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Full text of "The audience for American art museums"

The Audience 



« 

American Art Museums 



J. Mark Davidson Schuster 



NATIONAL 

endowment 

forW^the 



Research Division Report #23 A R 1 S 



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. Title. II. Series: 
Research Division report (National Endowment for the Arts. Research 
Division) ; 23. 
N510.S3 1990 

708. 13— <Ic20 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 

and the Arts Studies 10 
Comparing Participation Rates: 

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 pri- 
vate 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 


What portions of the population is the 


art museums as reflected in SPPA '85 


museum serving as compared to 


or in similar studies. 


museums on average? 


The profile of the overall population 


What segments of the population are 


or of the population in the museum's 


underrepresented in the museum's 


local area. 


audience? 


The profile of the museum's target 


Is the museum serving the segments 


population. 


of the population to which it has 




targeted its activities? 


The staff's impression of what the 


How well does the museum staff 


museum's audience profile is 


understand the composition of the 


currently. 


current audience? 




Is the programming promoted by the 




staff meeting the needs of the actual 




audience? 


The audience profile of other similar 


How does the museum's experience 


museums. 


compare to that of sister museums? 




Is the museum more successful or less 




successful than other museums at 




attracting particular groups to the 




museum? 


The audience profile of other nearby 


What are the other local educational 


"attractions." 


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? 


Changes in the museum's audience 


How has the audience profile 


profile over time. 


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? 



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 concern- 
ing 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 overall 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. 

Care 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. 



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 1 1 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 par- 
ticularly helpful in explaining the relative likelihood of attendance. Compar- 
ing 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 1 1 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 atten- 
dance 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 5 1 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, separat- 
ing students from non-students is once again important. While understand- 
ably 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 



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 



Overall 

Of all adults 



Participation Number Number 
Rate Attending in Category 



22% 



219 



1,000 



Income 

Of adults whose 
family income was 



$4,999 or less 
$5,000-$9,999 
$10,000-$ 14,999 
$!5,000-$24,999 
$25,000-$49,999 
$50,000 or more 



16% 
11% 
15% 
19% 
28% 
45% 



13 
14 
21 
47 
85 
42 



82 
126 
143 
247 
308 

94 









222 


1,000 


Education 










Of adults whose 


Grade School 


4% 


4 


110 


highest education 


Some High School 


71% 


8 


118 


level was 


High School Grad 


14% 


53 


376 




Some College 


29% 


60 


203 




Four-year College Grad 


45% 


50 


110 




Graduate School 


55% 


45 


82 








220 


1,000 


Age 










Adults whose 


18-24 years 


22% 


35 


161 


age was 


25-34 years 


25% 


61 


238 




35-44 years 


26% 


48 


182 




45-54 years 


23% 


30 


132 




55-64 years 


18% 


24 


130 




65-74 years 


16% 


16 


97 




75+ years 


10% 


6 

220 


59 
1,000 


Gender 










Of adult 


Female 


23% 


121 


528 




Male 


21% 


99 
220 


472 
1,000 


Race 










Of adults 


Black 


11% 


12 


108 




White 


23% 


203 


873 




Other 


26% 


5 

220 


19 
1,000 


Urbanization 










Adults who 


SMSA f and in Central City 


25% 


69 


271 


lived in 


SMS A but not Central City 


26% 


107 


413 




Area outside an SMS A 


14% 


44 


316 



220 



1,000 



Table 1 (Continued) 









