measured on a scale of 0 to 1, the closer R2 is to 1, the better the fit (the better the 

model predicts). 

21 
 

J. Mark Davidson Schuster 

for example, what the participation rate is for high-income individuals while 

controlling: for other independent variables--it is often instructive to consider 

instead the contribution that increases in each independent variable make to 

the dependent variable. For example, to determine the relationship between 

age and attendance, it would be useful to calculate how much the participation rate increases (or decreases) on average for every additional year of age. 

In measuring museum attendance, the underlying dependent variable is 

dichotomous: each person interviewed either attended an art museum in the 

previous year or did not attend, and the individual’s attendance can be 

expressed mathematically with a one (if he or she did attend) or with a zero 

(if he or she did not attend). To test the mathematical relationship between 

this type of dependent variable and a series of independent variables, a 

variation of regression analysis, called logit analysis, is often used. (Logit 

analysis is described further in the Appendix, where the actual mathematical 

results of the logit analyses used in this study are reported.) Logit analysis 

uses the collected data on the attendance pattern of the surveyed individuals 

to predict what the probability of attendance for another individual with a 

particular set of characteristics would be.x6 

Witho~at delving into the intricate mathematics of logit analysis, it is 

possible to present the essential idea with a simple example. Consider two 

variables: whether or not an individual attended an art museum in the 

previous year and that individual’ s number of years of education. Given what 

we already know about the relationship between these two variables, we 

expect that individuals with higher levels of education are more likely to 

attend. Suppose that a sample of 20 individuals revealed that 10 of them had 

attended and that 10 had not. Graphing these two variables for these 20 cases 

might lead to a graph like Figure la. Each square in Figure 1 a represents one 

surveyed individual and plots the number of years of education versus 

whether or not that person attended an art museum in the previous year. 

Figure la. 

Sample Attendance Data Graphed by Years of Education 

Yes = 1 

Attendance 

No = 0 

0 2 4 6 8 10 12 14 16 18 

Years of Education 

22 
 

The Audience for American Art Museums 

Using these data as a starting point, logit analysis fits an "s-shaped" curve 

to the data. The result would look like Figure lb. The curve is a simplified 

mathematical summary of the relationship between the two variables, and its 

shape reflects the fact that individuals with fewer years of education are much 

less likely to have attended an art museum than are individuals with more 

years of education. Note that the vertical axis of Figure lb is labelled 

"Probability of Attendance." Thus, in this example, logit analysis is using 

the actual attendance pattern in the survey data to predict the probability of 

attendance for other individuals whose educational levels are known but 

whose attendance patterns are unknown. The height of the curve can be 

interpreted as either the relative percentage of individuals at each level of 

education who are predicted to attend or the probability that an individual 

with a particular level of education will attend. 

Figure lb 

Logit Curve Fitted to Sample Attendance Data 

Yes- 1 

Probability 

of 0.5 

Attendance 

No =0  ̄  ̄  ̄  ̄  ̄  ̄ 

0 2 4 6 8 10 12 14 16 18 

Years of Education 

Keeping this intuitive understanding in mind, we can now turn to an 

analysis of the actual data. The results summarized here are from a model 

that predicts the probability of museum attendance as a function of income 

level, age, race, gender, educational level, whether the individual lives in a 

Standard Metropolitan Statistical Area or its central city or outside a SMSA, 

and whether or not the individual is a student. (The actual mathematical 

results of running this logit analysis are reported in Table A of the Appendix.) 

It is not necessary to understand the mathematics that lead to logit results 

in order to be able to interpret the key findings. Logit results can be used to 

help us answer three rather straightforward analytical questions concerning 

museum attendance patterns: 

 ̄ Is an increase in each independent variable associated with an increase or a decrease in the participation rate? 

 ̄ How strong is the increase or decrease in each case? Is the increase 

or decrease that is detected in the sample survey data strong enough 

23 
J. Mark Davidson Schuster 

so that one can conclude that the same relationship holds for the entire 

adult population of the United States? 

What do the results tell us about the probability of attendance for 

particular individuals whose demographic characteristics are known? 

Asking these questions of the logit analysis reported in Table A of the 

Appendix leads to a number of interesting results. The signs of six of the 

thirteen independent variables are negative, indicating that there is an inverse 

relationship between these variables and the probability of attendance. The 

negative coefficient of age indicates that as an adult gets older, all else being 

equal, his or her probability of attendance goes down. The signs for Blacks 

and other minority racial groups are also negative, indicating that the probability of attendance for these racial groups is lower than the probability of 

attendance for whites. But the coefficient for "other" minority racial groups 

is not statistically significant, so the evidence is not strong enough to be able 

to conclude that in the overall population minority groups other than Blacks 

have a probability of attendance that is actually different from that of whites. 

The s!igns of the seven other variables are positive. The positive coefficients for the two highest income groups indicate that individuals in these 

groups (incomes of $25,000 and above) have a higher probability of attendance than individuals in lower income groups. The coefficient of education 

is also po:sitive, indicating that for every additional year of formal education, 

the probability of attendance goes up. The positive coefficient of the gender 

variable indicates that the probability of attendance for women is higher than 

the probability for men. And the positive coefficients of the geography 

variables indicate that people who live in Standard Metropolitan Statistical 

Areas (i.e., relatively urbanized areas) are more likely to attend than people 

who live outside of these areas. All of the positive coefficients are statistically 

significant, indicating that these results would be expected to be replicated 

in the population at large. 

A surnmary measure of how well the logit curve actually fits the data is 

R2. For this analysis R2 --- .16; sixteen percent of the variation in the 

dependent variable is explained by the independent variables in this model. 

While the R2 statistics for both the multiple classification analysis and the 

logit analysis seem low, it is important to keep them in mind as benchmarks 

against which further analyses and other studies might be judged. As our 

ability to explain museum attendance improves, the predictive capability of 

our models will increase. The next section of this study, for example, will 

report the results of a better logit model that includes variables that measure 

the degree of an individual’s socialization into the arts. 

24 
The Audience for American Art Museums 

Finally, logit results can be used to predict the probability of attendance 

for particular individuals whose characteristics are known. For example, the 

probability of attendance for a white female who is 40 years old, has 16 years 

of formal education, lives in the central city of an SMSA, has an income 

between $15,000 and $24,999, and is not currently a student is estimated at 

52 percent. The probability is calculated by inserting the actual values of the 

variables for this sample individual into the equation that results from the 

logit analysis. 

These results can also be used to graph the relationship between the 

probability of attendance and each of the independent variables. Figure 2a is 

a graph of the relationship between probability of attendance and educational 

level for the sample female attender; it is the result of letting years of 

education vary while keeping all of the other variables the same as in the 

example above. Overall, the graph shows the probability of attendance rising 

dramatically across levels of education to a high of nearly 78 percent, a 

striking depiction of the importance of education in explaining participation. 

The specific example calculated above occurs on the right hand side of Figure 

2a at the point where education is equal to 16 years and the probability of 

attendance equals 52 percent. 

Similarly, Figure 2b fixes all of the independent variables except age to 

their values for the sample individual in order to graph the relationship 

between probability of attendance and age. This graph shows that once the 

other independent variables have been controlled for, the probability of 

attendance tends to decline slightly as age increases. 

In summary, using logit analysis affords a different view of the data; it 

focuses on the contribution that each independent variable makes to the 

probability of attendance and leads to a precise measurement of that contribution. For most purposes, however, the most important contribution this 

analysis makes to an understanding of these relationships is what it tells us 

about the direction and the strength of these relationships. And the availability of the SPPA data allow researchers in the field to explore these 

questions for the first time. 

25
 
 

 

J. Mark Davidson Schuster 

Figure 2a 

Logit Analysis--Graph of the Probability of Attendance 

by Education for Sample Individual 

0.9 

0.8 

o.~ 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0’o 6 8 10 12 14 16 18 

Years of Education 

Figure 2b 

Logit Analysis--Graph of the Probability of Attendance 

by Age for Sample Individual 

1 

0.9 

0.8 

0.7 

0.6 

0.5 

0.4 

O.3 

0.2 

0.1 

0 10 30 50 70 90
 

Age
 

26 
The Audience for American Art Museums 

Part I1: Socialization and Art Museum Attendance 

The fact that the model presented in Part I had such a low ability to predict 

the probability of attendance suggests that there must be factors in an 

individual’s background other than simple demographics that help explain 

attendance at art museums. One place to look for additional explanatory 

variables is to the possible role played by socialization activities such as art 

lessons. 

