Omnivores Show up AgainThe Segmentation of Cultural Consumers inSpanish Social Space

JordiLo¤ pez Sintas andErciliaGarc|¤ aA¤ lvarez

The sociological analysis of the consumption of cultural products predicts a relationship between

social class and lifestyle.We used a new exploratory methodology based on latent class models to

analyse the strati¢cation of cultural product consumption.We discovered four segments of Spanish

consumers based on their cultural lifestyle: the no cultural activity class, the popular class, the

highbrow class, and the omnivore class.The Spanish omnivore class is associated with the highest

social class indicator and level of education, is younger than the highbrowclass, and contains just as

many women asmen.

The Consumption of Cultural ProductsThe sociological analysis of the consumption ofcultural products predicts a relationship betweensocial class and lifestyle (Bourdieu, 1979; DiMaggioand Useem, 1978). However, according to van Rees,Vermunt and Verbood (1999), most of the researchcorpus has not analysed this relationship accurately.In some cases the consumption of, or preferencesfor, cultural products has been related to di¡erentsocial classes based on occupation (DiMaggio, 1982;Peterson andSimkus,1992; Peterson andKern,1996)instead of ¢rst obtaining homogeneous patterns ofconsumption (lifestyles) within each segment ofconsumers but di¡erent among them; and, secondly,analysing the relationship between these clusters oflifestyles and the individuals’ position in socialspace. Other research has looked for clusters of cor-related products that can be labelled as highbrow orlowbrow and then tried to establish a correlation oran association with di¡erent socioeconomic vari-ables (Bourdieu, 1987; Katz-Gerro and Shavit, 1998;Katz-Gerro,1999). Recently some authors have evenproposed that the upper social class participates notonly in high culture but also in popular culture,often at levels equivalent to the lower social classes

(DiMaggio, 1987), naming the former high-classomnivore and the latter low-class univore (Petersonand Simkus, 1992; Peterson and Kern, 1996).

These ways of proceeding provide valuable in-sights into the association between theconsumption of cultural products and di¡erentsocioeconomic statuses. However, the results arenot strong enough because the researchers havefailed to associate di¡erent lifestyles (characterizedby their behaviour, as sociological theory proposes)with di¡erent social classes. Our aim is twofold:¢rst, to analyse Spaniards’ consumption of culturalproducts by measuring the di¡erent lifestyles thatcan be found in their behaviour; and secondly, toanalyse the association between these lifestyles anddi¡erent socioeconomic variables.

Theoretical Approaches and PredictionsThe Strati¢ed Consumption of Culture

According to Bourdieu (1979,1989), the sociologicalanalysis of consumption can be broken down intothree spaces: (1) structural, (2) symbolic, and (3)

&Oxford University Press 2002

European Sociological Review,Vol. 18 No. 3, 353^368 353

habitus or taste. The structural space comprising theconditions and positions of the subjects insociety ^ their social class ^ is formed primarilyby capital that can be classi¢ed as cultural, social,and economic. In short, social class is a shared socialsituation with regard to control over goods andresources in markets (Hout, Brooks, and Manza,1993).

The symbolic space, on the other hand, refers tothe status group, the lifestyles, and the productsconsumed that connote individuality of taste anda distinctive choice of activities associated withspeci¢c groups (DiMaggio, 1987). Product charac-teristics are desired precisely for their symbolicproperties, for their relationship to the consumer’sdesire for distinction in social class (Peterson,1997a:71). The symbolic space can be divided into sub-spaces such as the consumption of culturalproducts. Common lifestyles indicators in the socio-logical literature on cultural consumption include,among others, cultural tastes related to clothing andhousehold appliances (Holt, 1997), music (Petersonand Simkus, 1992), reading habits (van Rees et al.,1999), and outdoor leisure activities (Katz-Gerroand Shavit, 1998; Katz-Gerro, 1999; Bihagen andKatz-Gerro, 2000).

Lastly, the habitus space includes schemes of per-ception and evaluation of daily habits, cognitivestructure, and evaluation that are acquired fromrepetitive experience with the consumer’s condi-tions and positions in the social context. Thehabitus space a¡ects the chances of attaining desir-able rewards in processes of social strati¢cation(DiMaggio,1982). People internalize it, determiningcultural as well as material choices that reproducethe very class structure itself (De Graf, 1991). Thedecisions made by social groups are governed bytheir own particular evaluation patterns, their tasteor habitus structure (DiMaggio, 1982). As a result,the latter relates and explains the decisions made byconsumers of a certain social class (Bourdieu, 1979).

The main proposition derived from Bourdieu’stheory as well as DiMaggio and Useem’s is that theconsumption of cultural products will be strati¢edin a homologous way as the society is strati¢ed intodi¡erent social classes (Bourdieu, 1979; DiMaggioand Useem, 1978). Since high arts are primarily thepreserve of the upper and upper-middle classes,di¡erential class exposure rates to the high arts have

the e¡ect of reinforcing class cohesion (DiMaggioand Useem, 1978; DiMaggio, 1987; Ostrower, 1998)and distinction, such that the consumption of thehigh arts will vary sharply by class.

Many recent investigations give support to thehomology thesis. Research conducted in the sym-bolic space of cultural consumption have commonlyused an interviewee’s socioeconomic status (SES)as an indicator of his or her position in social space(it is considered a good indicator of social class(Bourdieu, 1987: 4)) to analyse its impact on his orher consumption of cultural products. For instance,Peterson and Simkus (1992) analysed the associationbetween musical preferences and occupation andfound that high status occupation was more closelyrelated to high cultural musical tastes. Katz-Gerro(1999: 637); a study of leisure activities and musicaltastes based on the1991General Social Survey in theUSA found that lifestyle and cultural tastes aremarkers of social distinction and social status.Theseresults are along the same lines as those found byKatz-Gerro and Shavit (1998) and Bihagen andKatz-Gerro (2000), who concluded that social class(SES indicators) apparently has a signi¢cant e¡ecton cultural consumption, even after controlling forother variables.