Per 1,000 Adults 






Participation 


Number 


Number 






Rate 


Attending 


in Category 


Region 










Of adults who 


Northeast 


20% 


42 


209 


lived in the 


Midwest 


21% 


53 


252 




South 


19% 


64 


344 




West 


31% 


60 
219 


195 
1,000 


Subregion 










Of adults who 


New England 


24% 


13 


54 


lived in 


Mid Atlantic 


19% 


29 


155 




East Northcentral 


20% 


37 


182 




West Northcentral 


23% 


16 


70 




South Atlantic 


19% 


35 


180 




East Southcentral 


11% 


7 


66 




West Southcentral 


23% 


23 


98 




Mountain 


28% 


13 


46 




Pacific 


32% 


47 
220 


149 
1,000 


Selected States* 










Of adults who 


California 


32% 


36 


114 


lived in 


Florida 


20% 


9 


46 




Georgia 


17% 


5 


29 




Illinois 


23% 


11 


48 




Indiana 


23% 


5 


22 




Massachusetts 


25% 


6 


24 




Michigan 


21% 


9 


43 




New Jersey 


16% 


5 


31 




New York 


21% 


16 


75 




Ohio 


14% 


7 


50 




Pennsylvania 


14% 


7 


49 




Texas 


26% 


17 


64 




Virginia 


30% 


8 


27 




North Carolina 


13% 


4 


32 


Selected Occupations 










Of adults whose 


Professional 


49% 


44 


89 


occupation was 


Managerial 


37% 


32 


85 


classified 


Sales/Clerical 


27% 


64 


240 




Craftsman 


14% 


13 


91 




Operatives 


10% 


7 


73 




Laborers 


10% 


8 


80 




Service Workers 


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. 

'SMS A stands for Standard Metropolitan Statistical Area. 

4- 

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



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. (This 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 participa- 
tion 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 participa- 
tion rates whether or not they actually lived in the SMS A'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 some- 
what 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 metro- 
politan 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 SMS As in the West, 
and 33 percent outside of the central cities in the same SMS As. In addition, 
Boston has a participation rate of 26 percent, Baltimore/Washington, D.C. 
26 percent, Chicago 27 percent, and cities in Texas 3 1 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 Mas- 
sachusetts, 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 differ- 
ences 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 par- 
ticipation 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 



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 the Americans 
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 dis- 
crepancy 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' participa- 
tion rates are compared for each separate educational level, the discrepan- 
cies 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. More- 
over, 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 first treated with 
gratified astonishment and then were gradually incorporated into the estab- 
lished 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, 10 
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% 



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 



Income 



$4,999 or less 


16% 


43% 


$7,500 or less 


$5,000-49,999 


11% 


53% 


$7,501^$15,000 


$10,000-$14,999 ■ 


15% 


58% 


$15,001-$25,000 


$15,000-$24,999 


19% 


62% 


$25,001-$35,000 


$25,000-$49,999 


28% 


67% 


$35,001-$50,000 


$50,000 or more 


45% 


76% 


$50,001 or more 


Education 






Education 


Grade School 


4% 


27% 


Eighth Grade 


Some High School 


11% 






High School Grad 


14% 


46% 


High School Grad 


Some College 


29% 


70% 


Some College 


Four-year College Grad 


45% 


78% 


College Grad 


Graduate School 


55% 






Age 






Age 


18-24 years 


22% 


66% 


18-29 years 


25-34 years 


25% 






35-44 years 


27% 


62% 


30-49 years 


45-54 years 


23% 






55-64 years 


18% 


53% 


50-64 years 


65-74 years 


16% 


46% 


65+ years 


75+ years 


10% 






Gender 






Gender 


Female 


23% 


57% 


Female 


Male 


21% 


60% 


Male 


Race 




50% 


Race 


Black 


11% 


Black 


White 


23% 


59% 


White 


Other 


25% 


64% 


Hispanic 



12 



The Audience for American Art Museums 



Table 2 (Continued) 



Urbanization 



Size of Place 



SMSA Central City 
SMSA not Central City 
Outside SMSA 



25% 
26% 
14% 



66% 
58% 
49% 



Cities 

Suburbs 

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 SPPA. 11 This comparison shows very similar overall participa- 
tion 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 preceed- 
ing 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 participa- 
tion 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.) 12 



13 



Table 3-A 

A Cross-National Comparison of Participation Rates: 

The United States and Great Britain 



United States -— 1985 SPPA 

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



Great Britain — 1981 MORI 

Question: On another subject, which of 
these have you personally been to in the 
past 12 months? museum? 