This section focuses on three SPPA socialization questions that are most 

likely to be linked to attendance at art museums: whether or not, and at what 

ages, the respondent had ever taken lessons in the visual arts; whether or not, 

and at what ages, the respondent had taken art appreciation classes; and 

whether or not, and the frequency with which, parents had taken the respondent to art museums. 

An analysis of these questions reveals that all three of these factors show 

a strong relationship with increased attendance (Table 5). The overall 

attendance rate of 22 percent rises to 45 percent for those who had taken 

visual arts lessons. For those who had not taken these lessons, the participation rate is only 15 percent. The pool of visitors to art museums during the 

previous year is divided approximately in half between those who have 

taken art lessons and those who have not. Having taken a class in art 

appreciation or art history raises the participation rate to 51 percent, but 

among visitors the ratio of those who had not taken a class to those who had 

is 5:4. Yet, actual museum visitors are split in half between those who had 

taken lessons and those who had not. 

Attendance is highest for those whose first lessons were either during the 

elementary school years or during the college years (62 and 54 percent, 

respectively), suggesting that both earliness of socialization and the individual’s explicit choice of a socialization experience--as opposed to an 

educational or parental requirement-can be important factors in future 

attendance. 

Similarly, the influence of these classes is smaller during the high school 

years (39 percent participation) than in either elementary school (66 percent) 

or in the years after high school (57 and 61 percent). The figure of 66 percent 

attendance for adults who had taken an art appreciation course in elementary 

school is one of the highest art museum participation rates found in the SPPA 

data when considering the effects of a single independent variable. 

The participation rate is 55 percent for those who remembered having 

attended art museums frequently with their parents. The rates for those who 

27 
 

Table 5
 

Socialization and Attendance at Art Museums
 

and Art Galleries, 1985
 

Question: Have you ever taken lessons or a class in visual arts such as sculpture, painting, 

print making, photography, film making, etc. ? 

Per 1,000 Adults 

Participation Number in 

rate Number category 

All adults 22% 219 1,000 

who had taken lessons 45% 112 248 

who had not taken lessons 15% 110 752 

Adults who first took 

lessons at less than 12 years 62% 21 33 

12-17 years 37% 43 115 

18-24 years 54% 30 56 

25+ years 40% 18 44 

Adults who attended an art museum	 50% had taken lessons 110 219 

50% had not taken lessons 109 219 

Adults who had not 

attended an art museum 18% had taken lessons 137 781 

82% had not taken lessons 644 781 

Question: ttave you ever taken a class in art appreciation or art history? 

Al! adults 22% attended 219 1,000 

who had taken a class 51% attended 99 194 

who had not taken a class 15% attended 122 8O6 

Adults who first took a 

class at less than 12 years 66% attended 4 6 

12-17 years 39% attended 26 68 

18-24 years 57% attended 60 105 

25+ years 61% attended 8 14 

Adults who attended an art museum	 45% had taken a class 98 219 

55% had not taken a class 121 219 

Adults who had not 

attended an art museum 12% had taken a class 95 781 

88% had not taken a class 686 781 

Question: Did your parents---or other adult members of the lwusehold~take you to art 

museums or galleries often, occasionally, or never? 

Adults who had attended 

frequently with parents 55%attended 26 47 

occasionally with parents 35%attended 105 297 

never attended with parents 14%attended 92 656 

Source: "Survey of Public Participation in the Arts," 1985. 

28 
 

The Audience for American Art Museums 

visited occasionally with their parents and those who never visited with their 

parents are 35 percent and 14 percent, respectively. 

A logit model was run to see what happens to the probability of attendance participation rate when these three socialization factors are accounted 

for simultaneously, along with the demographic variables considered earlier. 

The results are reported in Table B in the Appendix. All of the socialization 

variables, along with education, turn out to be highly significant statistically. 

Age, the race variable for Blacks, and the highest income group variable also 

have coefficients that are statistically significant. 

All of the socialization variables add considerably to the probability of 

attendance. This can be most clearly seen using a graph like the one presented 

earlier. Figure 3 shows the relationship between the probability of attendance 

and education level for the sample individual with none of the three socialization experiences (Example no. 1) and with all three (visual art lessons, 

attendance with parents, and an art appreciation course) of the socialization 

experiences (Example no. 2). While the probability of attendance still 

increases with higher levels of education as before, the increase in the 

probability of attendance due to socialization is very striking. 

This model is a better one than the model formulated in Part I, which 

used only demographic variables. The proportion of the variation explained 

Figure 3 

Logit Analysis--Graph of the Probability of Attendance by Education 

for Sample Individual with Socialization Variables 

ir 

0.9 

0.8 i 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0 

6 8 10 12 14 16 18 

~’ears of Education 

 ̄ Example no. 1  ̄ Example no. 2 No Socialization Experiences All Three Socialization Experiences 

29 
J. Mark Davidson Schuster 

improved from 16 percent to :22 percent. The improvement was primarily in 

the model’s ability to predict correctly those who actually attend (47 percent 

in the socialization model as opposed to 27 percent in the raw demographic 

model), but this model is still a long way from what one would like to have 

in a predictive model. 

Part II1: Unsatisfied Demand and Barriers to 

Attendance 

If two adults out of nine attended an art museum or an art gallery in the 

previous year, seven did not. Who are the individuals who do not attend 

museums’? Why? Who would like to attend more? Who are the potential 

members of the museum audience? The answers to these questions are of 

concern both to museums that would like to market their services more 

effectively and to funding agencies that would like to expand the reach of 

arts organizations into previously unserved or underserved segments of the 

community. 

Unsatisfied Demand 

SPPA data on the responses of adults who said they would like to attend 

art museums more often must be approached with a degree of skepticism for 

two reasons. First, respondents’ answers are based on hypothetical situations 

rather than on actual behavior. It is easier to say you would like to go more 

often than to actually exert the effort to go. Second, when attention is 

restricted to demographic variables only, they become the only possible 

explanations for unsatisfied demand or non-attendance that are readily 

available. This again runs the risk of concluding that survey respondents are 

prisoners to their demographics. 

Table 6 shows that nearly a third of American adults would like to attend 

art museums more often. Yet 58 percent of the individuals who are already 

attenders would like to go more often, while only 23 percent of non-attenders 

would like to attend more frequently. (Interestingly, this percentage remains 

quite high across participation levels: of those individuals who indicated that 

they had attended an art museum two or three times in the previous month, 

62 percent indicated that they would like to go more during a year; of those 

who attended six or more times in the previous month, 52 percent indicated 

they would like to attend more often.) But because of the large number of 

non-attenders in the adult population, nearly 60 percent of those who would 

30 
Table 6
 

Unsatisfied Demand for Attendance at Art Museums
 

and Art Galleries, 1985
 

Question: Few people can do everything they would like to do. But if you could do any of 

the things listed on this card as often as you wanted, which ones would you do more often 

than you have during the last 12 months? 

Per 1,000 Adults 

Percentage who Number Who Number in 

checked museums Checked Museums Category 

Overall 31% 307 1,000 

Attendance 

Attenders 58% 128 219 

Non-Attenders 23 % 179 718 

Income 

$5,000orless 25% 21 82 

$5,000~9,999 25% 31 126 

$10,000-$14,999 

$15,000-$24,999 

$25,000-$49,999 

$50,000 or mom 

27% 

29% 

36% 

45% 

39 

72 

111 

42 

143 

247 

308 

94 

Education 

Grade School 

Some High School 

High School Grad 

Some College 

Four-year College Grad 

Graduate School 

12% 

22% 

29% 

38% 

44% 

44% 

13 

26 

108 

77 

48 

36 

110 

118 

376 

203 

220 

82 

Age 

18-24 years 

25-34 years 

35-44 years 

45-54 years 

55-64 years 

65-74 years 

75+ years 

34% 

35% 

35% 

27% 

28% 

26% 

17% 

55 

82 

63 

36 

36 

25 

10 

161 

238 

182 

132 

130 

97 

59 

Gender 

Females 

Males 

33% 

28% 

173 

134 

528 

472 

Race 

Black 

White 

Other 

25% 

32% 

18% 

27 

277 

3 

108 

873 

19 

Source." "Survey of Public Participation in the Arts," 1985. 

31 
J. Mark Davidson Schuster 

like to go more often are currently not attending. The problem for a museum 

is that these individuals are considerably more difficult to identify than those 

who are already attenders. 