Nevertheless, as the concept of Bourdieu’s (1979)structural space is more complex than the way ithas been operationalized by indicators of inter-viewees’ SES, some authors have elaborated thesocial class concept including cultural, social, andeconomic capital as well. For example, Anheier,Gerhards, and Romo (1995) studied whether di¡er-ences in capital endowments are in fact related to thesocial structure of cultural ¢eld (literary) and alsofound support for Bourdieu’s claim: cultural capitalproved to be the dominant factor inwriters’di¡erentsocial positions.

Reproduction Versus Mobility Models

Most of an individual’s cultural capital comesfrom his or her family. The socialization processundergone in one’s family naturally reproduces(unconsciously) the taste for consuming those cul-tural products that symbolizes the family’s socialclass. Parents usually show their children placesand activities that they enjoy (van Eijck, 1997).Thisparental behaviour reproduces the taste for cultural

354 LOPEZ SINTAS ANDGARCIA ALVAREZ

products and the knowledge of a special way ofbehaving and interacting according to the socialcontext of cultural consumption.1 Van Eijck (1997)has found that family background (father’s SES andeducation, and mother’s education) is the strongestdeterminant of siblings’cultural participation, evena better predictor than interviewee’s educationallevel, concluding that the e¡ect of an interviewee’seducational level is biased, if not controlled, byparental SES and cultural resources.

On the other hand, cultural resources transmittedthrough a socialization process in families thatbene¢t from a high social position could also beacquired by formal education. This cultural invest-ment (formal education) may have its own reward.DiMaggio (1982), when analysing the impact ofhigh-status culture participation (cultural capital)on school success, proposed and found supportfor two models of cultural capital returns: (1) thecultural reproduction model and (2) the cultural mobilitymodel. The former proposes that returns to culturalcapital are highest for students from high-statusfamilies and lowest for students from low-statusfamilies. The second suggests that returns to cul-tural capital are highest for students who are leastadvantaged, being a practical and useful strategyfor low-status students who aspire towards upwardmobility (DiMaggio, 1982: 190). He found thatfemales from high social-class backgrounds (mea-sured by their fathers’ socioeconomic status)received more returns to their cultural capital(measured by their participation in cultural activ-ities) than females from lower social classes. Heperformed the same analysis for males, ¢nding thereverse result. He concluded that females followeda cultural reproduction model and that malesadhered to the cultural mobility model.

Several authors have pointed to the possibility thatthe rise of the market has greatly eroded the statusorder, so that the salience of social class factors isdeclining and consumption patterns are becomingmore fragmented (Gartman, 1991; Featherstone,1992; Clark and Lipset, 1991; Clark, Lipset andRempel, 1993; Pakulski, 1993; Bihagen and Katz-Gerro, 2000). In consequence thehomologybetweensocial class and status, they propose, is more di¡useand more loosely bounded, and they suggest thatone should look for other variables that could stratifythe social interaction, for instance, gender.

There are two main arguments that predictwomen’s higher cultural consumption. On the onehand, if we consider men’s over-representation inthe dominant classes (they are order givers), and weacknowledgewomen’s less favourable position in theclass hierarchy (they are order takers), we wouldexpect women to consume more high culture thanmen in order to be respectable. On the other hand,Collins (1992) suggests that the management ofsymbolic status is a feminine speciality, given thatwomen are often employed in occupationsconcerned with the presentation of the self. Mostempirical evidence lends support to the conclusionthat women participate in high culture more thanmen (Lamont and Fournier, 1992; Lamont et al.,1996; Bryson, 1996; Katz-Gerro and Shavit, 1998;Katz-Gerro, 1999; Bihagen and Katz-Gerro, 2000;Van Erijck, 1997).

However, the constraint model argues that mar-ried women, mothers, and homemakers experiencethe strongest constraint on their leisure. For them,cultural consumption is not only more restrictedin time but also home-centred (Green et al., 1990).From this point of view, the constraint modelimplies that women would consume less highbrowculture than men would, an argument that, as wehave seen, appears to be contrary to empiricalevidence. Nevertheless, the constraint model maybe useful for understanding consumption di¡er-ences among women in di¡erent marital statuses.We would expect di¡erences in cultural consump-tion among single and married woman with andwithout children or elderly relatives living at home.

Omnivore Versus Univore Consumers

DiMaggio (1987) reported evidence that is notentirely consistent with the homology thesisbetween high position in a social space and theconsumption of high culture products: thereappear to be no rigid class boundaries in the con-sumption of popular and high culture. DiMaggioproposes that the variety of cultural products that aperson consumes is a function of his or her socio-economic status (1987: 444). Although the upperclass clearlyhasmore knowledge of, and participatesmore in, high culture, research has also consistentlyshown that its members also participate in popular

SEGMENTATIONOF CULTURALCONSUMERS IN SPANISH SOCIAL SPACE 355

culture, often at levels equivalent to the lower socialclasses.

For this reason, Peterson and Simkus (1992) andPeterson and Kern (1996) advanced the existence oftwo main types of consumers of cultural products:(1) high-class omnivore and (2) low-class univore.They proposed that omnivores have developed aliking for both highly classi¢ed and popular cul-tural genres, while the univore types stick only toa few kinds of cultural genres, whether high orpopular. Thus, social status is gained not only byconsuming prestigious forms of art, but also byshowing o¡ one’s cultural knowledge in a widevariety of genres (DiMaggio, 1987; Peterson andSimkus, 1992; Peterson and Kern, 1996). In contrast,high-class univores (snobs, according to Petersonand Kern, 1996) only show a liking for high art,high cultural performing art. They conclude thatthe ¢rst type seems to be replacing snobbishnessamong Americans of highbrow status. Recently,van Rees et al. (1999) also found support for theomnivore hypothesis in the Dutch population.