Overall 



Age 



18-24 years 
25-34 years 
35-44 years 
45-54 years 
55-64 years 
65-74 years 
75+ years 

Gender 



Female 
Male 

Occupation 





Museum 


Art Exhibition 




Participation 


Participation 


Participation 




Rate 


Rate 


Rate 




22% 


29% 


19% 


Overall 
Age 


22% 


21% 


17% 


18-24 years 


25% 


34% 


17% 


25-34 years 


27% 


35% 


21% 


35-49 years 


23% 








18% 


29% 


20% 


50-64 years 


16% 


20% 


18% 


65+ years 


10% 









23% 
21% 



27% 
31% 



18% 
20% 



Gender 



Female 
Male 



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 Frangais '81 
Questions: 



Overall 

Education 

No Diploma 

Elementary School Grad 

Certificate 

Bachelor's Degree or more 

Age 

15-19 years 
20-24 years 
25-39 years 
40-59 years 
60-69 years 
70+ years 

Gender 

Female 
Male 

Socio-Professional Category 

Agriculture 

Small Merchant/ Artisan 

Wholesale and Industrial 

Professional and Managerial 

Middle Class 

Clerical 

Foreman 

Laborer or Service Worker 

Urbanization 

Rural 

Less than 20,000 residents 

20,000-100,000 residents 

More than 100,000 residents 

Paris 

Paris Region 



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 


30% 


21% 


14% 


7% 


21% 


10% 


34% 


25% 


57% 


49% 


40% 


26% 


38% 


27% 


34% 


29% 


28% 


18% 


27% 


15% 


14% 


9% 


30% 


22% 


30% 


21% 


17% 


8% 


32% 


26% 


49% 


33% 


61% 


53% 


53% 


40% 


32% 


28% 


24% 


18% 


20% 


13% 


20% 


13% 


26% 


19% 


28% 


21% 


33% 


23% 


56% 


50% 


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) 



Overall 

Education 

Pre-Secondary 

Secondary 

Post-Secondary 



Age 



16-24 years 
25—44 years 
45-64 years 
65-74 years 

Gender 

Female 
Male 

Socio-Economic Group 

All Workers 

Unskilled and Semi-Skilled Workers 

Skilled Workers 
All Salaried Employees 

Junior Salaried Employees 

Intermediate Level Salaried Employees 

Senior Salaried Employees 
All Entrepreneurs 

Entrepreneurs Without Employees 

Entrepreneurs With Employees 
Farmers 

Regions 

Stockholm 

Goteborg and Malmo 

Other Large Cities and Towns 

Other Southern and Central Sweden 

Northern Densely Populated Areas 

Northern Sparsely Populated Areas 

Source: Statistics Sweden, "Level of Living Survey 1982/83," as reported in Official 
Statistics of Sweden, Cultural Statistics: Activities, Economy and Cultural Habits 1980- 
1984 (Stockholm: Statistics Sweden, 1987), p. 340. 



16 





Museums and 


Art Exhibitions 


Exhibitions 


and Art Galleries 


(Other than Art) 


Participation 


Participation 


Rate 


Rate 


31% 


45% 


20% 


32% 


31% 


46% 


61% 


74% 


25% 


51% 


32% 


51% 


35% 


41% 


29% 


29% 


34% 


45% 


28% 


45% 


19% 


34% 


19% 


33% 


20% 


38% 


48% 


59% 


38% 


47% 


49% 


62% 


65% 


75% 


29% 


37% 


32% 


41% 


40% 


47% 


17% 


27% 


41% 


56% 


35% 


53% 


30% 


44% 


26% 


37% 


31% 


45% 


21% 


30% 



Table 3-D 
A Cross-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 
8-11 years 
12-15 years 
16+ years 

Income (Canadian $) 

$10,000 or less 
$10,000-$19,999 
$20,000-$29,999 
$30,000 or more 



Age 

15-17 years 
18-24 years 
25-34 years 
35-44 years 
45-54 years 
55+ years 

Gender 

Female 
Male 



Source: Ministere des Affaires Culturelles du Quebec, ChiffresaL'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. 