As both income and education levels increase unsatisfied demand rises 

to a high of four adults out of nine. By income, more than a third of the 

individuals with unsatisfied demand can be found in the $25,000-$49,999 

income group; by education, nearly a third can be found among those whose 

highest level was graduation from high school. When we examine the effect 

of age, unsatisfied demand remains roughly constant at 35 percent for 

individuals age 16-44, but then begins to decline. 

To determine which demographic variables predict best those individuals 

who are most likely to have unsatisfied demand, a logit model was ran. The 

actual logit results are reported in Table C of the Appendix. Education 

emerges from this model as the most important predictor of unsatisfied 

demand, ’with a positive coefficient and the highest level of statistical 

significance among the variables tested. The probability of unsatisfied demand rises with the number of years of education and is generally higher at 

higher levels of income (except for the $15,000-$24,999 category). The 

probability of unsatisfied demand decreases gradually with age. Women are 

more likely to have unsatisfied demand than men; whites are more likely to 

have unsatisfied demand than Blacks or other racial groups; students are more 

likely than non-students; and the probability of unsatisfied demand rises with 

increased urbanization. 

The results show that while the model does help in identifying the 

variables that are most highly significant in a statistical sense, the overall 

performance of the model is again very weak. The model only explains 5 

percent of the variation in the dependent variable. Although there are 

statistically detectable relationships between the demographic variables and 

unsatisfied demand, there is a lot more variation in unsatisfied demand that 

cannot be. accounted for by these demographic variables. Together, these 

findings suggest the beginning of an explanation, but they are far from being 

determinant. 

Barriers to Attendance 

Do these results concerning unsatisfied demand reflect a general view 

among the population that museums are worthy things to attend and that more 

attendance would be preferable to less? Or is attendance actually constrained 

by other factors, which, if they were removed, would result in increased 

attendance? If the key binding constraints are ones that could be changed by 

32 
The Audience for American Art Museums 

museums, some interesting possibilities could arise for museums that are 

trying to decide how to attract new audiences and increase their old audiences. 

During one of the six months of the 1985.SPPA survey, respondents were 

asked about their reasons for not attending more often. The survey questionnaire offered the interviewers fifteen specific reasons according to which 

they coded the oral responses; they could check more than one if several 

factors seemed important. The results are summarized in Table 7. 

Before examining these results, it is important to realize that few of the 

barriers to attendance included in the SPPA are barriers that are within the 

direct control of the museums themselves. This is not to say that there are 

not important barriers to attendance that are the result of choices made by 

museum officials, only that these cannot be documented within the confines 

of the SPPA surveys. 

Overall, few of these barriers seem to have a serious effect on attendance. 

A very small percentage of the adult population cites each one (with the 

exception of the vague reasons "not enough time" and "lack of motivation"). 

Yet, 31 percent of the adult population cited one or more of these reasons for 

non-attendance. Although many people have reasons for not attending more, 

those reasons are diffuse. 

A second overall pattern of interest is that for every barrier except "prefer 

to watch TV," the percentage of attenders who cite each barrier is greater 

than or equal to the percentage of non-attenders. This further reinforces the 

finding that unsatisfied demand is greater among those who are already 

attenders. 

Some of the individual findings deserve more attention. The most frequently cited barrier is not having enough time (13.7 percent of the population). One barrier that might have been expected to have been selected more 

often is "feeling uncomfortable"---it is often suggested that arts institutions 

make it very difficult for the uninitiated to feel that the institution is accessible 

to them. Yet, only one-tenth of one percent of the population felt this to be 

a problem. (Interestingly, low percentages like this are found across all of 

the art forms included in SPPA.) 

A moderate percentage of individuals cites "lack of availability" or "too 

far to go" as reasons for lower attendance. While it seems that this could be 

attributed to the geographic distribution pattern of museums, without further 

comparative data on the distribution of respondents we cannot be sure; it is 

also possible that these answers were used by respondents to express an 

inaccessibility that was part psychological as well as geographical. 

To better target potential museum audiences, it will help to take this 

analysis one step further and ask, "Of those with unsatisfied demand, what 
Table 7
 

Barriers to Attendance at Art Museums
 

and Art Galleries, 1985
 

Question: What are the reasons you did not attend art galleries/art museums more often? 

Any other reasons? 

Tickets sold out 

All Adults 

Attenders 

Non-Attenders 

Cost 

All Adults 

At~:enders 

Non-Attenders 

Not available 

All Adults 

Attenders 

Non-Attenders 

Too far to go 

All Adalts 

Attenders 

Non-Attenders 

Transportation/Traffic/ 

Parking problems 

All Adults 

Attenders 

Non-Attenders 

Crime or fear of crime 

All Adults 

Attenders 

Non-Attenders 

Feel uncomfortable 

All Adults 

Attenders 

Non-Attenders 

Poor Quality/Not very good, etc. 

All Adults
 

Attenders
 

Non-Attenders
 

Percent Citing
 

Barrier
 

0.1% 

0.4% 

0.0% 

4.0% 

5.7 % 

3.5 % 

6.4% 

11.4 % 

4.9% 

6.7% 

13.9% 

4.6% 

2.7% 

3.7% 

2.5 % 

0.6% 

0.6% 

0.6% 

0.1% 

0.1% 

0.1% 

0.4% 

0.9% 

0.3 % 

Per 1,000 Adults 

Number Citing Number 

Barrier in Category 

1 1,000
 

1 219
 

0 718
 

40 1,000
 

13 219
 

27 718
 

64 1,000
 

25 219
 

39 718
 

67 1,000
 

30 219
 

36 718
 

27 1,000
 

8 219
 

19 718
 

6 1,000
 

1 219
 

5 718
 

1 1,000 

* 219
 

1 718
 

4 1,000
 

2 219
 

2 718
 

34 
Table 7 (Continued) 

Per 1,000 Adults 

Percent Citing Number Citing Number 

Barrier Barrier in Category 

Don’t have anyone to go with 

All Adults 

Attenders 

1.6% 

2.2% 

16 

5 

1,000 

219 

Non-Attenders 1.4 % 11 718 

Problem related to a handicap 

All Adults 

Attenders 

0.4% 

0.5 % 

4 

1 

1,000 

219 

Non-Attenders 0.3% 3 718 

Problem related to age/health 

All Adults 

Attenders 

0.7% 

1.2% 

7 

3 

1,000 

219 

Non-Attenders 0.6% 5 718 

Babysitter problems/ 

Must care for children 

All Adults 

Attenders 

1.7% 

3.5% 

17 

8 

1,000 

219 

Non-Attenders 1.2% 9 718 

Prefer to watch TV 

All Adults 

Attenders 

Non-Attenders 

0.9% 

0.2% 

1.1% 

9 

* 

9 

1,000 

219 

718 

Don’t have time 

All Adults 

Attenders 

Non-Attenders 

13.7 % 

27.9% 

9.7 % 

137 

61 

75 

1,000 

219 

718 

Procrastination/ 

Lack of Motivation 

All Adults 

Attenders 

Non-Attenders 

4.0% 

8.2% 

2.7% 

40 

18 

21 

1,000 

219 

718 

Source: "Survey of Public Participation in the Arts," 1985. 

Notes: For each barrier to attendance, the number of attenders plus the number of nonattenders who cited the barrier do not necessarily add up to the total number of adults 

who cited it because of rounding errors. 

*Less than one person per thousand. 

35 
Table 8
 

Barriers to Attendence and Unsatisfied Demand, 1985 

Question: What are the reasons you did not attend art galleries/art museums more often? 

Per 1,000 Adults 

Percent Citing Number Citing Number in 

this Barrier this Barrier Category 

Cost 

All adults with unsatisfied demand 12.8% 39 307 

Attenders 9.5% 12 129 

Non-Attenders 15.2% 27 178 

Not available 

All adults with unsatisfied demand 20.3% 62 307 

Attenders 18.6% 24 129 

Non -Attenders 21.5 % 38 178 

Too far to go 

All adults with unsatisfied demand 21.5% 66 307 

Attenders 23.5% 30 129 

Non-Attenders 20.1% 36 178 

Feel uncomfortable 

All adults with unsatisfied demand 0.4% 1 307 

Attenders 0.2% 129 

Non-Attenders 0.5% 178

Poor quality/Not very good, etc. 