Nevertheless, Bryson (1996) pointed out that onceone applies the idea of omnivores to groups ofrespondents who state their music preferences (asis the case with the research by Peterson andSimkus, 1992), the meaning of the term omnivoreis immediately transformed into a more restrictednotion. Bryson extended the ¢nding that educationincreases political tolerance to cultural tolerance.He proposes that the predicted e¡ect of educationis to reduce musical exclusiveness, just as it reducespolitical intolerance, and income and occupationalprestige are expected to have little or no e¡ect onmusical exclusiveness when the impact of educationis held constant (Bryson, 1996: 877). His ¢ndingssuggest that the apparently tolerant tastes of edu-cated respondents may mask a systematic dislikeof music genres whose audiences have lower thanaverage levels of education.

Some Critical Issues

Cultural consumption research, according to vanRees et al. (1999), has failed to meet a number ofconditions to be able to maintain the claim of thegrowing omnivorousness of higher status groups.The work of Peterson and Simkus (1992), forinstance, relies on preference data towards music,

not actual behaviour, measured at the aggregatelevel of occupational status. Peterson and Kern(1996) also rely on preference data towards music,and classify people as being highbrow if they likeopera and classical music. Bryson (1996) uses thenumber of genres disliked regressed on some socio-economic status covariates, demographic variables,and a measure of political intolerance. Katz-Gerro(1999) and Katz-Gerro and Shavit (1998), usedactual behaviour and preferences, but did notlook for clusters of lifestyles; they regressed clus-ters of cultural products found through the use ofprincipal components factorial analysis on somesocioeconomic variables. Bihagen and Katz-Gerro(2000) used data on highbrow leisure activitiesand lowbrow TV-watching preferences in Swedento ¢nd factors of closely related cultural activities(clusters of products that form a scale of highbrowproducts, lowbrow leisure and music, in theirresearch, based on the correlation shown betweenindicators and factors), and then regressed thosefactors on several socioeconomic covariates.

Instead, van Rees etal. (1999) proposed that socio-logical research on cultural consumption should:1. draw on a broad range of cultural practices and

preferences;2. measure people’s actual behaviour rather than

their declared preferences and do so at an indivi-dual level rather than the aggregate level ofoccupational status;

3. include a well-argued analysis of how culturalclassi¢cation and cultural strati¢cation are inter-dependent and how they change over time; and

4. in applying labels such as omnivore and univoreand classifying people according to their cul-tural behaviour, maintain an awareness that themeaning of the notion of omnivore is alwaysbounded by the cultural activities (products)used as indicator of clusters of lifestyle.

This is the research design that we will apply.

Research DesignResearch Questions

Wewere interested in ¢nding clusters of behaviours(lifestyles) that we can characterize by their patternof performed cultural activities and not in ¢ndingclusters of products (as in research based on a

356 LOPEZ SINTAS ANDGARCIA ALVAREZ

factorial analysis of cultural products). Once wehave these clusters of lifestyles we have to interpretthem. To help us in this task, we look for a way topro¢le and plot these clusters of lifestyles, so thatwe can label each one according to its associationwith manifest cultural indicators. Finally, we try to¢nd a relationship among lifestyles and some exter-nal variables identi¢ed in the literature review andrelated to the interviewee’s position in Spanishsocial space. In particular, we try to ¢nd answers tothe following questions:

^ Can we classify Spanish consumers of culturalproducts according to their behaviour ?

^ Can we ¢nd any association between clusters oflifestyles and social strati¢cation?

Sample

The data were obtained from the Culture asConsumption survey requested by the Centre forResearch on Social Reality (CIRES) in 1994. Thesurvey conducted home interviews of 1200 indivi-duals of either sex, 18 years old and over, living inSpain. It is a random sample, strati¢ed by auto-nomous regions and municipalities according totheir size. Other technical characteristics of thesample are described in CIRES (1994).

Lifestyle indicatorsThis article analyses eight indicators of culturalactivities, all practised during the last 12 months.Interviewees were asked ‘Did you go to any of thefollowing cultural activities within the past twelvemonths?’ These cultural activities are listed inTable 1, along with their frequency in the sample.

Explanatory variablesSocial class. We approximate social class throughthe Erikson^Goldthorpe procedure, EGP, (Evans,1992), as it is being used for analysing the relation-ship between social class and cultural consumption(Katz-Gerro and Shavit, 1998; Katz-Gerro, 1999;Bihagen and Katz-Gerro, 2000). We transformedthe original CIRES codi¢cation into an EGP classclassi¢cation with ¢ve categories: employees with aservice relationship (categories 1 (service 1) and 2(service 2)); routine and non-manual employees(category 3 (Non manuals)); entrepreneurs (category

4, including employers and self-employed workers);and, ¢nally, manual workers (category 5, includingskilled employees with a labour contract and semiand unskilled workers). In addition, we includedtwo more categories: category 6, the unemployedand those ‘not in the labour force’ (economicallyinactive, retired people, and otherswho are unclassi-¢ed); and category 7, students. As far as the father’ssocioeconomic class classi¢cation is concerned, wefollowed the same scheme except for the studentcategory.

Education. We formed the following four educa-tional categories: category1 ^ primary education orless; category 2 ^ low secondary school, vocational,and general education; category 3 ^ high secondaryschool, vocational, and general education (thislevel allows entrance to university); and category4 ^ college (3 years of university) and universitydegrees (4 or 5 years).