10% 


7% 


17% 


14% 


28% 


20% 


48% 


29% 


13% 


6% 


24% 


16% 


25% 


17% 


34% 


25% 


26% 


36% 


23% 


18% 


27% 


16% 


29% 


22% 


22% 


15% 


18% 


10% 


24% 


16% 


23% 


18% 



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 for 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 participa- 
tion 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 popula- 
tion being served is quite similar across countries, the frequency of attend- 
ance 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. 1 13 and the Quebec study a mean of 2. 1 1 . 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 separate 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 — in- 
come, 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 pre- 
dictor of museum attendance: participation rates ranged from 1 1 percent to 
45 percent. But when one controls for the influence of the other variables, 
the adjusted participation rate is roughly constant — approximately 20 per- 
cent — 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, par- 
ticularly 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 predic- 
tor 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 years 
45-54 years 
55-64 years 
65-74 years 
75+ years 

Gender 

Female 
Male 

Region 

Northeast 
Midwest 
South 
West 

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 vari- 
able by controlling for the effect of the others. 

** These rates differ slighdy from those in Table 1 because missing values necessitated 
dropping more cases from the analysis. 



20 



Participation 


MCA Adjusted* 


Rate 


Participation Rate 


22% 


22% 


16% 


22% 


11% 


19% 


15% 


19% 


19% 


20% 


28% 


24% 


45% 


32% 


4% 


7% 


8%** 


9% 


14% 


15% 


29% 


28% 


45% 


43% 


55% 


54% 


22% 


23% 


26%** 


25% 


27% 


24% 


23% 


21% 


18% 


20% 


17%** 


21% 


10% 


14% 


23% 


24% 


21% 


20% 


21%** 


21% 


21% 


21% 


19% 


21% 


31% 


28% 



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 mu- 
seums). 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 predic- 
tion — 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 R 2 statistic, 1 " which is .147 
here, indicating that 14.7 percent of the variation in participation rates is 
explained by the independent variables. 

Logit Analysis 

While multiple classification analysis focuses on the average value of the 
dependent variable for each value of each independent variable — explaining, 



fR is a "goodness of fit" measure of how well a model predicts the variation in the dependent 
variable. Measured on a scale of to 1, the closer R 2 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 participa- 
tion 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. 16 

Without 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 la 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 1a. 
Sample Attendance Data Graphed by Years of Education 



Yes = l 
Attendance 

No = 



■ ■ 



6 8 10 12 14 16 

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 1b 
Logit Curve Fitted to Sample Attendance Data 




Yes = l « 

Probability 

of 0.5 
Attendance 

No = ' 


■ ■ ■■■■■■! 


i 

i 


!■■■■■■ ■ ■ 1 




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 in- 
crease 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 prob- 
ability 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 signs of the seven other variables are positive. The positive coeffi- 
cients for the two highest income groups indicate that individuals in these 
groups (incomes of $25,000 and above) have a higher probability of attend- 
ance than individuals in lower income groups. The coefficient of education 
is also positive, 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 summary measure of how well the logit curve actually fits the data is 
R 2 . For this analysis R 2 = .16; sixteen percent of the variation in the 
dependent variable is explained by the independent variables in this model. 
While the R 2 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 con- 
tribution. 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 avail- 
ability 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 




l 

0.9 




0.8 






Attendance 

p p 






8M 

o 0.5 






S 0.4 
£ 0.3 

On 






0.2 






0.1 






°0 2 4 6 8 10 12 14 16 18 


Years of Education 







0.9 




0.8 


V 




<y 




S 


0.7 


A 




-o 




e 




4> 


0.6 


•t— ' 




< 




o 


0.5 


>> 




■** 




15 


0.4 


« 




A 




o 

1m 


0.3 


e- 






0.2 




0.1 








Figure 2b 

Logit Analysis— Graph of the Probability of Attendance 

by Age for Sample Individual 



10 



• •- 



30 



50 



70 



90 



Age 



26 



The Audience for American Art Museums 

Part II: 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 respon- 
dent 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 participa- 
tion 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 indi- 
vidual'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 6 1 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.? 





