Media repertoires of selective audiences: the impact of status, gender, and age on media use

Poetics 31 (2003) 465–490 www.elsevier.com/locate/poetic

Media repertoires of selective audiences: the impact of status, gender, and age on media use Kees van Reesa, Koen van Eijckb a

Department of Language and Literature, Tilburg University, PO Box 90153, 5000 LE Tilburg, The Netherlands b Department of Leisure Studies, Tilburg University, PO Box 90153, 5000 LE Tilburg, The Netherlands

Abstract Data from the 2000 Time Use Survey (TUS; n=1819) are used to analyze the composition of media repertoires of the Dutch population. Bourdieu’s theory of taste would predict that a repertoire is internally consistent in terms of status: in the repertory of high status groups, highbrow is coupled with highbrow (NYT with PBS) while in low status groups lowbrow goes with lowbrow (New York Post with Big Brother). In light of previous research, however, we expect first that media repertoires are characterized by other dimensions than degree of ‘browship’ or legitimacy; second, that status in itself is inadequate to segment these repertoires’ audiences. Some segments focus on one and the same medium type and they select items which differ in level. Other segments focus on a particular type of content irrespective of the nature of the medium, while still other audience segments are guided by both content and medium type. Analyses are based on the entire media supply (here: 19 kinds of media). The first research question of this paper bears on the stepwise segmentation of the media audience. This question is answered by interpreting the results of a hierarchical cluster analysis (HCA) in a new way. In addition to the cluster solution, factor analysis was carried out in order to identify repertoires. Eight factors, for the most part similar to the clustering by HCA, structure the repertoires. Multiple regression analysis confirmed that the eight repertoires are clearly distinct in terms of status, gender, age, labor market position situation, as well as religion and political interest. # 2003 Published by Elsevier B.V.

1. Introduction Media use can currently be regarded as a cultural practice in its own right. In the Western world, this practice is almost universal: on average, the majority of the

E-mail addresses: [email protected] (K. van Rees), [email protected] (K. van Eijck). 0304-422X/$ - see front matter # 2003 Published by Elsevier B.V. doi:10.1016/j.poetic.2003.09.005

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population spends more leisure time on media-related activities than on any alternative leisure pursuit. The term ‘media use’ refers to a practice which varies greatly in intensity and scope, that is, in the amount of time and mental effort people spend on media, the regularity of use, the number of media which make up people’s repertoire, and people’s preferences for specific media over others. The purpose of the present study was to gain greater insight into the nature of media repertoires and of their corresponding audiences. This may help to clarify the concept of the active and selective audience, which underlies contemporary media research (McQuail, 1991: 233; Kubey, 1996). This concept is understood in different ways. In the present study, media use implies activity. It is also taken as fact that the Western media market allows consumers a free choice from a broad media supply. But given time budget restrictions alone, users are obliged to choose their own repertoires. In this study, we used data from the 2000 Time Budget Survey (TBO, 2000) to analyze the media repertoires of the Dutch population. It was assumed that a specific media orientation underlies consumers’ decisions to adopt and use specific media and exclude others. The notion of media orientation refers to a set of mediarelated schemes in the mind of media users. Given the nature of the current data, we did not, and could not, focus primarily on these schemes. However, since we had at our disposal a complete palette of media behavior of a representative sample of the Dutch population, we were in the position to better understand patterns of use. Each of these patterns can be regarded as a set of mutually compatible media. Conversely, differences between patterns or repertoires can be traced back to the fact that consumers tend to consider specific media to be incompatible or barely compatible. Thus, in bringing to light differences between patterns, the analysis in this study made it possible to answer indirectly the question which media fit into one and the same orientation. Previous research showed how the television-viewing behavior of reader types changed between 1975 and 1995, and to what extent reading and watching television represented complementary activities (Van Eijck and Van Rees, 1999, 2000). In the present article on media repertoires in 2000, the complete range of media is accounted for since audio (public and commercial radio) and new media (PC, Internet) are included in the analysis as well. Furthermore, the use of the Internet is differentiated according to the user’s purpose. Hence, the items involved reflect the diversity of both the content (e.g., information, entertainment) and medium types (magazines and newspapers, radio and television, interactive media). We are aware that the global distinction between information and entertainment is a relative one, and that these are audience-related concepts, the meaning of which varies with the medium at issue. By considering how content and type are related to one another, it is possible to differentiate media somewhat by degree of legitimacy. This is important from the perspective of empirically questioning the idea of homogeneity of lifestyle repertoires by status groups, which is central to Bourdieu’s theory of taste (Bourdieu, 1979). 1.1. Homogeneous media repertoires of distinct audience segments? In his research on media use by the Swedish audience, Weibull made the valuable suggestion that people differ in their media use by their media orientation, that is,