Marital and parental status. This variable has fourcategories: 1¼single, 2¼single with children ordependants, 3¼married, 4¼married with childrenor elderly dependants.

Control variablesAge. Many authors have found that there seemsto be a generational e¡ect in the consumption ofculturalproducts.To control for this e¡ectwe formedseven age categories: category 1: under age 25; cate-gory 2: age 25^34; category 3: age 35^44; category 4:age 45^54; and category 5: over age 54.

SEGMENTATIONOF CULTURALCONSUMERS IN SPANISH SOCIAL SPACE 357

Table 1. Indicators of cultural activities

Outdoor cultural

activities Frequency

Percentage

of attendance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

(1) Museums 272 22.67(2) Art galleries 215 17.92(3) Historical monuments 264 22.00(4) Book fairs 226 18.83(5) Craft fairs 187 15.58(6) Trade fairs 185 15.42(7) Lectures 137 11.42(8) Music/theatre festivals 153 12.75

Urbanstatus. In order to control for the in£uence ofliving in a city on a consumer’s exposure to highculture ^ as found by Blau, Blau, and Golden(1985) and Lamont et al. (1996) ^ we formed fourcategories: category 1: less than 100,000 inhabitants;category 2: 100,00^250,000; category 3: more than250,000; and category 4: Barcelona or Madrid.

Analysis

To answer the ¢rst research question we con-ducted an unsupervised classi¢cation. We de¢neda latent class model (McCutcheon, 1987; Heinen,1996; Dayton, 1998) for our eight indicators ofcultural activities. As Lazarsfeld and Henry (1968)put it, the aim of a latent class model is to introducelatent variables that account for the observed patternof association between the manifest variables. Alatent class model splits the original sample intoTclusters or classes such that the original associa-tion observed in the whole sample between goers tomuseums and art galleries, for instance, is removedfrom the classes or clusters. That is, the observedpatterns of cultural activities are assumed to beindependent given that latent class membershipis taken into account.

Once we had the estimated number of classes ofpatterns of cultural consumption, we pro¢led theindicators of cultural activities to be able to visuallycharacterize each cluster of consumers (MadigsonandVermunt, 2000;Vermunt and Madigson, 2000).Finally, we conducted an exploratory latent classmodel with active and inactive concomitant vari-ables in order to analyse the association of theclusters found with the variables suggested by theliterature review (Hagenaars, 1990; Madigson andVermunt, 2000;Vermunt and Madigson, 2000).

FindingsLooking for a Taxonomy of Consumers

of Cultural Products

Model formulationDe¢ning cs¼{a,b,c,d,e,f,g,h} as the vector ofresponses to the eight cultural activities for the sthpattern of possible vectors of responses (28), thelatent class model can be formulated in two steps(Dayton, 1998). First, for any response pattern of

cultural activities, cs, the probability of observing it,assuming consumer membership in latent class t, is

p(csjt) ¼ pABCDEFGH Xabcdefght ¼

Y

8s, �SS

p�SS,Xs, t

where the overbar on variables such as �AA indicatesthat it is conditioned to the latent variable (thesame for the rest of the variables), and s andS overbarstand for each one of the eight conditioned culturalindicators.

The second step formulated the unconditionalprobability of observing a cultural pattern of con-sumption, cs, as aweighted sum across latent classes:

p(cs) ¼XT

t¼1

pXtY

8s, �SS

p�SS,Xs, t

Maximum likelihood is the conventional approachto estimate the parameters of equation (2) by formu-lating the following likelihood function:

L ¼Y28

s¼1

p(cs)nn .

Model selectionTo estimate the parameters of the latent class modelwe usedVermunt’s general program for the analysisof categorical data, LEM(Vemunt,1997), andLatent-Gold (Vermunt and Madigson, 2000). InTable 2 wereport some measures for goodness of ¢t (Vermunt,1997: 21^2; Vermunt and Madigson, 2000: 169^170): the chi-squared likelihood-ratio statistic (L2),the consistent Akaike information criteria (CAIC),and the Bayesian information criteria (BIC), bothbased on L2.The likelihood-ratio statistic indicatesthe amount of the relationship between the indi-cators that remains to be explained: the smaller L2,the better the ¢t of the model. BIC and CAIC, onthe other hand, look for parsimonious models: thelower the BIC or CAIC, the better the model.Nevertheless, one consideration must be stated forthese statistics. Although the likelihood-ratio sta-tistic is appropriate to test nested models, it is notadequate for comparing models based on di¡erentnumbers of latent classes (Dayton, 1998: 17; Wedeland Kamakura, 1998: 89^90), as is the case when wecompare latent class models with di¡erent levels orclusters. For this reason we must rely on statisticaltests based on information criteria (CAIC and BIC).

358 LOPEZ SINTAS ANDGARCIA ALVAREZ

Models 4 and 5 seem to be close to a correctmodel, althoughwe must relyonAkaike’s consistentinformation criteria and the Bayesian informationcriteria (Agresti, 1990: 246; Dayton, 1998: 18^20) toselect the correct model. Both statistics point tomodel 4 as the best one, the one that conveys themost information with the lowest number of para-meters. The likelihood-ratio chi-squared test alsostates that there is no association left to be explained(at a p-level of 5 per cent we cannot reject the hypo-thesis of independence among cultural activitiesindicators when we take into account membershipof the latent class levels).

ModelparametersTable 3 shows the parameter estimates for the four-cluster model. The ¢rst row shows the cluster size,p̂pXt , and the following rows give the probability ofbelonging to a particular category of cultural orleisure activities given one’s score on the cluster,p̂p �SS,Xs, t (level of the latent variable). For instance, if

one interviewee has been assigned to cluster 1, heor she has a 96 per cent probability of not going toanymuseum and therefore a 4 per cent chance of hav-ing gone to somemuseum.On the other hand, if theinterviewee has been allocated to cluster 4, his orher probability of going to museums is expectedto be really high, 87 per cent, with a 13 per centpossibility of not going. For the members of cluster3, there is a 96 per cent likelihood of attending and 4per cent chance of not going. Based on these condi-tional probabilities we can characterize theprobabilistic behaviour of the Spanish respondentsregarding to this set of eight cultural indicators.