Participation 
rate 


Per 1,000 Adults 




Number 


Number in 
category 


All adults 
who had taken lessons 
who had not taken lessons 




22% 
45% 
15% 


219 
112 
110 


1,000 

248 
752 


Adults who first took 
lessons at less than 12 years 
12-17 years 
18-24 years 
25+ years 




62% 
37% 
54% 
40% 


21 
43 
30 
18 


33 

115 

56 

44 


Adults who attended an art museum 


50% had taken lessons 
50% had not taken lessons 


110 
109 


219 
219 


Adults who had not 
attended an art museum 




18% had taken lessons 
82% had not taken lessons 


137 
644 


781 
781 


Question: Have you ever taken a 


class 


in art appreciation or art history? 




All adults 
who had taken a class 
who had not taken a class 




' 22% attended 
51% attended 
15% attended 


219 
99 

122 


1,000 
194 
806 


Adults who first took a 
class at less than 12 years 
12-17 years 
18-24 years 
25+ years 




66% attended 
39% attended 
57% attended 
61% attended 


4 
26 
60 

8 


6 
68 

105 
14 


Adults who attended an art museum 


45% had taken a class 
55% had not taken a class 


98 

121 


219 
219 


Adults who had not 
attended an art museum 




12% had taken a class 
88% had not taken a class 


95 
686 


781 
781 



Question: Did your parents — or other adult members of the household — 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 then- 
parents are 35 percent and 14 percent, respectively. 

A logit model was run to see what happens to the probability of atten- 
dance 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 socializa- 
tion 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 



14 

c 
« 

■o 
c 



o 







6 8 10 

Years of Education 



12 



14 



16 



Example no. 1 

No Socialization Experiences 



• Example no. 2 
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 III: 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 

$5,000 or less 


25% 


21 


82 


$5,000-$9,999 


25% 


31 


126 


$10,00O-$14,999 


27% 


39 


143 


$15,00O-$24,999 


29% 


72 


247 


$25,00O-$49,999 


36% 


111 


308 


$50,000 or more 


45% 


42 


94 


Education 








Grade School 


12% 


13 


110 


Some High School 


22% 


26 


118 


High School Grad 


29% 


108 


376 


Some College 


38% 


77 


203 


Four-year College Grad 


44% 


48 


220 


Graduate School 


44% 


36 


82 


Age 








18-24 years 


34% 


55 


161 


25-34 years 


35% 


82 


238 


35-44 years 


35% 


63 


182 


45-54 years 


27% 


36 


132 


55-64 years 


28% 


36 


130 


65-74 years 


26% 


25 


97 


75+ years 


17% 


10 


59 


Gender 








Females 


33% 


173 


528 


Males 


28% 


134 


472 


Race 








Black 


25% 


27 


108 


White 


32% 


277 


873 


Other 


18% 


3 


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 $25,00O-$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 run. 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 de- 
mand 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 question- 
naire 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, 3 1 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 fre- 
quently cited barrier is not having enough time (13.7 percent of the popula- 
tion). 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 



33 



Table 7 

Barriers to Attendance at Art Museums 

and Art Galleries, 1 985 

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

Per 1,000 Adults 





Percent Citing 


Number Citing 


Number 




Barrier 


Barrier 


in Category 


Tickets sold out 








All Adults 


0.1% 


1 


1,000 


Attenders 


0.4% 


1 


219 


Non-Attenders 


0.0% 





718 


Cost 








All Adults 


4.0% 


40 


1,000 


Attenders 


5.7% 


13 


219 


Non-Attenders 


3.5% 


27 


718 


Not available 








All Adults 


6.4% 


64 


1,000 


Attenders 


11.4% 


25 


219 


Non-Attenders 


4.9% 


39 


718 


Too far to go 




- 




All Adults 


_ 6.7% 


67 


1,000 


Attenders 


13.9% 


30 


219 


Non-Attenders 


4.6% 


36 


718 


Transportation/Traffic/ 








Parking problems 








All Adults 


2.7% 


27 


1,000 


Attenders 


3.7% 


8 


219 


Non-Attenders 


2.5% 


19 


718 


Crime or fear of crime 








All Adults 


0.6% 


6 


1,000 


Attenders 


0.6% 


1 


219 


Non-Attenders 


0.6% 


5 


718 


Feel uncomfortable 








All Adults 


0.1% 


1 


1,000 


Attenders 


0.1% 


* 


219 


Non-Attenders 


0.1% 


1 


718 


Poor Quality/Not very good, 


etc. 