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their mindset regarding media (cf. Weibull, 1992: 270–27). Schemas related to a media orientation bear on the perception and valuation of the media supply. The nature and acquisition of media-related schemes depend on a variety of factors (socialization, age, gender, life stage, status, time pressure and, foremost, previous media use). Children who were avid watchers of MTV in their early teens may shift toward other music-video stations or to other (especially, new) media altogether as they grow older. More highly educated people aged roughly between 20 and 30 who were not used to reading newspapers may feel their new job situation obliges them to become regular readers of quality newspapers. Different orientations are due to factors such as the ones just mentioned and they will continue to lead to various media uses until important changes occur in the factors affecting this use. Thus, the configuration of medium types and kinds of programs which constitute a repertoire may change under the influence of a new life stage, changes in job situation or family composition, or as a consequence of changes in the media supply (new media, new kinds of programs). This conceptualization can be sensibly connected with Bourdieu’s theory of taste and his view of the habitus as a set of schemes of perception, appreciation, and action (Bourdieu, 1979: 189–196; 1980: 87vv; Rosengren, 1996: 30–46). It is possible to test two theses which hold a central position in Bourdieu’s theory (1979). The first is the thesis of homogeneity which states that taste repertoires are homogeneous per class fraction. The second is the thesis of homology, according to which the structure organizing cultural practices (e.g., their hierarchization according to degree of legitimacy) is homologous to that of class fractions ordered by status (1979: 196 and passim). The position media use has among the daily cultural practices, as well as the nature of our data on Dutch media use, provide sufficient grounds for focussing on media use as a cultural practice sui generis. The first research question bears on the segmentation of the audience and, more specifically, the composition of their media repertoires. The latter was assessed by analyzing time budget data of a representative sample of the Dutch population, and by describing their media use in relation to the entire media supply. It turned out that homogeneity of repertoires is not selfevident. The second research question is: How can these media patterns be explained in terms of user characteristics? Besides descriptive statistics, regression analysis allows us to relate these repertoires to specific user characteristics, such as level of education (Bourdieu’s main indicator of status), age, gender, and factors like time budget, religion, and political interest. This led us to relativize Bourdieu’s homology thesis. To identify dominant modes of media orientation and to distinguish them from one another, researchers can adopt several approaches. They may examine whether users focus on a medium type (print, screen, degree of interactivity), on a specific content type media provide (for example, serious or light information, legitimate or popular entertainment, infotainment, or a combination of these). Underlying the first approach is the assumption that the audience decides on the basis of its preference for a specific medium. Thus, if the difference between print and broadcast media is relevant to the choice, implying that the type of medium is given priority in

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people’s decision whether or not to take note of it, we might expect to find both a group of fervent readers and a group of intensive television viewers, irrespective of content. An alternative view presumes that media users decide on the basis of a dominant inclination toward content, irrespective of the medium that provides it. Then, the differentiation in use of print media, television, etc., is accounted for by pointing to the extent to which media consumers focus on information, entertainment, or a mixture of both. A third approach, which is advocated and which we tested in this study, combines the previously mentioned approaches but adapts them. If one assumes that the medium takes priority over content, it can be expected that serious print media would be preferred by higher status groups, television by middle and lower status groups, and new media by younger generations. However, researchers making this assumption risk insufficiently taking into account the dynamics of the media industry, particularly the interdependence of the production and consumption of culture. The enormous growth of the media supply, admittedly with ‘much of the same,’ was a major factor inducing consumers to adopt a more hybrid, less exclusive lifestyle — read: media use. One must also be on the watch for the questionable premise that the oldest media (print) evidently count as more legitimate than other, less old media (television or internet). If, by contrast, one holds the second view (as occurs in Bourdieu, 1979), that selection of a content which fits users’ status has priority (high with high, etc.), one may expect to find within each type of medium use a differentiation by status (in particular education). In addition to quality newspapers, opinion magazines, and books, higher status groups are likely to prefer serious television fare, while lower status groups are likely to prefer (light) entertainment through popular newspapers and the yellow press and, increasingly, commercial television. In this view, however, a rather strong automatism is presumed in the way people combine kinds of media. Moreover, this view does not sufficiently take into account issues such as the nature of processing medium types and the growing heterogeneity of taste patterns. With respect to content, medium types may be considered to provide a range of programs which hold a similar position on an imaginary scale (from serious information to light entertainment). This ought not make one overlook the fact that print, broadcast, and internet presume quite different processing mechanisms. For certain groups, one-sided socialization at an early life stage may, of course, lead to one-sided use. A one-sided media-orientation and a media use that is consequently limited in range appear more likely in the case of lower status groups. Higher status groups seem more inclined to combine various contents and to derive them from distinct media. In this context, serious print information can be combined with legitimate or even light entertainment rather than this print information supplementing television information. Previous research on changes in media use between 1975 and 1995 show that young, more highly educated people are more ‘omnivorous,’ that is, they tend to combine rather heterogeneous categories of items (serious print media with television entertainment; see also Peterson, 1992; Van Rees et al., 1999; Van Eijck and Van Rees, 2000). The approach which attempts to simultaneously account for content type and medium type, is more refined but imposes stronger conditions. One must have clear

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indications of the content of the media used, and their categorization (e.g., in terms of degree of legitimacy) may raise problems. Even though there are only limited possibilities for specifying content categories, it is believed that using the current operationalizations of kinds of media and of content categories, these conditions can be met. Insofar as time budget data permit, content aspects of both print media, broadcast, and internet are also taken into account. Thus, we expect to bring to light differences in media repertoires of types of media users. By examining actual time spent on media, it becomes clear which selections respondents make from the supply. In order to gain insight not only into the repertoire of media selected for use but also into the stepwise segmentation of the audience, hierarchical cluster analysis was applied. This technique permits us to show which selections are subsequently made by consumers and how this results in the use of specific media. This was crucial for our first research question, which we might rephrase as follows: Does selection of medium type have priority over that of a specific content, or the other way around? Or will we find a certain mixture among consumers? In defining media orientation in a way analogous to Bourdieu’s distinction between kinds of tastes in legitimate, middle-brow, and popular taste (1979: 14; troisie`me Partie ‘‘Gouˆts de classe et styles de vie’’), one cannot answer these questions. What is needed is an empirical analysis which accounts for the nature of both the repertoires and their users. From the viewpoint of arbitrary media users, their combinations of media appear homogeneous by default. The question of (degree of) ‘heterogeneity’ barely arises, unless consumers view their repertoires with an analytical eye and proceed on specific assumptions regarding factors which could make a repertoire heterogeneous. Media policy makers, and audience researchers and advertisement executives may vary in regard to the major standards they apply in assessing a repertoire’s heterogeneity. A repertoire may be said to be heterogeneous because it combines items which, from a content point of view, represent the opposite poles of a scale, or because media users combine different medium types. Audience segments can also be called homogeneous or heterogeneous to the extent to which their members share characteristics that are thought to be relevant. Though homogeneity of repertoires is an entirely different issue from that of audiences, they do affect each other. In recent decades research in the sociology of culture has sharpened our awareness that the manner in which media items are positioned on scales changes over time and that the media audience tends to be more broadminded in that it is integrating a broader range of media items in its repertoire. As items which previously were positioned widely apart are combined over a more prolonged period of time and are now shared by different status groups, the perception that they are heterogeneous wanes. The reputation that parts of it are vulgar or elitist also fades because these evaluations of product quality were based on a judgement of the status of those who consumed them. Previous research on media use shows that people vary greatly as to their interest in print media and television. Social groups differ in their orientation to these media and ways of using them; these differences have always existed. With time, the composition of repertoires changes, even though kinds of repertoires will show a high degree of continuity. What also changes with time is the effect of background and