The estimated model suggests that in the Spanishpopulation there is a very large group, the no culturalactivity class, that spends very little of their leisuretime attending or going to any high cultural exhibi-

tion (museums, artgalleries, lectures,ormonuments)or popular cultural events (book, craft, or trade fairs,or theatre and music festivals). Two rather smallgroups, the popular and the omnivorous classes, do goand attend popular cultural activities (book, craft,and trade fairs, and festivals of theatre and music).However, they have very di¡erent patterns of high-culture product consumption.The popular class has avery low chance of going to museums and a lowprobability of going to art galleries or exhibitionsand attending lectures. On the other hand, the omni-vorous class has the highest chance of attending thesecultural activities. Finally, highbrow cultural consu-mers have a high probability of consuming high-culture events and popular events with the highestcultural content (book fairs).

Visualizing the clusters’pro¢leTable 3 shows the probability of observing a patternof activities as a weighted sum across latent classesand the probability of attending each of these eightcultural activities conditioned to be in latent classlevel t:

p̂p(cs) ¼XT

t¼1

p̂pXtY

8s, �SS

p̂p�SS,Xs, t .

If, however, we had the probability of being in eachone of the four consumer classes conditioned togoing, and not going, to the museum, art galleries,and so on until the eight indicators, we would beable to obtain the pro¢le of each indicator.This pro-cedure would be equivalent to estimating the rowpro¢les in correspondence analysis (Greenacre,1993). Pro¢les would show how the positive (goingto) and negative (not going to) responses to eachindicator are distributed among the four consumerclasses, and the class size would now stands for the

SEGMENTATIONOF CULTURALCONSUMERS IN SPANISH SOCIAL SPACE 359

Table 2. Goodness-of-¢tmeasures formodel selection

L2 CAIC BIC df. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Model 1 1-Cluster 2028.93 (0.00) 30.68 277.68135 247Model 2 2-Cluster 479.42 (0.00) �1446.02 �1208.0145 238Model 3 3-Cluster 364.74 (0.00) �1480.37 �1258.8870 229Model 4 4-Cluster 254.36 (0.06) �1525.46 �1305.4610 220Model 5 5-Cluster 229.25 (0.19) �1477.76 �1266.7595 211

cluster or row mean pro¢le. In that case we can dis-play the clusters and their characteristics using atriangle called a regular simplex with three vertices(Grenacre, 1993: 13). To obtain the pro¢le of eachindicator, we need the conditional probability ofbeing in cluster no cultural activity, t, conditioned tohave answered positively to going to museums, a,p(tja), de¢ned as the joint probability of being inthe class no cultural activity and having answered yesto going to museums, divided by the probability ofanswering yes to going to museums,

p(tja) ¼p̂pAXa, tp̂pAa

¼p̂pXt p̂p

�XX,At, a

XT

t0¼1

p̂pXt0 p̂p�XX,At0, a

so that

XT

t¼1

p(tja) ¼ 1

(see van der Ark and van der Heijden, 1998: 502;van der Heijden, Gilula and van der Ark, 1999:176; and Madigson and Vermunt, 2000: 23; forfurther details).

Figure 1 displays the tri-plot and shows theindicator pro¢les.These sixteen pro¢les (eight indi-cators by 2 levels) all lie in the plane de¢ned by thetriangle that joins the extreme points (1,0,0), (0,1,0),and (0,0,1) on the three respective axes. Of course, aswe have four classes or clusters we have to sum upthe pro¢les of two classes (omnivore and highbrowclasses in this case). The conclusions, nevertheless,that we arrive at are the same, hence the tri-plotcomplements the analysis already done and permitsa visual representation.

To characterize each cluster we have to look atthe levels of each indicator (its pro¢le) and see ifit is greater than its mean overall probability. Thearrows in the ¢gures point to the cluster to which

360 LOPEZ SINTAS ANDGARCIA ALVAREZ

Table 3. Parameter estimates for the four latent classesmodel

Cluster 1

No cultural activity

Cluster 2

Popular culture

Cluster 3

Omnivorous

Cluster 4

Highbrows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cluster size 0.67 0.12 0.12 0.09Museums

No 0.96 0.93 0.04 0.13Yes 0.04 0.07 0.96 0.87

Art exhibitionsNo 0.97 0.80 0.30 0.40Yes 0.03 0.20 0.70 0.60

MonumentsNo 0.96 0.68 0.06 0.52Yes 0.04 0.32 0.94 0.48

Book fairsNo 0.97 0.45 0.29 0.84Yes 0.03 0.56 0.71 0.16

Craft fairsNo 0.98 0.50 0.40 0.89Yes 0.02 0.50 0.60 0.11

Trade fairsNo 0.96 0.55 0.43 0.99Yes 0.04 0.45 0.57 0.01

LecturesNo 0.98 0.78 0.40 0.95Yes 0.02 0.22 0.60 0.05

Theatre and music festivalsNo 0.96 0.69 0.54 0.94Yes 0.04 0.31 0.46 0.06

each pro¢le belongs. For example, for going tomuseums, the no cultural activity class (cluster 1) has aprobability of 83 per cent of not going, greater thanits overall probability, 67 per cent; the popular culturalclass (cluster 2) has a chance of not going of 15 percent, greater than its mean probability, 13 per cent;the omnivorous class (cluster 3) has a likelihood ofgoing of almost 50 per cent, clearly greater than12 per cent, its overall probability; ¢nally, highbrowclass (cluster 4) has a chance of going of 34 percent, greater than its mean probability, 9 per cent.So if a particular consumer answers that he or shedoes not go to museums, he or she has a 83 per centchance of being in class 1, a 15 per cent of being inclass 2, and almost no chance of being in classes 3of 4.