All Adults 


0.4% 


4 


1,000 


Attenders 


0.9% 


2 


219 


Non-Attenders 


0.3% 


2 


718 



34 



Table 7 (Continued) 





Percent Citing 
Barrier 


Per 1,000 Adults 




Number Citing 
Barrier 


Number 
in Category 


Don't have anyone to go with 

All Adults 
Attenders 
Non-Attenders 


1.6% 

2.2% 
1.4% 


16 

5 

11 


1,000 
219 
718 


Problem related to a handicap 

All Adults 
Attenders 
Non-Attenders 


0.4% 
0.5% 
0.3% 


4 
1 

3 


1,000 
219 
718 


Problem related to age/health 

All Adults 
Attenders 
Non-Attenders 


0.7% 
1.2% 
0.6% 


7 
3 
5 


1,000 
219 
718 


Babysitter problems/ 
Must care for children 

All Adults 
Attenders 
Non-Attenders 


1.7% 
3.5% 
1.2% 


17 
8 
9 


1,000 
219 
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 non- 
attenders 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? 





*ercent Citing 


Per 1,000 Adults 


I 


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% 


1 


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 








All adults with unsatisfied demand 


44.3% 


136 


307 


Attenders 


47.6% 


61 


129 


Non-Attenders 


42.0% 


75 


178 


Procrastination/Lack of motivation 








All adults with unsatisfied demand 


12.8% 


39 


307 


Attenders 


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 discom- 
fort and lack of quality remain unimportant barriers to participation; but cost, 
availability, distance, and lack of time are all of significantly higher impor- 
tance 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 motiva- 
tion," 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 microf actors 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 different individuals 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 dis- 
tributions 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 



Income t 








$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% 
100% 


19% 
100% 


27% 




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% 


35-44 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% 


100% 


100% 


Race 








Black 


11% 


5% 


3% 


White 


87% 


93% 


92% 


Other 


2% 


2% 


5% 




100% 


100% 


100% 


Urbanization 








Central City of SMS A 


27% 


31% 


45% 


SMS A but not Central City 


41% 


49% 


40% 


Outside an SMS A 


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 Popula- 
tion 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 1 985: Number per 1 ,000 Adults 





Adult Population 


Visitors 


Visits 


Income' 

$4,999 or less 


Of 82 adults, there 


were 13 visitors, 


making 66 visits 


$5,000- $9,999 


126 


14 


53 


$10,000-$ 14,999 


143 


21 


77 


S15,000-$24,999 


247 


47 


149 


$25,000-S49,999 


308 


85 


200 


$50,000 or more 


94 


42 


206 


Education 

Grade School 


110 


4 


7 


Some High School 


118 


8 


29 


High School Grad 


376 


53 


97 


Some College 


203 


60 


218 


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 


35^44 years 


182 


48 


170 


45-54 years 


132 


30 


105 


55-64 years 


130 


24 


62 


65-74 years 


97 


16 


54 


75+ years 


59 


6 


24 


Gender 




- 




Female 


528 


121 


392 


Male 


472 


99 


359 


Race 








Black 


108 


12 


23 


White 


873 


203 


693 


Other 


19 


5 


35 


Urbanization 








Central City of SMS A 


271 


69 


339 


SMS A but not Central City 


413 


107 


302 


Outside an SMSA 


316 


44 


110 



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 Popula- 
tion 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. 