All adults: with unsatisfied demand 1.2% 307 

Attenders 1.2% 129 

Non-Attenders 1.2% 178 

Don’t have time 

44.3% 136 307 

Attenders 47.6% 61 129 

Non-Attenders 42.0% 75 178 

All adults with unsatisfied demand 

Procrastination/Lack of motivation 

All adults with unsatisfied demand 12.8% 39 307 

Attend ers 13.8% 18 129 

Non-Attenders 12.0% 21 178 

Source: "Survey of Public Participation in the Arts," 1985. 

*Less than one person per thousand. 

36 
The Audience for American Art Museums 

percentage cites each of these barriers?" (Table 8) In this case, both discomfort and lack of quality remain unimportant barriers to participation; but cost, 

availability, distance, and lack of time are all of significantly higher importance among those who also said that they would like to be able to attend or 

to attend more frequently. The responses to the last barrier, "lack of motivation," are more difficult to interpret; there is a paradox in the fact that even 

12 to 13 percent of those who expressed a desire for more attendance cite 

"lack of motivation" as a barrier to attendance.17 

Part IV: Profiles of the Museum Audience(s) 

Up to this point the analysis has focused on demographic groups one at 

a time and asked what percentage of each group attends art museums, what 

percentage of the group would like to attend more, and what percentage of 

the group cites specific reasons for not attending more. This section takes a 

different perspective, and examines how the demographic characteristics of 

the SPPA respondents are distributed among the museum audience and how 

this audience profile compares to the profile of the general population. 

But proceeding with this analysis requires a much clearer definition of 

the group of individuals we are actually referring to when we speak of the 

"museum audience." The audience a museum sees coming through its doors 

is not the same as the audience that is documented in a cross-sectional 

sample of the population, such as the SPPA. This is true for two reasons. 

First, the audience of a particular museum will differ from the overall 

average audience profile resulting from a population survey, each museum 

will be operating in the midst of a number of microfactors that are not typical 

of the abstract, "average" museum. A museum’s ability to attract certain 

demographic groups is a function of both its own programming choices, 

which make it more attractive to certain demographic groups than to others, 

and of the demographic groups that actually live near enough to make access 

easy of the museum. 

Second, a cross-sectional survey of the adult population allows the 

identification of visitors (and non-visitors), while a survey of admissions at 

the door of the museum is a survey of visits. The fundamental difference lies 

in differences in frequency of attendance. A visitor who is a frequent attender 

is much more likely to be picked up in a survey within a museum than an 

individual who attends, but infrequently. A museum that wishes to figure out 

how many differentindividuals it is serving and who they are in demographic 

terms must carefully account for the fact that frequent attenders are more 

37 
J. Mark Davidson Schuster 

likely to appear in audience samples in proportion to their frequency of 

attendance.18 

While it is undoubtedly an oversimplification, it is not unreasonable to 

suggest that the audience that is perceived by the museum is the audience of 

visits, while the audience on which funding agencies focus is the audience 

of visitors.. But which focus is ultimately appropriate is a function of which 

decisions are at stake. A museum that is interested in better targeting its 

museum shop to its market, for example, will be concerned with the income 

profile of visits. The museum that is trying to target its activities to new 

population groups may be more concerned with the demographics of visitors. 

The funding agency that is concerned about outreach and new constituencies 

will stress visitors, while a funding agency that is trying to assess how reliant 

a museum can become on paid admissions (in order to determine appropriate 

levels of government or private funding) will stress visits. 

Tables; 9a and 9b summarize the distribution of visitors and visits 

according to several of the demographic variables and compare those distributions to the corresponding distributions for the adult population. To 

estimate visits from the 1985 SPPA data in order to construct these tables, 

individuals who indicated they had visited an art gallery or art museum in 

the previous year were weighted according to their stated frequency of 

attendance.19 

Figures 4a and 4b and 5a and 5b display some of the information in Tables 

9a and 9b as bar charts, giving audience profiles according to income and 

education--two of the key variables whose distribution museums attempt to 

manage through reaching out to new and underrepresented constituencies-­

and comparing them to the overall adult population. 

Looking first at the distribution of visitors, the audience is composed 

disproportionately of individuals with incomes over $25,000 (as compared 

to their relative proportion in the overall population). Also overrepresented 

are individuals with more than a high school education. Visitors are slightly 

younger, :more likely to be white, and less likely to come from outside of 

urbanized areas than the overall adult population. Professionals are twice as 

likely to be found among visitors to art museums as among the general 

population. 

Among visits, upper income and more highly educated individuals are 

even more overrepresented, indicating that these individuals are not only 

more likely to attend art museums but that they also attend more frequently. 

From the individual museum’s perspective, this means that an income or 

education profile of visits will give a picture of an audience more weighted 

toward the upper categories than a profile of the actual, identifiable visitors 

38 
Table 9a
 

Audience Profiles 1985" Percent Distribution
 

Adult Population Visitors Visits 

Incomef 

$4,999 or less 8% 6% 9% 

$5,000-$9,999 13% 7% 7% 

$10,000-$14,999 14% 9% 10% 

$15,000-$24,999 25% 21% 20% 

$25,000-$49,999 31% 38% 27% 

$50,000 or more 9% 19% 27% 

100% 100% 100% 

Education 

Grade School 11% 2% 1% 

Some High School 12% 4% 4% 

High School Grad 38% 24% 13% 

Some College 20% 27% 29% 

Four-year College Grad 11% 23% 25% 

Graduate School 8% 21% 28% 

100% 100% 100% 

Age 

18-24 years 16% 16% 21% 

25-34 years 24% 28% 23% 

3544 years 18% 22% 23% 

45-54 years 13% 14% 14% 

55-64 years 13% 11% 8% 

65-74 years 10% 7% 7% 

75+ years 6% 3% 3% 

100% 100% 100% 

Gender 

Female 53% 55% 52% 

Male 47% 45% 48% 

100% I00% 100% 

Race 

Black 11% 5% 3% 

White 87% 93% 92% 

Other 2% 2% 5% 

100% 100% 100% 

Urbanization 

Central City of SMSA 27% 31% 45% SMSA but not Central City 41% 49% 40% Outside an SMSA 32% 20% 15% 

100% 100% 100% 

Source: "Survey of Public Participation in the Arts," 1985. 

*The income distribution of the population reported here differs from the data in the 1985 Current Population Survey, which shows a higher proportion of the population in the upper income groups. Nevertheless, 

the figures reported here are internally consistent with the SPPA data and relative comparisons of the 

population to visitors and visits are the best possible with the available data. 

39 
Table 9b
 

Audience Profiles 1985: Number per 1,000 Adults
 

Adult Population Visitors Visits 

Income* 

$4,999 or less Of 82 adults, there were 13 visitors, making 66visits 

$5,000-- $9,999 126 14 53 

$10,000-$14,999 143 21 77 

$15,000-$24,999 247 47 149 

$25,000-$49,999 308 85 200 

$50,00t3 or more 94 42 206 

Education 

Grade School 110 4 7 

Some tligh School 118 8 29 

High School Grad 376 53 97 

203 60 218 Some College 

Four-year College Grad 110 50 188 

Graduate School 82 45 212 

Age 

18-24 years 161 35 161 

25-34 years 238 61 176 

48 170 35-44 years 182 

45-54 years 132 30 105 

55-64 years 130 24 62 

65-74 years 97 16 54 

75+ years 59 6 24 

Gender 

528 121 392 

Male 472 99 359 

Female 

Race 

108 12 23 

Whi~ 873 203 693 

Other 19 5 35 

Black 

Urbanization 

Central City of SMSA 271 69 339 

SMSA but not Central City 413 107 302 

Outside an SMSA 316 44 110 

Source: "Survey of PuNic Participation in the Arts," 1985. 

tThe income distribution of the population reported here differs from the data in the 1985 Current Population Survey, which shows a higher proportion of the population in the upper income groups. Nevertheless, 

the figures reported here are internally consistent with the SPPA data and relative comparisons of the 

population to visitors and visits are the best possible with the available data. 