The top of the triangle is the point of the omni-vorous and highbrow classes (the two that have beensummed up). The lower-right point is the vertexof the popular culture class. The bottom-left point isthe vertex for the no cultural activity class. As a generalrule, every indicator level falling in the area markedby the overall cluster mean (they mark a division inthree areas) and its class vertex has a greater pro¢lethan the overall probability and characterizes theclass. If an indicator level is greatly associatedwith the no cultural activity class, then it will beplotted near the lower-left. That is what we see: allthe negative answers fall very near the lower-leftvertex. If we look at the positive level of going tomuseums,we see that it lies close to the upper vertex.All positive indicator levels associated with popular

SEGMENTATIONOF CULTURALCONSUMERS IN SPANISH SOCIAL SPACE 361

Figure 1. Tri-plot ofthe four clusterpro¢les

culture fall in the area of the popular culture class,whereas all positive indicator levels (high and pop-ular culture) fall in the area of the omnivorous andhigh-brow classes, and, ¢nally, all negative indicatorlevels fall in the area of the no cultural activity class.

Variables of Social Strati¢cation Associated

to Clusters of Lifestyles

The latent class cluster model can be extended toincorporate concomitant variables (Hagenaars, 1990,1993) in order to make the distribution of the latentvariable dependenton the externalYvariables,p �XX,Y

t, y .Now the probability of observing any pattern ofcultural consumption, cs, assuming membership inlatent class t, is:

p(cs) ¼XT

t¼1

p �XX,Yt, y

Y

8s, �SSp�SS,Xs, t .2

The variables father’s education, marital status,sex, and the interaction of sex with marital statuswere not statistically signi¢cant. Education andsocial class as measured by the EGP classi¢cationare closely related and so the interviewee’s socialclass is not signi¢cant when we take into accounteducation. The same pattern is found between theinterviewee’s social class and his or her father’ssocial class. The model does not ¢t the data, as is

quite usual (Madigson and Vermunt, 2000). This isdue to the assumption that the variables of socialstrati¢cation are not related to the cultural activityindicators, and to the sparseness of the cross-tabulation between the latent variable and theexternal variables, the chi-squared likelihood ratiois very high in comparison to model 4 in Table 2(L2¼4141.65). Nevertheless, the two statistical testsbased on information criteria (BIC¼�486829.21,and CAIC¼�556142.21) suggest that this is a bettermodel. Results of the model with active covariatesare shown inTables 4a and 4b, with model A usingfather’s social class and interviewee’s educationallevel as indicators of the interviewee’s social posi-tion, andmodel B only the interviewee’s social class.

For this reason, in addition to the active modeland in order to explore the association betweenexternal variables and clusters of behaviour, we willuse the inactive covariates method that allocatessubjects proportionally to the various latent classes,with proportions equal to their latent classi¢cationprobabilities, according to their pattern of beha-viour (Vermunt and Madigson, 2000). So we havethe subjects’ probability of being in each culturalclass conditioned on their behaviour.

This is the same procedure used when pro¢lingconsumers’ answers to plot the characterization oflifestyles’ clusters, but now we look for the prob-ability of being in the cluster no cultural activity, t,

362 LOPEZ SINTAS ANDGARCIA ALVAREZ

Table 4a. Parameter estimates for the logitmodelAwith linear e¡ects ofthe active concomitant variables (standard errors in parentheses)

Covariates Cluster 1 Cluster 2 Cluster 3 Cluster 4 Wald p-value. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Intercept 1.22 (0.35) 1.05 (0.42) �0.73 (0.41) �1.53 (0.51) 21.58 0.00000AGE 0.17 (0.05) �0.26 (0.07) �0.08 (0.06) 0.16 (0.07) 30.02 0.00000FATEGP 0.17 (0.05) 0.04 (0.06) �0.18 (0.05) �0.03 (0.06) 18.73 0.00031EDUCATIO �0.68 (0.08) �0.10 (0.09) 0.45 (0.08) 0.33 (0.09) 86.06 0.00000CITY �0.18 (0.06) �0.12 (0.07) 0.20 (0.07) 0.10 (0.08) 16.82 0.00077

Table 4b. Parameter estimates for the logitmodel B with linear e¡ects ofthe active concomitant variables (standard errors inparentheses)

Covariates Cluster 1 Cluster 2 Cluster 3 Cluster 4 Wald p-value. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Intercept �0.40 (0.30) 0.62 (0.34) 0.47 (0.32) �0.69 (0.39) 7.58 0.05500AGE 0.37 (0.04) �0.18 (0.06) �0.21 (0.06) 0.02 (0.07) 81.95 0.00000SOCCLASS 0.17 (0.04) 0.06 (0.05) �0.17 (0.05) �0.06 (0.06) 29.60 0.00000CITY �0.27 (0.05) �0.17 (0.07) 0.28 (0.07) 0.16 (0.08) 48.63 0.00000

conditioned on being aged below 25 years, z, p(tjz),which is de¢ned as the joint probability of beingclassi¢ed in the cluster no cultural activity and in theage category ‘below 25’ divided by the probabilityof being aged below 25 years:

p(tjz) ¼pZXztpZz

so that:XT

t¼1

p(tjz) ¼ 1

(see Madigson and Vermunt, 2000: 23 for furtherdetails). Again this is equivalent to row pro¢ling acontingency table in correspondence analysis.