40 



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 
School 



Some High 
School 



High 
School 



[ | Visitors 



Some 
College 

Population 



College 
Grad 



Graduate 
School 



SNN Visits 



Figure 4b 

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

Total Number of Visitors, Visits, and the Adult Population 



.a 
E 

3 

z 




Grade Some High High 
School School School 



Visitors 



Some 
College 

Population 



College Graduate 
Grad School 



S£3 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% 




S0-$5K 



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



[ 1 Visitors 



Population 



7 77\ 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 



S 30 



4> 

JO 




$0-$5K $5-$10K 

[ -J Visitors 



$10-$15K $15-$25K $25-$50K 
I Population 




$50K + 

Visits 



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. 20 

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 dramati- 
cally 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 au- 
dience 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 educa- 
tion — 1.60 — and highest for those with at least some graduate school educa- 
tion — 4.69. 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 


$15,000-524,999 


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 


0.24 


3.64 


High School Grad 


0.26 


1.84 


Some College 


1.08 


3.65 


Four-year College Grad 


1.71 


3.80 


Graduate School 


2.58 


4.69 



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

Note: The number 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 mu- 
seums 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 profes- 
sional 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 respon- 
dents. 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. 24 Though the documentation is not explicit as to how the calcula- 
tions 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 distribu- 
tions of visits are incorrect. Unless one wishes to argue that individuals in 
certain income groups or educational levels are more likely to overestimate 



45 



— I — __ 



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.LT. 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 Art Museum: 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 Review, Research Division 
Report #9 (Washington, D.C.: National Endowment for the Arts, No- 
vember 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 Univer- 
sity 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 pre- 
sented 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., Ameri- 
cans and the Arts: A Survey of the Attitudes Toward and Participation 
in the Arts and Culture of the United States Public (New York: As- 
sociated 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 Hanford, 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 Com- 
parisons 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, Sep- 
tember 1986), pp. 294-301); Ministere de la Culture, Service des Etudes 
et Recherches, Pratiques Culturelles des Frangais: Description Socio- 
Demographique— 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 [Kul- 
turstatistik] (Stockholm: Statistics Sweden, 1987); Ministere des Af- 
faires Culturelles du Quebec, Chiffres d L App ui, 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 
T 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%). 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. Ministere de la Culture, Service des Etudes et Recherches, Pratiques 
Culturelles des Frangais, p. 151. 



48 



The Audience for American Art Museums 



14. Ministere des Affaires Culturelles du Quebec, Chiffres d 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 Divi- 
sion, National Endowment for the Arts. 

1 6. A relatively readable presentation of logit 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 expecta- 
tions — "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. 
Pam Brusic has suggested that, ". . . today people are more burdened 
with personal than societal expectations — Tf I want to be a well- 
informed 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 re- 
spondents 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 extract- 
ing 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 respon- 
dent 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 
answers 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 respon- 
dents 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 percent- 
age 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; 



50 



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 Dilem- 
ma, Cambridge, Mass.: M.LT. 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 2.7 1 83) 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 to 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 



Variable Name 


Definition 


Coefficient 


Significant at 
.05 Level? 


Intercept 




-6.075 




Income 2 


= 1 if $4,999 < income < $10,000 
= otherwise 


-O.l 50 


No 


Income 3 


= 1 if $9,999 < income < $15,000 
= otherwise 


-0.123 


No 


Income 4 


= 1 if $14,999 < income < $25,000 
= otherwise 


-0.004 


No 


Income 5 


= 1 if $24,999 < income < $50,000 
= otherwise 


+0.201 


Yes 


Income 6 


= 1 if $49,999 < income 
= otherwise 


+0.563 


Yes 


Age 


= age in years 


-0.004 


Yes 


Race 2 


= 1 if individual is Black 
= otherwise 


-0.815 


Yes 


Race 3 


= 1 if individual is "other" race 
= otherwise 


-0.064 


No 


Gender 


= 1 if female 
= if male 


+0.355 


Yes 


Educational Level 


= number of years of formal education 


+0.328 


Yes 


SMSA1 


= 1 if live in central city of an SMS A 
= otherwise 


+0.689 


Yes 


SMS A 2 


= 1 if live in SMS A but not in central city +0.450 
= otherwise 


Yes 


Student 


= 1 if currently a student 
= otherwise 


+0.393 


Yes 



R =.16 



Logit Equation: 



If, P = Probability of attendance for a particular individual. 