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explanatory variables on a repertoire’s composition. Conclusions on repertoires in the year 2000 do not automatically hold for previous periods. The emergence of a medium changes the status of extant media (television relative to print; PC relative to television). At the same time, the ways in which media are interrelated change, as can be seen from the variety of uses groups make of them: not only were the more highly educated less inclined to adopt a distant or hostile attitude towards the ‘new’ medium, but the less educated and, later on, those with a moderate level of education loosened their traditional bond with print media. Recent birth cohorts among the more highly educated are now doing the same. But even if the intensity of television viewing is similar among these groups, this does not mean that they follow intensively the same program repertoire. Less than in the past, user status runs parallel to repertoire status. In 2000, the homology suggested by Bourdieu, the identity in structure and organization of — in our case — audience segments and media repertoires, is absent. (We leave open the question whether it can be shown to exist for the data from La Distinction.) It was assumed it was possible to segment ‘the’ media audience into distinct audiences, partly according to their major preference for specific content types, partly according to the medium type they each prefer, and partly also according to a weighted combination of content and type. Differences between segments were initially described with the help of a set of background characteristics. Then multiple regression analysis was applied to assess the effect each of these characteristics had on the media repertoire. This allows for interpreting differences among groups in, for example, age, gender, or education with the help of supplementary traits such as time budget, job status, political interest, or religion. It might be expected that older, more politically interested people will use print media more frequently than young people, irrespective of their level of education (Van Eijck et al., 2001). People with limited time are likely to spend less time on media, but reading will be the practice that suffers most from this limitation (Knulst and Kraaykamp, 1996: 211–216). Commercial television is more popular among men, irrespective of educational level, while for internet, a positive education effect may be expected. Public television is more popular among the older generations, especially women. The latter also count among the readers of books, regional newspapers, and women’s magazines. In addition to a greater interest in Protestant newspapers, people with a religious affiliation are also more reluctant to view commercial television.

2. Media market Media use and media supply are closely connected. Although the focus of this article is on the former, this close connection requires a brief consideration of recent developments in the media market. Over the past 20 years, changes in the structure of the media world have had a serious impact on the organization of media firms (Bakker and Scholten, 1999). Economic developments on the newspaper markets

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can be summarized with the help of two concepts: concentration of producers and title reduction. Since the mid-1980s, the process of concentration has accelerated, and in 2001 only three large companies — PCM, Telegraaf, and Wegener — share the oligopolistic market of national and regional newspapers. It is also a market in contraction. In the past few years, the loss of advertisers and readers (in Holland mostly subscribers) forced newspaper publishers to take measures such as merging regional titles and editorial staffs, reducing the number of journalists, and bringing to a halt recently-started experiments with new media. As the analysis of time budget surveys since 1975 shows, interest in newspapers has declined sharply (Van Eijck and Van Rees, 2000: 593–596). From the 2000 time budget survey, it appears that this downward trend continued. The notion of supplier concentration is, likewise, applicable to the market for consumer magazines. In contrast to the newspaper market, however, there is no question of title reduction. To compensate for the loss of subscribers to successful titles, magazine publishers developed new titles on more specialized sectors of information, for example, with regard to specific aspects of lifestyle. Since the 1980s, interest in opinion weeklies and family magazines in particular has declined, being replaced by television programs and supplementary sections which newspaper firms added to their products. However, it remains possible for consumers to select from a broad range of titles a magazine that fits their interest. For economic reasons, newspaper subscriptions are usually limited to one title per family. This is different for magazines, most of which are more explicitly targeted towards age and gender groups. In their use of electronic media, more particularly in their selection of television networks, consumers appear to be virtually unrestricted by economic considerations. In the Netherlands, cabling, a new (third) public network, and the advent of several new commercial networks significantly enlarged the range of channels from which television viewers could select a variety of programs at a reasonable rate. Though operating conditions for broadcasters differ from those of print media publishers, the broadcasting market which, for a long period, was dominated by the oligopoly of seven public networks on two (since 1975) and then three (1988) channels, turned into a battle, first between public broadcasters and the newly-admitted commercial ones (RTL 4 in 1989; RTL 5 in 1993). As of the mid-1990s, these two parties were obliged to adapt their strategy to the arrival of several new, foreignowned, commercial networks (SBS 6 and Veronica in 1995; Net 5 in 1999), all firmly decided to have a piece of the audience pie by targeting even lighter entertainment programs towards younger age groups. To counter the decline in their viewer rates, the government forced public networks into the straightjacket of a new organization involving compulsory collaboration between networks and loss of autonomy in programming. Because of cable, Dutch television viewers now have at their disposal no less than 10 Dutch channels (including two Flemish ones) and, in addition, a considerable number of foreign channels from, e.g., England, Germany, France and Turkey. Selection from this range may be assumed to frequently occur in a routine manner, just as the newspaper subscriber picks up his daily from the welcome mat.