Table A1 in the appendix shows the pro¢le of theeight cultural-activity indicators, and Figure 2 theirgraphical representation (this timewehave combinedthe no cultural activity and popular classes to clarify thedi¡erence between the highbrow and omnivore clusters).To facilitate the visualization of socioeconomic vari-ables we have created two charts: Figure 2a, withinterviewee’s father social class (FATEGP), educa-tion (EDUCATIO) and interviewee’s social class(SOCCLAS); and Figure 2b, with generation (AGE)and city size (CITY).

To see how to interpret these two plots, we needto focus our attention on the interviewees’ fathersocial class. Log-linear parameters indicate thatthe lower the father’s social class is (see FATEGPin Table 4a), the greater the probability of display-ing behaviour behaviour like the no cultural activityclass. Table A1 shows that the probability of beingin the no cultural activity class is greater for intervie-wees if their father works in any manual ocupation.So in Figure 2a the manual category is displayednear the top vertex. On the other hand, if thefather’s occupation were classi¢ed as service 1(labelled 1 to distinguish it from interviewee’s ser-vice 1 category), the probability of being in theomnivorous class would be greater: the highestfather’s social class category is near the omnivorousvertex (lower-right). Popular culture and highbrowhave low associations, although the former is posi-tive (indicating an association with low socialclasses) and the latter is negative (indicating a rela-tionship to high social class). For this reasonwe ¢ndlow status jobs near the top vertex (this vertexincludes the no cultural activity and popular cultureclasses) and service 2 (labelled as 2 to di¡erentiate

it from the interviewee’s social class) at the mid-point between lower-left and the lower-right.

DiscussionIn our work we have classi¢ed Spanish consumersaccording to their behaviour, unlike most of theresearch that has analysed the consumption of cul-tural products. Our results agree with those foundby van Rees et al. (1999) when using the same mea-surement methodology of latent class models.However, they di¡er depending on the social spaceanalysed, the set of indicators of cultural activities,and themoment in time.VanReesetal. (1999) studiedthe reading habits of a sample of Dutch consumersin 1990. In our case, we analysed eight culturalactivities from a Spanish sample in 1994.

Both pieces of research found a large cluster(67 per cent) of consumers who participated in nocultural activity of any kind, a ¢nding that agreeswith DiMaggio’s (1987: 444) remark that culturalconsumption studies invariably reveal large groupsof people who ¢nd no enjoyment in consuming anycultural product. Another cluster, named lowbrowreaders in van Rees et al. (1999) and the popular cultureclass here, makes up around 12^13 per cent of thesample. Omnivorous readers in Holland represent thesmallest group (4 per cent), in proportion, and is aneven smaller group than the Spanish omnivore class(12 per cent), although in contrast the Dutch high-brow reader group is proportionately (15 per cent)larger than the Spanish highbrow class (9 per cent).

Our results found evidence, therefore, thatsupports the thesis of Peterson and Simkus (1992)and Peterson and Kern (1996), which proposes theexistence of a lifestyle characterized by an insatiableconsumption of a variety of cultural genres oractivities. DiMaggio (1987) proposed that peoplewith wide-ranging networks develop ‘tastes’ for thewidest variety of cultural forms, and that thenumber of cultural genres that a person consumesis a function of his or her socioeconomic status.Wecannot determine using our data sample whether ornot the Spanish high-class omnivore model ofconsumption is replacing the high-class highbrowmodel, as Peterson and Kern (1996) proposed.

Nevertheless, our results do castdoubt on the stra-ti¢ed consumption hypothesis based on the high

SEGMENTATIONOF CULTURALCONSUMERS IN SPANISH SOCIAL SPACE 363

classi¢cation or legitimization of cultural products,as Bourdieu’s proposition has been interpreted (see,for instance, Peterson and Simkus,1992, Katz-Gerroand Shavit, 1998, Katz-Gerro, 1999; and Bihagenand Katz-Gerro, 2000).

This contradiction is only apparent if we look atproducts that characterized the four segments of cul-tural consumers reported here, but also highlightsthe necessity of analysing patterns of consumption(lifestyles) instead of clusters of correlated products.Tohelp us compare the results,we conducted a latentclass factor analysis (not reported here) and foundtwo dimensions, one labelled highbrow culturalproducts and the other popular products.3 Thetwo high-class segments of consumers that wehave labelled omnivore and highbrow classes sharetheir pattern of highbrow cultural activities (thoseindicators more associated with the latent factor

dimension labelled highbrow culture), but with adi¡erence: the omnivore class also consumes productsclustered around the latent dimension labelledpopular culture products. As Bryson (1996) states thiscontemporary emphasis on breadth would be moreaccurately described as multicultural capital: thesocial prestige a¡orded by familiarity with a rangeof cultural styles that is both broad and predictablyexclusive. Popular and highbrow classes, on the otherhand, can be classi¢ed as univore, as their patternof cultural activities is only one of the two under-lying cultural dimensions found in the latentstructure of the lifestyle’s clusters.

The latent class cluster model with inactive andactive concomitant variables used to explore therelationship between lifestyles found amongstSpanish consumers and their position in the Spanishsocial space suggests that, on the one hand, the

364 LOPEZ SINTAS ANDGARCIA ALVAREZ

Figure 2a. Tri-plot ofsocioeconomic variables in the space of consumers’classes

association between the patterns of behaviour foundand the socioeconomic status of the respondent’sfather, SES, is greater than the association to theinterviewee’s SES, and, on the other hand, thatboth SES variables are related. This gives supportto the hypothesis of social reproduction (DiMaggio,1982,1987), that asserts that parents’ SES has a greatin£uence on their children’s activities and prefer-ences, even more than the children’s ¢nal socialposition. However, the father’s in£uence can bemodi¢ed by an interviewee’s educational level: thehigher the level of education, the greater the prob-ability of being found in highbrow and omnivorousclasses of lifestyles.This last ¢nding also lends sup-port to the social mobility hypothesis (DiMaggio,1982, 1987). Nevertheless, due to the sparseness of

the cross-tabulation of our sample, we did not tryto test the interaction between the social reproduc-tion hypothesis and gender, as DiMaggio did (1982).