Then, Natural logarithm (P/l-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(Race2) 
- 0.064(Race 3) + 0.355(Gender) + 0.328(Educational Level) 
+ 0.689(SMSA 1) + 0.450(SMSA 2) + 0.3 93 (Student) 



53 



J. Mark Davidson Schuster 

Table B 

Logit Results Predicting the Probability of 

Attendance with Socialization Variables 



Parents 2 



Parents 3 



R 2 = .22 



in art history or appreciation 
= otherwise 

= 1 if parents took individual to arts 
museum occasionally 
= otherwise 

= 1 if parents took individual to arts 
museum frequently 
= otherwise 



Significant at 



Variable Name 


Definition 


Coefficient 


.05 Level? 


Intercept 




-4.137 




Income 2 


= 1 if $4,999 < income < $10,000 
= otherwise 


-0.316 


No 


Income 3 


= 1 if $9,999 < income < $15,000 
= otherwise 


-0.091 


No 


Income 4 


= 1 if $14,999 < income < $25,000 
= otherwise 


-0.196 


No 


Income 5 


= 1 if $24,999 < income < $50,000 
= otherwise 


+0.144 


No 


Income 6 


= 1 if $49,999 < income 
= otherwise 


+0.540 


Yes 


Age 


= age in years 


-0.007 


Yes 


Race 2 


= 1 if individual is Black 
= otherwise 


-0.852 


Yes 


Race 3 


= 1 if individual is "other" race 
= otherwise 


-0.177 


No 


Gender 


= 1 if female 
= if male 


-0.008 


No 


Educational Level 


= number of years of formal education 


+0.186 


Yes 


Lessons 


= 1 if individual has ever taken 








visual arts lessons 


+0.758 


No 




= otherwise 






Appreciation 


= 1 if individual has ever taken course 







+0.783 



+0.625 



+ 1.359 



No 



Yes 



Yes 



Logit Equation: 

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(Parents3) 



54 



The Audience for American Art Museums 

Table C 

Logit Results Predicting the Probability 

of Having Unsatisfied Demand 



Variable Name 


Definition 


Coefficient 


Significant at 
.05 Level? 


Intercept 




-2.834 




Income 2 


= 1 if $4,999 < income < $10,000 
= otherwise 


+0.107 


No 


Income 3 


= 1 if $9,999 < income < $15,000 
= otherwise 


+0.135 


No 


Income 4 


= 1 if $14,999 < income < $25,000 
= otherwise 


+0.105 


No 


Income 5 


= 1 if $24,999 < income < $50,000 
= otherwise 


+0.289 


Yes 


Income 6 


= 1 if $49,999 < income 
= otherwise 


+0.312 


No 


Age 


= age in years 


-0.007 


Yes 


Race 2 


= 1 if individual is Black 
= otherwise 


-0.339 


Yes 


Race 3 


= 1 if individual is "other" race 
= otherwise 


-0.749 


Yes 


Gender 


= 1 if female 
= if male 


+0.315 


Yes 


Educational Level 


= number of years of formal education 


+0.147 


Yes 


SMSA1 


= 1 if live in central citv of an SMS A 


+0.314 


Yes 



= otherwise 

= 1 if live in SMS A but not in central city +0.218 
= otherwise 



= 1 if currently a student 
= otherwise 



+0.290 



No 



No 



SMS A 2 

Student 

R 2 = .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) + 0.3 15(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, Mas- 
sachusetts 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 quan- 
titative 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 Study, 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 a!., "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 Robinson, 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 Identifica- 
tion Number: ED 289 762. 

Paul DiMaggio, "Race, Ethnicity and Participation in the Arts: Patterns of Par- 
ticipation 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 investi- 
gators. 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 



NATIONAL 

endowment 

forMthe 



S^r? 



ARTS 



Research Division Report #23 



Seven Locks Press 

Washington, D.C. 



78 



929"765 



06 



5 10 



95 



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