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3. Data and method 3.1. Data In this study we used time budget data that were collected in October 2000. Data were gathered by means of a diary, supplemented with two oral interviews. The diary covers seven consecutive 24 hour periods. For each quarter of an hour, respondents had to indicate their activity by means of pre-coded categories. The sample consisted of 1813 respondents age 12 or over. Weighting for degree of urbanization, gender, age, number of persons in the household, and profession resulted in a representative sample of the Dutch population. By eliminating outliers on the media variables, a final sample of 1791 respondents was obtained.1 In contrast to previous time budget surveys, we now for the first time had information on Internet use at our disposal. This allowed us to examine whether and to what extent new media belonged for the most part to the repertoire of younger generations (cf. Huysmans and De Haan, 2001: 87–93). Like print media and broadcasting, which can be differentiated according to content, Internet use was classified according to the kind of information people used via the web. For the use of personal computer and VCR, such a differentiation was not possible. However, by taking into account the repertoire in which the latter were embedded, we were able to indicate what kind of content-related interest is involved. 3.2. Operationalization For the differentiation of the media in 2000, we build on the analyses set forth by Van Eijck and Van Rees (2000). For television viewing, the basic categorization refers to the kind of broadcasting network: public or private. This was used in the analysis as an indicator of type of content, with public broadcasters tending to be located more at the serious information end of the scale and the commercial networks at the light entertainment end (see also SCP, 2002: 590). For folio media, we limited ourselves to a bipartition into serious information (quality newspapers and opinion magazines) and other print media (popular newspapers, women’s magazines, special interest magazines, etc.). Admittedly, the latter category, with its neutral designation, is susceptible to further subcategorizations. Appendix A indicates which media were used, which represented a separate item, and which were combined in a type of medium (e.g., regional newspaper, popular national daily). To construct media repertoires, 19 media items were used. (The items used can be seen in the first column of Table 1). Scores reflect the time respondents spent on each item during the registration week. The independent variables that were used in the regression analysis were derived from the oral interviews. Social status could be divided into three measurable 1 Scores on a media item count as outlier under two conditions: (1) respondents belonged to the highest scoring 2 or 3% of the sample, and (2) they spent at least three hours more time on a media item than the large group of respondents in the next scoring category.

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components: respondent’s level of education (highest level attained or present level of enrollment measured with six categories), his/her cultural job status, and his/her economic job status (both measured as standardized score; see Ganzeboom, De Graaf, and Kalmijn, 1987). In addition, gender (1=male and 2=female) and age (three categories: 12–29; 30–54; 55+) were included. In order to control for respondents’ time budget, the following variables were also included:
The time respondents spent on obligations related to household and child care, measured in hours per week;
The time respondents spent on paid work during the registration week, measured in hours;
Respondents’ main activity, consisting of working (part time, that is > 12 hours, or fulltime), retired, unemployed/laid off, housewife, or student;
Household composition, consisting of four categories: family with children, partners without children, single, or living with parents. In addition to these familiar indicators, we included two indicators of ideological involvement that might affect the selection of specific media. Political interest was measured using two categories (1=not interested; 2=(moderately and/or highly) interested); religion was divided into four categories: no religion; Catholic; Protestant; other religion.

4. Method Two methods were used to discover media repertoires: hierarchical cluster analysis and factor analysis. The former is not usual for this type of research, but it fits our main research question. The question whether the media audience can be segmented on the basis of preferences for content or preferences for medium types can be conceived of as a stepwise process of increasingly fine segmentation. If the first main division of the audience would be based on medium type preferences, segmentation on the basis of media content would be secondary. Conversely, if the majority is primarily looking for specific information, the initial segmentation will be based on content and only if the segmentation gets more fine-grained will the content-based audience be divided further into people using different media to meet their content needs. Hierarchical cluster analysis is suitable for describing this segmentation process, because its result is presented as a stepwise joining of items to the degree these are more or less closely allied. Hierarchical cluster analysis results in a nested cluster structure (the dendrogram), which consist of clusters comprising smaller clusters, which in turn contain smaller clusters, etc. The smallest clusters are actually the individual variables, in our case media items.2 2 What hierarchical cluster analysis achieves is the joining of items by order of similarity or affinity into clusters and, subsequently, joining the latter into larger clusters. At each step in the clustering process, the Ward Linkage method used was aimed at joining the (small groups of) objects into a cluster with the least internal variance: the within-groups sum of squares was minimized so that the difference within clusters was minimal as compared to differences between clusters (Aldenderfer and Blashfield, 1984).

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Inherent to cluster analysis is that the technique fails to indicate how many clusters are needed to adequately replicate the data structure. In order to determine the number of dimensions that have to be distinguished for understanding media repertoires, we will therefore use factor analysis. ‘‘Although factor analysis has an underlying theoretical model and cluster analysis is much more ad hoc, both identify related groups of variables (. . .) Factor analysis and cluster analysis need not always arrive at the same variable groupings, but it is comforting when they do’’ (Norusis, 1994: 99). Each factor resulting from the analysis represents one of the dimensions that structure media use. If a factor was found which, for example, exhibited high scores (factor loadings) for all television items and low or negative scores on the remaining items, it could be concluded that the dimension ‘television viewing yes or no’ is important to the charting and understanding of media repertoires. Each respondent was assigned an individual score on each factor. Respondents are allowed to score high or low on each factor. The factors are, thus, by no means mutually exclusive (as are the clusters). Someone scoring high on the television factor may very well score high on other factors. Hence, factors are, in fact, the dimensions underlying media use and they do not represent complete repertoires of different groups. However, it may be assumed that, due to their close relationships, the most current combinations of media items will wind up on the same dimension or factor. Finally, for each of the dimensions, a user profile was designed. These profiles allowed for the examination of the ‘active’ audience segments that, each in their own way, proved to be selective in their use of available possibilities. By regressing the aforementioned independent variables on each respondent’s score on the dimensions, we analyzed which user characteristics actually affected the preference for each of the dimensions.