Although recent research in Spain has foundthat women attend middle and high culture eventsto agreater extent thanmen (Cuadrado andFrasquet,1999; SGAE, 2000), we did not ¢nd support forthe hypothesis that women consume more highculture products than men in our analysis of eightindicators of cultural activities. Neither did wedetect any support for the constraint hypothesis(marital status and its interaction with sex). Citieswere discovered to be associated with the clustersof lifestyle patterns of behaviour. Omnivores aremore likely to be found in Madrid and Barcelona,highbrow consumers in middle-sized cities, and

SEGMENTATIONOF CULTURALCONSUMERS IN SPANISH SOCIAL SPACE 365

Figure 2b. Tri-plot ofsocioeconomic variables in the space of consumers’classes

popular and no cultural activity classes in smallcities.

We found, nevertheless, support for the genera-tional hypothesis. Age shows a ¢rm associationwith classes of lifestyles. People classi¢ed in theno cultural activity class are older, followed by thepopular class and highbrow consumers (in thatorder). Being Omnivorous is typical of the youngerclass, the same pattern found by van Rees et al.(1999). This ¢nding contrasts with that found byKatz-Gerro (1999) Katz-Gerro and Shavit (1998),and Bihagen and Katz-Gerro (2000), that youngerindividuals consume more popular culture thanolder people, and the reverse for high cultureproducts. This highlights the fact that when welook for association between clusters of culturalproducts (low and highbrow, for instance) andage, results show another type of generationale¡ect: young people consume more popular(probably more contemporary genres) than high-brow cultural products in comparison to olderconsumers. Many genres classi¢ed in the past aspopular are now seen as high or middle brow cul-tural products (Peterson, 1997b). However, whenwe focus on lifestyle de¢ned as a cluster of patternof cultural activities, young people’s consumptionof culture is more omnivorous than is the case forolder people.

ConclusionWe have classi¢ed Spanish consumers according totheir behaviour when consuming a set of culturalactivities.The use of exploratory latent class modelsallowed us to ¢nd di¡erent segments of behaviourinstead of clusters of products, as has been theusual method followed in the sociological researchon cultural consumption. By proceeding in thisway, we were able to analyse the strati¢ed consump-tion hypothesis that relates the lifestyle cluster tosocial position.We found support for the omnivoreclass hypothesis being related to the highest socialclass, the highest educational level, and youngerage categories. Our data also lend support toDiMaggio’s social reproduction and mobilitymodels. Nevertheless, we did not ¢nd that womenconsume more highbrow cultural products.

Notes1. Probably for that reason Baumol and Bowen (1966:

282) found that high-culture outdoor performancesattract audiences with a lower median family income,less education, and a greater proportion of blue-collarworkers than indoor performances.

2. The estimation of p �XX,Yt, y in the LatentGold and

LEMprogrammes is restricted by a logistic regressionmodel with e¡ect coding, linear e¡ects of covariates,and category scores that have a mutual distance of oneand a mean of zero over the levels of the categories(seeVermunt, 1997: 25;Vermunt andMadigson, 2000:154; van Ries etal., 1999: 360).

3. The authors will send the results upon request.

AcknowledgementThe authors would like to thank Albert Padro¤Solanet (UAB) for providing access to the dataused in this analysis.

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Authors’ AddressUniversidad Auto¤ noma de Barcelona, School of

Economics and Business Science, Business EconomyDept., Edi¢cio B, 08193-Bellaterra (Cerdanyola delValle' s), Spain. Tel: +34-935-812-270; fax: +34-935-812-555; email: Jordi.Lopez@uab.es

Manuscript received: December 2000.

368 LOPEZ SINTAS ANDGARCIA ALVAREZ

AppendixTable A1. Pro¢le ofthe inactive covariates levels

Cluster 1

No cultural activity

Cluster 2

Popular culture

Cluster 3

Omnivorous

Cluster 4

Highbrows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Overall probability 0.67 0.12 0.12 0.09CovariatesAge

5 25 0.55 0.17 0.21 0.0725^34 0.57 0.16 0.13 0.14

35^44 0.59 0.16 0.17 0.09

45^54 0.68 0.12 0.11 0.09

54+ 0.82 0.07 0.04 0.07Education

Primary (EGB) 0.80 0.10 0.04 0.06Low secondary 0.55 0.19 0.16 0.10

High secondary 0.47 0.17 0.20 0.16

University 0.26 0.16 0.41 0.17

Father’s social classService 1 0.25 0.14 0.49 0.12

Service 2 0.41 0.11 0.26 0.22

Non manual 0.55 0.19 0.18 0.08Entrepreneurs 0.64 0.16 0.11 0.09Manual 0.72 0.11 0.09 0.08Not in labour force 0.76 0.11 0.06 0.07

City5 100 0.73 0.12 0.08 0.07100^250 0.60 0.17 0.12 0.11

4 250 0.60 0.12 0.19 0.08Madrid^Barcelona 0.53 0.11 0.21 0.15

Social classService 1 0.19 0.10 0.56 0.15

Service 2 0.41 0.18 0.14 0.27

Non manual 0.52 0.15 0.26 0.07Entrepreneurs 0.62 0.19 0.10 0.09Manual 0.70 0.13 0.08 0.09

Not in Labour-force 0.76 0.11 0.06 0.07Students 0.40 0.19 0.30 0.11