4O
 
 

 

Figure 4a 

Education Profile of the Audience for Art Museums and Art Galleries, 1985: 

Distribution of Visitors, Visits, and the Adult Population 

50% 

40% 

30% 

20% 

10% 

Grade Some High High Some College Graduate 

School School School College Grad School 

D Visitors I~ Visits 

Figure 4b
 Education Profile of the Audience for Art Museums and Art Galleries, 1985:
 

Total Number of Visitors, Visits, and the Adult Population
 

40 

30 

N\ 

N\ 

N\
 

20
 

10 

0 Grade Some High High Some College Graduate 

School School School College Grad School 

~ Visitors l Population ]~ Visits 

41 
Figure 5a 

Income Profile of the Audience for Art Museums and Art Galleries, 1985: 

Distribution of Visitors, Visits, and the Adult Population 

50% 

40% 

30% 

20% 

10% 

$0-$5K $5-$10K $10-$15K $15-$25K $25-$50K $50K + 

Visitors I Population ~-~ Visits 

Figure 5b 

Income Profile of the Audience for Art Museums and Art Galleries, 1985: 

Total Number of Visitors, Visits and the Adult Population 

60 

50 

40 

~ 20 

10 

$0-$5K $5-$10K $10-$15K $15-$25K $25-$50K $SDK + 

Visitors [~ Visits 1 Population 

42 
The Audience for American Art Museums 

who are being served. This is not a new phenomenon; earlier studies have 

noticed much the same pattern, which has not changed substantially in the 

25 years for which various data sources are available.2° 

While these distributions provide useful bases by which to compare both 

aggregate changes in the museum audience over time and a particular 

museum’s audience to the aggregate audience, one should not be too hopeful 

that interventions in the operation of art museums will succeed in dramatically changing the audience profile. These aggregate profiles are very robust, 

reflecting a variety of factors, not the least of which is the interaction of the 

population’s tastes with its demographic characteristics. Research into audience demographics has repeatedly shown that while short-term changes in 

the audience profile may be attained through very visible and popularly 

attractive exhibitions or programs, it is much more difficult to sustain these 

changes over a longer period.21 

But note that a growth in attendance figures is not incompatible with an 

overall stability in the profile of the audience. The size of the audience can 

increase, either through new attenders or through increases in the frequency 

of attendance of previous attenders, while the demographic profile of the 

audience might change very little (except to reflect general societal changes 

in the level of income or the level of education). Another way to state this is 

that the raw numbers per 1,000 adults in Table 9b could increase while the 

relative percentages in Table 9a remained more or less the same. 

Table 10 shows the average number of visits per adult and visits per 

visitor disaggregated by income and by education level. The average number 

of visits per adult per year is 0.75; this means that the average American adult 

attends an art museum or art gallery once every 16 months. Visits per adult 

remain more or less at this level across income groups, with the exception of 

individuals with incomes over $50,000. These adults attend art museums an 

average of 2.26 times per year. Looking at only those visitors who actually 

visited an art museum in the previous year, the average number of visits per 

visitor is 3.42; individuals who go to art museums go slightly more than once 

every four months. Only the lowest income group (5.33 visits per visitor) 

and the highest income group (5.03 visits per visitor) have rates substantially 

different from the overall rate. (Separating students from non-students does 

not remove the apparent anomaly in the lowest income group.) 

Across education levels, visits per person increase from 0.06 to 2.58. 

Visits per visitor are lowest for individuals with only a grade school education--l.60~and highest for those with at least some graduate school education~.69. The dip to 1.84 visits per visitor for high school graduates is 

another anomaly in the data. 

43 
J. Mark Davidson Schuster 

Table 10
 

Frequency of Attendance by Income and Education,
 

1985
 

Visits Per Visits Per 

Adult Visitor 

Overall 0.75 3.42 

Income 

$4,999 or less 0.83 5.33 

$5,000-.$9,999 0.43 3.75 

$10,000-$14,999 0.55 3.80 

$15,000-$24,999 0.62 3.28 

$25,000-$49,999 0.67 2.41 

$50,000 or more 2.26 5.03 

Education 

Grade School 0.06 1.60 

Some High School 

High Sc, hool Grad 

Some College 

Four-year College Grad 

0.24 

0.26 

1.08 

1.71 

3.64 

1.84 

3.65 

3.80 

Graduate School 2.58 4.69 

Source: "Survey of Public Participation in the Arts," 1985. 

Note: The rmmber of visits per year for each respondent was estimated from the 

respondent"s answer to the question: "How many times did you do this [visit an art 

museum or an art gallery] last month?" For a detailed discussion of the procedure used, 

see Note 19. 

Projecting the estimate of 0.75 visits per adult to the entire 1985 adult 

population leads to a rough estimate of 128 million visits made by 37.5 

million adult American visitors to art museums and art galleries in 1985. 

However., because of the number of assumptions necessary to derive an 

overall estimate from the SPPA data, one should not place too much 

confidence in this overall estimate. 

What do other sources say about the volume of attendance at American 

art museums? Museums USA was the first major cross-sectional study of 

American museums. It estimated that in 1971-1972 there were 1,821 museums that met the accreditation criteria of the American Association of 

Museums, 340 of which were primarily art museums.22 According to the 

survey results, art museums had an average attendance of 127,000 in that 

year, for a total of 43 million visits. The 186 art/history museums had an 

44 
The Audience for American Art Museums 

average attendance of 94,000 visits, or an additional 17.5 million visits, for 

a total of 60.5 million visits to art and art/history museums. This study 

employed a broad definition of attendance, including general attendance by 

adults, children, and foreign tourists, and attendance at special exhibitions, 

by school class groups, at workshops and classes, and performing arts 

presentations, films, etc. Taken together these lead to a more inclusive total 

attendance figure than the one that can be derived from SPPA. 

More recently, the Institute of Museum Services commissioned the 

National Center for Education Statistics to undertake a more comprehensive 

study of the museum universe.23 This 1979 study used a slightly broader 

definition of a museum that included nonprofit museums without professional staff. This study identified a universe of 4,408 museums, 609 of which 

were defined as primarily art museums. These museums had an average 

annual attendance of 81,817. This figure is lower than the Museums USA 

figure from seven years earlier because of the broader definition of museums, 

which brought many smaller museums into the overall calculations, rather 

than because of any substantial fall in museum attendance. This figure 

projects a total of 49.8 million visits in 1979. Yet, these figures are not 

particularly reliable because the survey also uncovered the fact that only 247 

of the art museums were using what could be termed "accurate attendance 

measurement methods"; the others were forced to estimate. Once again, this 

total includes many individuals beyond the American adults on whom SPPA 

focused. 

Despite their drawbacks, these benchmarks suggest that the aggregate 

figures derived from SPPA reflect overestimation on the part of the respondents. It would not be surprising if the SPPA-derived estimate is high by a 

factor of two or more. 

But the estimate derived from the SPPA data is not as high as the estimate 

of total attendance that one would infer from the Harris Americans and the 

Arts data.2’~ Though the documentation is not explicit as to how the calculations were made, Harris reports a mean of 2.7 visits per visitor for his data 

(lower than the comparable estimate from SPPA data). Adjusting this figure 

by the participation rate calculated by Harris leads to a mean of 1.57 visits 

per adult in the U.S. population. Multiplying this figure by the size of the 

adult population leads to the highest attendance estimate of all, 267 million 

visits to art museums by American adults in 1984. 

Although the overall estimates derived from the SPPA frequency of 

attendance data seem high, that does not necessarily imply that the distributions of visits are incorrect. Unless one wishes to argue that individuals in 

certain income groups or educational levels are more likely to overestimate 

45 
J. Mark Davidson Schuster 

their attendance patterns than individuals in other demographic groups, using 

the relative frequency of attendance to generate the distributions of visits 

presented in Tables 9a and 9b is a reasonable procedure and provides the best 

currently available profiles of the American audience for art museums. 

Conclusion 

An understanding of audiences for museums begins with attendance 

figures and is enhanced by demographic information, but it will not be 

complete without a better understanding of why people visit museums and 

how those visits are integrated into their value system. That work is just 

beginning. 

One of the next steps is to turn to measures of museum effectiveness: 

What is the quality of a visit to a museum? In studying their audiences, 

museums will do well to heed the reminder of Alma Wittlin: 

Neither visitors’ books in which the attendance is supposedly 

registered nor the stricter control of the turnstile at the gate of the 

museum which mechanically records the number of visitors is a 

true indicator of performance. At their best they record the number 

of warm bodies entering the premises.25 

A museum can change itself or it can work to change its audience. Either 

kind of change will be difficult, but it will be impossible to measure one 

important aspect of that change---changes in the makeup of its audience--if 

the museum does not document and understand its current audience first.26 

It is my hope that in this monograph I have provided a solid base on which 

museums, can begin, or expand, the study of their own audiences in a 

systematic fashion. It is increasingly important for a museum to understand 

the population it serves as well as the population it does not yet serve.27 

46 
The Audience for American Art Museums 

NOTES 

1. Alma S. Wittlin, Museums." In Search of a Usable Future (Cambridge, 

Mass.: M.I.T. Press, 1970), p. 76. 