5. Results 5.1. Breaking up the media audience through hierarchical cluster analysis Since hierarchical cluster analysis aggregated our 19 media items into clusters of variables in a stepwise fashion, the dendrogram depicting this process (Fig. 1) shows which items have been subsequently combined on the basis of their frequent simultaneous use. The sooner items are combined into clusters, the more they represent common combinations according to the audience. This procedure was repeated until all of the items were united in a single comprehensive cluster. Mapping the entire clustering procedure, starting with 19 separate items and ending with one cluster encompassing all these items, can be considered as a reversed stepwise audience segmentation. For each combination of media items, it becomes visible at which phase of the process they merge into a larger cluster or repertoire. Moving through the dendrogram in the opposite direction, from right to left, displays the segmentation process directly. Each step in the clustering procedure can be taken as a subsequent distinction that leads to ever more specific audience segments.

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Fig. 1. Dendogram HCA. REGIONWS=regional newspaper; TVNETPUB=public television networks; TVNLOCAL=local television; POPNEWSP=national popular newspaper; RADIOPUB=public radio; WOMENMAG=women’s magazines; ADWEEKLY=free home-to-home advertisement weeklies in newspaper format; RADIOCOM=commercial radio; TVCOM=commercial television networks; PC=personal computer; INTOTHER=internet use for other purposes than serious information; VIDEO=video tapes; INTSERI= internet use for serious purposes; HOBBYMAG=hobby magazines; VOLKSKR=de Volkskrant; BOOKRDG=book reading; OPINMAG=opinion magazines; NRCFIN=NRC Handelsblad & Financieel Dagblad; RELINWS=religious newspapers.

Statistically, the clustering process is carried out from left to right (see Fig. 1). The first items to be joined are regional newspapers and public television, in the upper left quadrant of the figure. These are the two items that are most often used together. Since this is a combination of a visual medium and a folio medium, it cannot be assumed that there is an underlying orientation on medium type. An orientation on a specific content, or a preference for more traditional media, is more likely to lead to this combination. At the second step, reading opinion weeklies and reading NRC Handelsblad+Financieel Dagblad are joined: two print media, but also two sources of serious information. Step 3 merges PC use and the use of the Internet for anything but serious information. After that, women’s magazines and free papers

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were combined. In the last step, the cluster containing the items 3–16 (upper half of the dendrogram) was united with the cluster containing items 7–15.3 Moving backward through the clustering procedure, we view the dendrogram as it is supposed to be viewed here, that is, as a depiction of the stepwise segmentation of the media audience. A first general division of the audience can be made on the basis of the difference between those who are more interested in the cluster of items 3 through 16, and those preferring the cluster of items 7–15 (below). As these two sets of items are only merged at the final step of the hierarchical clustering procedure, we may consider the choice between them to represent the most elementary segmentation of the media audience and thereby the most fundamental difference between media orientations. Those belonging to the ‘upper’ half of the dendrogram seem to prefer popular and regional newspapers, radio and television, women’s magazines, and free papers. If, on the other hand, one belongs to the lower half of the figure, apparently PC and the Internet, quality newspapers, opinion weeklies, hobby magazines, and video are preferred. This suggests the existence of a very basic distinction between audio-visual media and popular or middle-brow print matter, on the one hand, and serious information, interactive media, and ‘stories’ (books, video), on the other. This distinction is based on both medium types and media content. All audiovisual media (except video) are in the first big cluster; all serious information (with the possible exception of public television) is in the second cluster. After this first division, the audience segmentation process moves on. The audience of the lower cluster of items subsequently splits up between the users of media items 7–6 and those using items 1–15. The first set contains PC and Internet, video, and hobby magazines, whereas the second set encompasses quality newspapers, books, and opinion weeklies. Thus, the second set represents most of the serious print media of the set of items under study, while the first set represents interactive and electronic media. The hobby magazines and video cannot be specified further on the basis of content. Moving on, it appears that the next division of consumers of the serious print media separates those preferring books and de Volkskrant from those reading opinion weeklies, NRC/Financieel Dagblad and a religious newspaper. Within the latter audience, the choice between opinion weeklies and NRC/Financieel Dagblad takes place farthest down the process because, as was pointed out before, nearly all readers of Financieel Dagblad also read NRC-Handelsblad. The audience segment that chose the sub-cluster consisting of items 7–6, can be divided further into users of PC and the Internet (the latter not for serious information), on the one hand, and video, hobby magazines and also internet, but now for serious information, on the other. Thus, the choice is between using the PC for unknown purposes, but certainly not for information on, for example, politics or socioeconomic issues, and a purposeful search for information (but possibly also entertainment) through the Internet, hobby magazines, and video.

3

A cluster named by two item numbers refers to the range of variables which, reading downwards along the y-axis, starts with the first number and ends with the second.

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K. van Rees, K. van Eijck / Poetics 31 (2003) 465–490 Table 1 Comparison of a four-factor model with hierarchical cluster analysis

Factor 1 Cluster Factor Cluster Factor 3 Cluster Factor 4 Cluster regio 2 serious pc & commercial & public info internet Regional newspapers Public television Home-to-home ad. nwsp Local television Public radio NRC/Financieel Dagblad Opinion magazines Popular newspapers Books Relig newsp Personal computer Women’s magazines Hobby magazines Internet, serious info Internet, other use Commercial television Commercial radio Volkskrant Video

0.689 0.609 0.474 0.444 0.299 0.030 0.130 0.317 0.022 0.138 0.072 0.149 0.314 0.052 0.017 0.002 0.066 0.015 0.121

X X X X

X

0.102 0.271 0.008 0.272 0.167 0.591 0.552 0.442 0.388 0.368 0.035 0.027 0.036 0.052 .123 0.242 0.090 0.114 0.035

X X X X

X

0.103 0.018 0.227 0.049 0.032 0.073 0.084 0.075 0.194 0.133 0.646 0.509 0.470 0.373 0.371 0.052 0.007 0.104 0.055

X X X X

X

0.227 0.086 0.212 0.247 0.025 0.008 0.164 0.361 0.124 0.297 0.069 0.191 0.212 0.046 0.164 0.561 0.529 0.309 0.203

X

X

X X

Source: TBS 2000 R2=29.8%. Bold parameters indicate per column the media items with high (positive or negative) factor loadings.

What about the audience segment that was separated from the abovementioned segments at the first division? This group is divided into a segment using items 3–8 and one using items 5–16. Subset 3–8 represents public and regional broadcasters and regional or popular national newspapers. This might be considered to be an audience for middle-brow information. Subset 5–16 represents the audience of commercial broadcasters, women’s magazines, and free papers. People belonging to this subset can be divided further into an audience for either commercial broadcast media emphasizing entertainment, or entertaining print media. We might conclude that, here, the audience is first segmented based on content (entertainment) and subsequently broken down according to the specific medium type offering this content. But this does not hold for the audience for subset 3–8. This audience can be split up into consumers of either regional newspapers and public or local television, or a popular national newspaper combined with public radio. The rationale underlying this division cannot be discerned, except that, from the viewpoint of audience segmentation, a cost-determined division between regional and national popular newspapers seems logical.

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5.2. Repertoires: the four-factor solution Since it is rather unusual to interpret hierarchical cluster analysis in the above manner, we have used factor analysis to gain additional insight into media repertoires. The coefficients belonging to the dendrogram (agglomeration schedule) indicate the distance between clusters that are being joined at a certain step. The larger the difference between the coefficients belonging to two subsequent steps (shown in the fourth column of Table A1), the ‘larger’ this step is, or in other words: the more difficult it is, given the structure of covariances, to force two subsets into a single cluster. Logically, this difficulty increases as we move to the right-hand side of the dendrogram, as the audiences to be joined become increasingly heterogenous. Given the coefficients from the agglomeration schedule, we have to conclude that a solution with four clusters of items offers the most plausible ‘breaking point’ in the process of subsequent cluster expansions.4 In order to check whether this solution reoccurs when another technique is used, we estimated a factor model (principal components with varimax rotation), fixing the number of factors to four. The result is shown in Table 1. Next to each column of factor loadings, this table shows which items, according to the dendrogram, belong to the cluster most similar to the factor to its left. The four-factor model renders a proportion of explained variance of 29.8%. This relatively low percentage shows that more factors are needed in order to adequately describe the relations between the items. Therefore, after this analysis we did a second factor analysis, this time without directly restricting the number of factors to be discerned. The first dimension resulting from the factor analysis (Table 1, left hand column) combines regional, public, and local television, public radio, and free papers. This set falls entirely within the upper half of the dendrogram, so the combination is also present in our cluster analysis. Comparing it to the second column of Table 1 shows that four of these items belong to the first of the four clusters shown in Fig. 1. Free papers belong to the second cluster in Fig. 1. Popular national newspapers, which belong to the first cluster, load fairly high on the first factor, but even higher on the second and the fourth factors. This item does not clearly belong to one specific dimension. Popular national newspapers are combined with all sorts of other media, as the factor analysis demonstrates. If we know a person reads a popular national newspapers, this does not tell us much about this person’s media repertoire. 4 A look at the dendrogram reveals that merging four clusters into a smaller number involves a relatively long distance across the X-axis. The coefficients confirm this observation. At the step right before the four-cluster solution is reached, that is, when subsets 1–13 and 4–15 merge, the difference in coefficients belonging to the solutions before and after this merger is 1897.043. In fact, from step 8 onwards (where subsets 3–11 and 2–8 merge into 3–8), all other coefficients range between 1727 and 1833. But when the four-cluster solution is thickened by combining subsets 3–8 and 5–16, this coefficient increases to 2237.819. Although the hierarchical cluster analysis displays a stepwise process that is continued until a single cluster remains, such an increase in the coefficient does indicate that adding sets 3–8 and 5–16 is statistically difficult. That is also true of joining sets 7–6 and 1–15, where the coefficient increases by 2270.31. The last step, where all items are joined into one final cluster, is the most difficult; witness the increase in coefficient by 2545.529.

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The second factor, largely representing serious information, is very similar to the cluster at the lower end of the dendrogram. In addition to the aforementioned popular newspapers that landed elsewhere in Fig. 1, de Volkskrant is the only other deviating item. Yet, unlike the popular national newspapers that fit many repertoires and thus load on three factors, de Volkskrant does not seem to fit any pattern well. Factor 3 and the third cluster coincide, with video as the only exception. Like de Volkskrant, video does not relate strongly or exclusively to any of the four factors. Factor 4 represents commercial radio and television. As such, this factor diverges from the cluster solution regarding free papers (factor 1) and women’s magazines (only strongly negative on factor 3). Commercial radio and television obviously have much more in common with one another than with any other item, although it is clear that frequent users of commercial broadcasting media have more affinity with popular national newspapers than with de Volkskrant or religious newspapers. It can be concluded that the four-factor solution by and large points toward the same dimensions as the four-cluster solution. Diversions were mostly found for items that cannot be clearly assigned to a single factor (popular national papers, women’s magazines, de Volkskrant, video). This difference is not very surprising since HCA operates differently from factor analysis.5 5.3. Repertoires: the factor analysis The four-factor solution shows that the repertoires of the audience segments we distinguished by means of HCA do indeed reflect relevant dimensions of the media supply. Yet the result is unsatisfactory due to its low explanatory power and a number of free-floating items. We therefore carried out a factor analysis without special restrictions on the number of factors to be discerned (other than the standard criterion of Eigenvalue > 1). This analysis yielded a model with eight factors and a proportion of explained variance of 52.5%. The accompanying Table 2, can be compared to the eight-cluster solution from the dendrogram, similar to what was done in Table 1. In Table 2, we have underscored items that, according to the dendrogram, in this phase of the segmentation process, together belong to the cluster most similar to the factor under discussion. Factor 1 mirrors the cluster consisting of the three upper items from the dendrogram (all factor loadings printed bold are also underscored). This is the combination of regional newspapers, local television, and public television: these are all omnibus media offering a combination of information and entertainment, emphasizing one’s immediate, or everyday, environment. Factor 2 represents an interest in serious information. The, by now familiar, combination of opinion weeklies and NRC/ Financieel Dagblad pops up again. In the cluster analysis, religious newspapers also 5