2. Ibid., pp. 102-103. 

3. Nathaniel Burt, Palaces for the People: A Social History of the American 

Art Museum (Boston: Little, Brown and Company, 1977), pp. 282-283; 

and Karl E. Meyer, The ArtMuseum: Power, Money, Ethics (New York: 

William Morrow and Company, 1979), pp. 64, 121. 

4. Paul DiMaggio, Michael Useem, and Paula Brown, Audience Studies of 

the Performing Arts and Museums : A Critical R eview, Research Division 

Report #9 (Washington, D.C.: National Endowment for the Arts, November 1978). 

5. Ibid, p. 33. An example of the latter approach is contained in Alan L. 

Feld, Michael O’Hare, and J. Mark Davidson Schuster, Patrons Despite 

Themselves: Taxpayers and Arts Policy (New York: New York University Press, 1983), pp. 74-75. 

6. The reader who wishes to extrapolate these findings to estimates for the 

entire American population can multiply any of the figures reported in 

the tables that are expressed in terms of number per 1,000 adults by 

170,520. This multiplication will weight these figures to the size of the 

adult American population in 1985, which the U.S. Bureau of the Census 

estimated at 170,520,000 in constructing its own weighting for SPPA ’85. 

7. Unfortunately, because the Bureau of the Census has masked the regional 

variables on the data tape that is publicly available to protect the 

confidentiality of the respondents, it is not possible to explore regional 

differences any further than through the simple analyses that are presented at the end of Table 1. These analyses were prepared separately by 

the Bureau of the Census from the complete data tape and provided to 

the National Endowment for the Arts. 

8. National Research Center of the Arts, Inc., Americans and the Arts: A 

Survey of Public Opinion (New York: Associated Councils of the Arts, 

1975), [1973 study]; National Research Center of the Arts, Inc., Americans and the Arts: A Sur~’ey of the Attitudes Toward and Participation 

in the Arts and Culture of the United States Public (New York: Associated Councils of the Arts, August 1975), [1975 study]; National 

Research Center of the Arts, Inc., Americans and the Arts (New York: 

American Council for the Arts, 1981), [1980 study]; National Research 

Center of the Arts, Inc., Americans and the Arts (New York: Louis Harris 

and Associates, October 1984), [1984 study]; National Research Center 

47 
J. Mark Davidson Schuster 

of the Arts, Americans and the Arts V: A Nationwide Survey of Public 

Opinion (New York: American Council for the Arts, March 1988), [1987 

study]. 

9. John P. Robinson, Carol A. Keegan, Terry Hartford, and Timothy A. 

Triplett, Public Participation in the Arts: Final Report on the 1982 

Survey, Appendix B, unpublished report available from the Research 

Division, National Endowment for the Arts. 

10. J. Mark Davidson Schuster, "Making Compromises to Make Comparisons in Cross-National Arts Policy Research," Journal of Cultural 

Economics, Vol. 11, No. 2, December 1987. 

11. Market & Opinion Research International Limited, unpublished report 

on a survey conducted for BBC "Panorama," 26 November 1981 (some 

results from this survey have been published in John Myerscough, Facts 

About the Arts 2:1986 Edition (London: Policy Studies Institute, September 1986), pp. 294-301); Ministbre de la Culture, Service des l~tudes 

et Recherches, Pratiques Culturelles des Fran~ais: Description SocioDemographique--Evolution 1973-1981 (Paris: Dalloz, 1982), report of 

a survey conducted by ARCmc; Official Statistics of Sweden, Cultural 

Statistics: Activities, Economy and Cultural Habits 1980-1984 [Kulturstatistik] (Stockholm: Statistics Sweden, 1987); Minist~re des Affaires Culturelles du Qufibec, Chiffres c~ L’Appui, Bulletin du Service de 

la Recherche et de la Planification, Vol. 2, no. 2, May 1984, pp. 9-14, 

report of a public opinion poll conducted by the Centre de Recherche sur 

l’Opinion Publique in 1983. 

12. Market & Opinion Research International Limited, unpublished report 

on a survey conducted for BBC "Panorama,," 26 November 1981. This 

study also found that trade union members were more likely to go to 

museums than non-members (31% :28%), but non-members were more 

likely to go to art exhibitions (15%:21%1). Participation rates were 

highest among persons intending to vote Conservative, somewhat lower 

for those intending to vote Social Democrat/Liberal Alliance, and 

lowest for Labour (35 %:29% :25% for museums and 27%:21%: 13% for 

art exhibitions). Not surprisingly, museum participation rates were the 

highest among those who supported public funding for ballet, opera, or 

theatre: 36-38 percent of supporters attended museums, 26 to 28 percent 

attended art exhibitions. Participation rates were roughly three times 

higher for individuals who had heard of the Arts Council of Great 

Britain. 

13.	 Minist~re de la Culture, Service des l~tudes et Recherches, Pratiques
 

Culturelles des Frangais, p. 151.
 

48 
The Audience for American Art Museums 

14.	 Ministbre des Affaires Culturelles du Quebec, Chiffres c~ L’Appui, May 

1984, pp. 9-14. 

15.	 For a useful discussion of multiple classification analysis using an arts 

example with SPPA data, see John P. Robinson, Carol A. Keegan, 

Marcia Karth, and Timothy A. Triplett, Public Participation in the Arts: 

Final Report on the 1985 Survey, "Volume I: Overall Project Report," 

1987, pp. 62-76, unpublished report available from the Research Division, National Endowment for the Arts. 

16. A relatively readable presentation oflogit analysis is contained in Robert 

S. Pindyck and Daniel L. Rubinfeld, Econometric Models and Economic 

Forecasts (New York: McGraw-Hill, 1981), pp. 275-301. 

17. When I wrote about this paradox in the first draft of this monograph, I 

suggested that it might indicate a separation between societal expectations--"I ought to go to museums because it is considered a worthy thing 

to do"--and personal desires--"I am not really motivated to go." 

Since then readers have suggested two other possible explanations. 

Pare Brusic has suggested that, "... today people are more burdened 

with personal than societal expectations--’If I want to be a wellinformed and cultured person, I ought to go to museums.’--and are more 

likely to mean lack of ability to organize their personal time sufficiently 

to attend when they cite ’lack of motivation.’... (T)here is an undertone 

of self-disapproval in a ’lack of motivation’ response and.., to lack 

motivation is generally thought of as a personal character flaw... (T)his 

alternate explanation., reflects more on the respondent’s attitude toward 

himself than toward the museum he is not motivated to attend." 

Harold Horowitz has offered a more prosaic explanation. When respondents got to this point in the survey they were asked if they would 

have liked to have gone to various artistic activities more often. Thinking 

that the long survey was almost over, they answered "Yes," but they were 

then asked a series of questions about barriers to attendance for each of 

the art forms for which they had indicated a desire to attend more often. 

Not having well-thought-out reasons in mind, they gave a vague reponse 

that was invariably coded "lack of motivation." 

These three rival explanations illustrate well the difficulty of ex~’acting definitive theories and explanations even from a dataset as complete 

and as carefully collected as SPPA ’85. 

18. For a further discussion of these concepts see Feld, O’Hare, and Schuster, 

Patrons Despite Themselves, p. 74; and Michael O’Hare, "The Audience 

of the Museum of Fine Arts," Curator, Vol. 17, no. 2, June 1974, p. 129. 

Unfortunately, this important distinction is often overlooked; for 

49 
J. Mark Davidson Schuster 

example, the otherwise excellent manual, Surveying Your Arts Audience, 

published by the Research Division of the National Endowment for the 

Arts (Washington, D.C.: National Endowment for the Arts, 1985), is 

silent on this subject. 

19. SPPA ’85 used two-part questions to ascertain levels of participation in 

various artistic activities. The first part asked whether or not the respondent had participated in the activity in the previous year, and the second 

how often the respondent had actually attended in the previous month. 

Robinson et al. have studied apparent inconsistencies between the 

answe~rs to these two parts and have concluded that it is most likely that 

the monthly frequency question overestimates frequency of attendance 

because respondents "telescope" their previous year’s experience into 

the previous month. (It is still logically possible, however, that respondents underestimate their annual participation.) Robinson et al., Public 

Participation in the Arts: Final Report on the 1982 Survey, pp. 227-233. 