The former method is inexorable in the sense that a cluster, once formed, cannot be split again. When the items mentioned above are coupled to another item, often in a relatively late phase of the clustering procedure, they are really inextricably linked from that moment on, and the linkage to this one ‘partner’ may cause them to get lost in the process. This phenomenon, however, is limited to the weaker items that cannot be assigned their own definite place in the factor analysis. That is to say: not if we force them into a four-factor solution.

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Table 2 Standard factor solution for dimensions of media use

Regional newspapers Local television Opinion magazines NRC/Financieel dagblad Popular national newsp Public radio Public television Women’s magazines Home-to-home ad. newsp Commercial television Commercial radio Relig newspapers Personal computer Hobby magazines Internet, serious info Internet, other use Video Books Volkskrant

1 regio & pub

2 ser info

3 pop & pub

4 women

5 commerci

6 pc hobby

7 internet

8 story

0:665 0:639 0.065 0.079

0.114 0.129 0:730 0:638

0.033 0.010 0.063 0.188

0.346 0.118 0.086 0.104

0.074 0.019 0.100 0.039

0.005 0.003 0.075 0.055

0.083 0.110 0.003 0.007

0.124 0.075 0.040 0.011

0.055

0.220

0:706

0.041

0.169

0.053

0.040

0.032

0.087 0:454 0.107 0.216

0.135 0.204 0.082 0.044

0:620 0.461 0.005 0.048

0.030 0.097 0:688 0:660

0.169 0.106 0.003 0.092

0.035 0.042 0.198 0.119

0.039 0.040 0.032 0.041

0.069 0.125 0.058 0.026

0.073 0.157 0.234 0.166 0.165 0.003 0.072 0.161 0.109 0.232

0.099 0.174 0:231 0.065 0.090 0.032 0.025 0.187 0.125 0.337

0.090 0.040 0.080 0.023 0.078 0.116 0.054 0.030 0.189 0.282

0.177 0.002 0.211 0.144 0.116 0.123 0.020 0.068 0.160 0.218

0:627 0:559 0.546 0.059 0.145 0.092 0.088 0.068 0.350 0.030

0.022 0.037 0.086 0:639 0:598 0:571 0.157 0:156 0.072 0.100

0.015 0.214 0.236 0:268 0.073 0.447 0:808 0.040 0.148 0.123

0.011 0.138 0.275 0.110 0.151 0.049 0.047 0.655 0:495 0:466

Source: TBS 2000 R2=52.5%. Underlined factor loadings indicate per column which media items belong together according to the intermediate solution with eight clusters from hierarchical cluster analysis. Bold parameters indicate per column the media items with high (positive or negative) factor loadings.

belonged to this repertoire. These papers also have their highest positive loading on this factor (0.231), but a closer look at the row showing the loadings for religious newspapers shows that they are actually better characterized by their negative loading on factor 5. This can also be more or less seen in the dendrogram: religious newspapers are the single item that is linked last to an existing cluster (only at step 11; see also Table A1 in the Appendix). This makes this item the ‘wallflower’ of the dendrogram and this is again reflected in Table 2, where it does not positively belong to any factor. This demonstrates that the media orientation of the readers of these papers leaves little room for other media, especially television. The third factor represents the combination of popular national newspapers, public radio, and, to a lesser extent, public television, which is in line with the cluster solution. Subscribers to popular national newspapers are, like regional newspaper readers, relatively intense users of public television.

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Factor 4 represents women’s magazines and free papers; factor 5 is commercial radio and television. These are exactly the two adjacent clusters from Fig. 1 that indicate an interest in entertainment. Factor 6 shows the combination of PC, hobby magazines, and Internet for serious information. Here we see some diversions from the cluster solution, where video belonged to the two latter items and the PC clustered together with Internet for other (than serious information) purposes. This last item stands alone in the factor analysis as factor 7, whereas video has joined factor 8, in combination with books and de Volkskrant. 5.4. The audience segments Now that we have considered the media dimensions using factor analysis, we have added each respondent’s score on each dimension to the data set as a new variable. As mentioned above, this score represents the degree to which the respondent used the media belonging to this dimension. A user profile can be put together for each of the dimensions. For these profiles, we used, for each dimension separately, the respondents whose factor scores on this dimension belong within the upper quartile. This allowed us to look at the ‘active’ segments of the audience who, each in its own manner, selectively but actively use part of the available media. This quartile boundary is of course arbitrary, but useful in providing a description of the typical representatives of a certain dimension without ending up with subgroups that are too small to render reliable results. Thus, for each column (Table 3) the scores are based on a subsample of almost 450 respondents. The right-hand column shows the means for the entire sample (n=1791). It is added because the subsamples of the other eight columns are all made up of respondents who make active use of at least one media repertoire (since they belong to at least one upper quartile). To illustrate this, note that the large sample mean for ‘hours paid labor’ is higher than the seven out of eight subsample means because people who spend a lot of time on a media repertoire, with the exception of the Internet, are less likely to work long hours than the average person. That is why only comparing the upper quartiles may be misleading if we want to develop profiles. Comparing the audience profiles to the righthand column shows to what extent the audience deviates from the average respondent. In addition to these descriptive results from Table 3, Table 4 shows the effects of each of the background characteristics we selected on the preference for each of the repertoires. Unlike Table 3, which shows differences in background between audience segments consisting of the upper quartiles only, Table 4 shows which characteristics affect the (degree of) preference for each repertoire. The effects are estimated using a standard multiple regression and are, of course, based on the entire sample. Those with high scores on the ‘regional and public’ dimension are more often male than female (Table 3: 42.3% are women). This is also reflected in the negative gender effect (0.122) in Table 4. It is the oldest audience segment and people who work many hours a week have a relatively small chance of belonging to this group. The time spent on household chores and care-giving, occupational status, and political