In the analysis of the relative profiles of the museum audience I have 

used the frequency data to weight respondents’ attendance to calculate 

the distribution of visits. This procedure is valid as long as there is no 

reason, to believe that individuals in one demographic grouping are more 

likely to overestimate their attendance than individuals in another 

demographic grouping. 

SPPA ’85 was conducted over six months. I weighted each month’s 

respondents by a weight that was the product of how many individuals in 

the total population each respondent represented (a function of his or her 

demographic characteristics) times the frequency of attendance by that 

respondent in the previous month. Adding the six estimates together gave 

an estimate of the total number of visits to art museums made by the total 

adult population over those six months. I then multiplied these factors by 

two to represent one entire year of attendance. In cases where the 

frequencies were reported in categories---e.g, two to three times in the 

month--I used the lower bound of the interval to represent the frequency 

of attendance, using the most conservative assumption in a situation 

where there is reason to believe that overestimation is common. 

I tested the reasonableness of this procedure by doing a sensitivity 

analysis, performing a second analysis using the midpoints of the 

categories (and 8 visits for the 6+ category). The distributions of visits 

across the various demographic variables changed by only one percentage point in one or two cases. Thus, the percentage distributions are not 

sensitive to the choice of frequency to represent the categories. 

20. Feld, O’Hare, and Schuster, Patrons Despite Themselves, pp. 80-83; 

5O 
The Audience for American Art Museums 

also, J. Mark Davidson Schuster, unpublished comparison of results 

from the Baumol and Bowen audience surveys in the 1960s (William J. 

Baumol and William G. Bowen, Performing Arts: The Economic Dilemma, Cambridge, Mass.: M.I.T. Press 1967, pp. 71-98) with results from 

the Americans and the Arts surveys of the 1970s (see Note 9). 

21. A variety of studies done in Great Britain and France, particularly under 

the auspices of the Research Division of the French Ministry of Culture, 

suggest that audience demographics are surprisingly stable across fine 

art forms, across regions, and over time. Unfortunately, there has been 

no attempt to bring them together in one place to further explore the 

resilience of this stability. 

22. National Research Center of the Arts, Museums USA: A Survey Report 

(Washington, D.C.: U.S. Government Printing Office, January 1975), 

pp. xi and 130. 

23. Lewis C. Price, Lisa DiRocco, and Janice D. Lewis, Contractor Report: 

Museum Program Survey, 1979 (Washington, D.C.: National Center for 

Education Statistics, March 1981), pp. 52-64. This report is also referred 

to as the "Museum Universe Survey." 

24. National Research Center of the Arts, Inc., Americans and the Arts [ 1984 

study], pp. 62 and 65. 

25. Wittlin, Museums, p. 161. 

26. As a starting point see, for example, Marilyn G. Hood, "Getting Started 

in Audience Research," Museum News, Vol. 64, no. 2, February 1986, 

pp. 25-31; and Research Division, National Endowment for the Arts, 

Surveying Your Arts Audience. 

27.	 This is one of the points stressed in Wittlin’s "Twelve-Point Program for 

Museum Renewal." Wittlin, Museums, pp. 212-213. 

51
 
Appendix 

Results from Three Logit Analyses 

The text discusses the results of three different logit analyses that were 

conducted with the SPPA museum attendance data. The actual mathematical 

results of these three analyses are reported in this appendix. 

It may be helpful for the more mathematically inclinded reader to 

understand that logit analysis is a form of regression analysis in which the 

"natural logarithm" (logarithm to the base "e"--a mathematical constant 

equal to 2.’7183) of the odds ratio (the probability of attending divided by the 

probability of not attending) is predicted as a linear combination of the 

independent variables. In this way, the separate marginal contribution of each 

of the independent variables to the logarithm of the odds ratio can be 

calculated as the "coefficient" of each variable. (By comparison, ordinary 

regression analysis calculates the separate marginal contribution of each 

independent variable directly to a dependent variable.) The "intercept" is the 

value of the logarithm of the odds ratio when all of the independent variables 

are equal ~:o zero. This value is necessary to position the logit curve in the 

proper place. The probability of attendance at any point on the logit curve 

can be calculated algebraically from the logit equation. 

The results of using logit analysis to predict the probability of attendance 

from seven independent demographic variables--income, age, race, gender, 

education level, urbanization, and student status--is reported in Table A. The 

logit results in Table B predict the probability of attendance from eight 

independent variables, five of the most important demographic variables plus 

three variables that measure whether or not the individual had different 

socialization experiences. And Table C reports the results of a logit analysis 

that predicts the probability of an individual having unsatisfied demand using 

the seven original demographic variables. 

52 
The Audience for American Art Museums 

Table A 

Logit Results Predicting the Probability of Attendance 

Significant at 

Variable Name Definition Coefficient .05 Level? 

Intercept	 -6.075 

Income 2	 = 1 if $4,999 < income < $10,000 .0.150 No 

= 0 otherwise 

Income 3	 = 1 if $9,999 < income < $15,000 -0.123 No 

= 0 otherwise 

Income 4	 = 1 if $14,999 < income < $25,000 -0.004 No 

= 0 otherwise 

Income 5	 = 1 if $24,999 < income < $50,000 +0.201 Yes 

= 0 otherwise 

Income 6	 = 1 if ,5,49,999 < income +0.563 Yes 

= 0 otherwise 

Age	 = age in years -0.004 Yes 

Race 2	 = 1 if individual is Black -0.815 Yes 

= 0 otherwise 

Race 3	 = 1 if individual is "other" race -0.064 No 

= 0 otherwise 

Gender	 = 1 if female +0.355 Yes 

= 0 if male 

Educational Level = number of years of formal education +0.328 Yes 

SMSA 1 = 1 if live in central city of an SMSA +0.689 Yes 

= 0 otherwise 

SMSA 2 = 1 if live in SMSA but not in central city +0.450 Yes 

= 0 otherwise 

Student = 1 if currently a student +0.393 Yes 

= 0 otherwise 

R2 = .16 

Logit Equation: 

If, P = Probability of attendance for a particular individual.
 

Then, Natural logarithm (P/1-P) = - 6.075 - 0.150(Income 2) - 0.123(Income 3) - 0.004(Income 4)
 

+ 0.201 (Income 5) + 0.563(Income 6) - 0.004(Age) - 0.815(Race 2) 

- 0.064(Race 3) + 0.355(Gender) + 0.328(Educational Level) 

+ 0.689(SMSA 1) + 0.450(SMSA 2) + 0.393(Student) 

53 
J. Mark Davidson Schuster 

Table B
 

Logit Results Predicting the Probability of
 

Attendance with Socialization Variables
 

Variable Name Definition 

Intercept 

Income 2 = 1 if $4,999 < income < $10,000 

= 0 otherwise 

Income 3 = 1 if $9,999 < income < $15,000 

= 0 otherwise 

Income 4 = 1 if $14,999 < income < $25,000 

= 0 otherwise 

Income 5 = 1 if $24,999 < income < $50,000 

= 0 otherwise 

Income 6 = 1 if $49,999 < income 

= 0 otherwise 

Age = age in years 

Race 2 = 1 if individual is Black 

= 0 otherwise 

Race 3 = 1 if individual is "other" race 

= 0 otherwise 

Gender = 1 if female 

= 0 if male 

Educational Level = number of years of formal education 

Lessons = 1 ff individual has ever taken 

visual arts lessons 

= 0 otherwise 

Appreciatien = 1 if individual has ever taken course 

in art history or appreciation 

= 0 otherwise 

Parents 2 = 1 if parents took individual to arts 

museum occasionally 

= 0 otherwise 

Parents 3 = 1 if parents took individual to arts 

museum frequently 

= 0 otherwise 

R2 = .22 

Logit Equation: 

Coefficient 

-4.137 

-0.316 

Significant at 

.05 Level? 

No 

-0.091 No 

-0.196 No 

+0.144 No 

+0.540 Yes 

-0.007 

-0.852 

Yes 

Yes 

-0.177 No 

-0.008 No 

+0.186 Yes 

+0.758 No 

+0.783 No 

+0.625 Yes 

+1.359 Yes 

If, P = Probability of attendance for a particular individual. 

Then, Natural logarithm (P/l-P) = - 4.137 - 0.316(Income 2) - 0.091(Income 3) - 0.196(Income 4) 

+0.144(Income 5) + 0.540(Income 6) - 0.007(Age) - 0.852(Race 2) 

- 0.177(Race 3) - 0.008(Gender) + 0.186(Educational Level) 

+0.758(Lessons) + 0.784(Appreciation) + 0.625(Parents 2) 

+ 1.359(Parents 3) 

54 
 

The Audience for American Art Museums 

Table C
 

Logit Results Predicting the Probability
 

of Having Unsatisfied Demand
 

Significant at 

Variable Name Definition Coefficient .05 Level? 

Intercept	 -2.834 

Income 2	 = 1 if $4,999 < income < $10,000 +0.107 No 

= 0 otherwise 

Income 3	 = 1 if $9,999 < income < $15,000 +0.135 No 

= 0 otherwise 

Income 4	 = 1 if $14,999 < income < $25,000 +0.105 No 

= 0 otherwise 

Income 5	 = 1 if $24,999 < income < $50,000 +0.289 Yes 

= 0 otherwise 

Income 6	 = 1 if $49,999 < income +0.312 No 

= 0 otherwise 

Age = age in years ~3.007 Yes 

Race 2 = 1 if individual is Black ~).339 Yes 

= 0 otherwise 

Race 3 -- 1 if individual is "other" race ~).749 Yes 

= 0 otherwise 

Gender = 1 if female +0.315 Yes 

= 0 if male 

Educational Level = number of years of formal education +0.147 Yes 

SMSA 1 = 1 if live in central city of an SMSA +0.314 Yes 

= 0 otherwise 

SMSA 2	 = 1 if live in SMSA but not in central city +0.218 No 

= 0 otherwise 

Student = 1 if currently a student +0.290 No 

= 0 otherwise 

R2 = .05 

Logit Equation: 

If, P = Probability of attendance for a particular individual. 

Then, Natural logarithm (P/l-P) = - 2.834 + 0.107(Income 2) + 0.135(Income 3) + 0.105(Income 4) 

+ 0.298(Income 5) + 0.312(Income 6) - 0.007(Age) - 0.339(Race 2) 

-0.749(Race 3) + 0.315(Gender) + 0.147(Educational Level) 

+ 0.314(SMSA 1) + 0.218(SMSA 2) + 0.290(Student) 

55
 
Acknowledgments 

I would like to thank those individuals who served as my surrogate 

audience by reading and commenting upon drafts of this monograph: Harold 

Horowitz and Tom Bradshaw of the Research Division at the National 

Endowment of the Arts, as well as the staff of the NEA Museum Program; 

Pam Brusic, former Executive Director of the New England Museum 

Association; Gary Burger, former Director of the Berkshire Museum; Janet 

Saleh Dickson, Curator of Education, Yale University Art Gallery; and 

Professor Joe Ferreira, Department of Urban Studies and Planning, Massachusetts Institute of Technology. They have forced me to clarify both my 

thinking and my presentation. Thanks also to my colleagues Augustin Girard, 

Leif Gouiedo, and Marie-Charlotte de Koninck who provided me with 

comparable audience statistics for France, Sweden, and the province of 

Quebec. Jun Han served as my Research Assistant and handled the intracies 

of the computer programming with ease, competence, and good humor. 

56 
About the Author 

Dr. J. Mark Davidson Schuster is the Ida and Cecil Green Career 

Development Associate Professor of Urban Studies and Planning at the 

Massachusetts Institute of Technology where he teaches courses on quantitative reasoning, nonprofit institutions, and environmental design policy. 

His research focuses on government policy vis-?a-vis the arts, culture, and 

environmental design. He has written widely on issues of cultural policy and 

is author of Supporting the Arts." An International Comparative Stud)’, an 

analysis of arts funding patterns in eight countries, and coauthor with Alan 

Feld and Michael O’Hare of Patrons Despite Themselves: Taxpayers and 

Arts Policy, a Twentieth Century Fund Report on tax incentives for the arts. 

He and Milton Cummings are editors of Who’s to Pay for the Arts? The 

International Search for Models of Arts Support, a volume in the American 

Council for the Arts Research Seminar Series. He is a coauthor with Judith 

Blau of The Geography of Participation in the Arts and Government Funding 

also published by Seven Locks Press. He was a postdoctoral fellow in the 

Research Division of the French Ministry of Culture under the auspices of 

the United States-France Exchange of Scientists. More recently, he was 

named Fulbright Scholar and Distinguished Visitor to New Zealand under 

the auspices of New Zealand-United States Educational Foundation and the 

Queen Elizabeth II Arts Council. He has served as a consultant to the Arts 

Council of Great Britain, the British American Arts Association, the British 

Museum, the National Endowment for the Arts, National Public Radio, the 

American Council for the Arts, the Canada Council, the Massachusetts 

Council on the Arts and Humanities, and many other arts and cultural 

organizations. 

57
 
Other Publications of Interest 

Readers of this report may wish to obtain more information about the details 

of the study and about related research projects conducted for the Research 

Division of the National Endowment for the Arts. The following reports are 

available at libraries, bookstores or from their publishers: 

Socialization and Participation in the Arts 

Richard J. Orend 

Research Division Report #21 

54 pages 

National Endowment for the Arts (1989) 

Available from the American Council on the Arts, 1285 Avenue of the 

Americas, New York, NY 10019 

Who Reads Literature? 

Nicholas Zill & Marianne Winglee 

Research Division Report #22 

104 pages, 0-932020-86-0 

Seven Locks Press (1990) $9.95 

Expanding the Audience for the Performing Arts 

Alan R. Andreason 

Research Division Report #24 

64 pages, 0-929765-01-X 

Seven Locks Press (1991) $10.95 

In addition the following reports are available through the Education 

Research Information Center (ERIC) system: 

Dan Abreu, "Survey of Public Participation in the Arts, Musical Theater, 

Operetta, and Opera Attendees." April 1, 1987, ERIC Identification Number: 

ED 289 760. 

Carol Keegan, "Public Participation in Classical Ballet: A Special Analysis of 

the Ballet Data Collected in the 1982 and 1985 Survey of Public Participation in 

the Arts." April 30, 1987. ERIC Identification Number: ED 288 756. 

59 
David Waterman, "Public Participation in the Arts Via the Media." September 

1987, ERIC Identification Number: ED 290 674. 

Jerry West, "Public Participation in the Arts: Demands and Barriers." ERIC 

Identification Number: ED 287 764. 

Harold Horowitz, "The American Jazz Audience." ERIC Identification 

Number: ED 280 757. 

John Robinson, et al., "Public Participation in the Arts: Final Report of the 1982 

Survey." Survey Research Center, University of Maryland, January 1986. ERIC 

Identification Number: ED 264 168. 

John Robin son, et al., "Survey of Public Participation in the Arts: 1985 Volume I, 

Project Report." Survey Research Center, University of Maryland, March 1987. 

ERIC Identification Number: ED 289 763. 

Judith R. Blau, "The Geography of Arts Participation: Report on the 1982 and 

1985 Surveys of Public Participation in the Arts." March 1987. ERIC Identification Number: ED 289 762. 

Paul DiMaggio, "Race, Ethnicity and Participation in the Arts: Patterns of Participation by Black, Hispanic and White Americans in Selected Activities from 

the 1982 and 1985 Surveys of Public Participation in the Arts." June 1987. ERIC 

Identification Number: ED 293 759. 

J. Mark Davidson Schuster, "An Inquiry into the Geographic Correlates of 

Government Arts Funding." ERIC Identification Number: ED 298 023. 

The documents are the original research reports as prepared by the investigators. They contain extensive information about methods, and numerous tables 

and figures. The ERIC collection is available at hundreds of libraries in the United 

States and abroad, as well as "on-line" from computerized information services. 

Requests for information about the purchase of microfiche or photocopies 

of these reports should be sent to: ERIC Document Reproduction Services, 

Consumer Service, P.O. Box 190, Arlington, VA 22210. 

60 
The Audience for
 

American Art Museums
 

In the last decade, public and private contributors to 

the arts have taken as part of their mandate to increase both 

the number and the diversity of people who are exposed to 

the visual arts. Overall attendance figures and audience 

demographics have thus become increasingly important to 

museums. 

This study offers a series of profiles of the audience 

for American art museums and galleries based on an analysis 

of data from the 1985 Survey of Public Participation in the 

Arts and comparisons with several other sources. 

A survey report by 

J. Mark Davidson Schuster 

Massachusetts Institute of Technology 

N A T 1 0 N A L 

ENDOWMENT 

FOR~T H E Research Division Report #23 

ARTS 

ISBN 0-929765-00-1