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Table 3 Intensive users’ mean scores on each dimension (and mean scores of the entire sample in last column) 1 regio & pub

2 ser info

3 pop & pub

4 woman

5 comm

6 pc hobby

7 internet

8 story

Total sample

% woman Education level Hours paid labor Hours household care Cultural status Economic status Political interest

42.3 3.47 17.2 14.4 0.19 0.15 1.76

43.1 4.15 17.6 13.9 0.16 0.17 1.95

46.6 3.58 14.5 14.8 0.01 0.05 1.83

67.7 3.43 12.3 19.6 0.27 0.27 1.61

54.5 3.13 15.4 16.0 0.42 0.36 1.50

28.2 3.81 19.1 11.0 0.09 0.02 1.67

40.3 4.04 19.5 12.3 0.01 0.02 1.67

55.6 3.91 19.0 14.6 0.03 0.01 1.68

51.5 3.65 19.4 15.3 0.17 0.15 1.64

% age 12 –29 % age 30 –54 % age 55+

4.5 43.8 51.4

14.5 40.9 43.3

8.5 38.8 51.9

16.3 39.9 42.1

34.4 37.8 26.6

29.0 46.8 22.7

31.1 48.3 20.0

25.5 45.6 26.8

27.0 43.5 27.7

% now employed % pensioner % unemployed % housewife % student

51.5 30.2 4.4 11.1 2.8

49.4 27.6 5.5 11.2 6.4

44.8 32.0 5.8 12.7 4.7

42.2 26.4 5.7 20.9 4.7

46.8 17.5 6.6 13.6 15.5

52.3 12.0 5.3 9.1 21.4

57.9 10.6 2.9 10.3 18.2

56.6 16.0 5.5 11.4 10.6

54.4 16.3 4.9 11.8 12.5

% family + children % partner, no child % single % living w. parents

32.9 48.1 16.1 2.8

34.5 39.5 20.0 6.0

28.9 49.5 16.9 4.7

37.9 40.5 16.2 5.4

38.2 30.0 15.2 16.6

33.7 32.5 13.5 20.4

37.3 35.1 10.0 17.5

33.3 38.5 18.4 9.8

37.4 33.6 15.9 13.1

% no religion % Catholic % Protestant % other religion

41.6 38.3 17.4 2.8

50.8 22.2 22.5 4.2

51.7 20.2 23.2 4.6

40.7 31.7 23.8 3.8

59.5 22.9 13.6 3.7

58.4 22.7 16.2 2.7

57.8 23.4 14.0 4.8

57.2 22.9 16.3 3.6

53.3 24.9 17.4 4.4

Source: TBO 2000

interest have no effect on the degree to which people use media from the ‘regional and public’ dimension. This segment contains many pensioners and very few students (Table 3), but these social positions have no independent effect after age has been controlled for (Table 4). The same holds for family constellation: we see many double-income couples (partner, no child) and few people living with their parents, but these deviations from the sample mean seem to have already been accounted for by the effect of age. In addition, the share of Catholics in this audience is high (38.3%; the grand mean is 24.9%). Table 4 shows an independent positive effect of being Catholic relative to having no religion, which is the reference category. Belonging to ‘other religion’ (only 2.8% of this audience), on the contrary, decreased the score on this dimension relative to that of the non-religious. The group with high scores on the ‘serious information’ factor has the highest level of schooling and is most politically interested. The number of hours spent on

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Table 4 Standardized effects of background characteristics of respondents on preferences for media repertoires 1 regio & public

Woman Education level Hours paid labor Hours household care Cultural status Economic status Political interest Age 12–29a Age 55+a Pensionerb Unemployedb Housewifeb Studentb Partnerc Singlec Living with parentsc Catholicd Protestantd Other religiond adjusted R2

2 ser info

3 pop & public

4 woman

0.122*** 0.044 0.019 0.167*** 0.007 0.171*** 0.065* 0.009 0.097* 0.130*** 0.075 0.140*** 0.064 0.172*** 0.110** 0.029 0.046 0.017 0.019 0.144*** 0.205*** 0.024 0.011 0.059 0.041 0.023 0.003 0.026

0.083 0.019 0.090*** 0.041 0.200*** 0.049 0.067* 0.039 0.036 0.109*** 0.059* 0.024

0.064 0.074 0.111*** 0.051 0.124*** 0.181*** 0.027 0.047 0.007 0.016 0.012 0.021

0.101*** 0.067** 0.094*** 0.031 0.004 0.006 0.064** 0.018 0.011 15.30%

15.40%

14.10%

0.078 0.009 0.023 0.014 0.093* 0.055 0.039 0.059 0.038 0.024 0.060* 0.038

5 6 7 commercial pc hobby internet

0.009 0.195*** 0.038 0.037

0.294*** 0.073* 0.118*** 0.067* 0.032 0.089** 0.222*** 0.177*** 0.147*** 0.110** 0.116** 0.119***

0.106* 0.041 0.082** 0.098*** 0.018 0.021 0.018 0.035 0.005 0.048 0.023 0.040

0.012 0.116** 0.007 0.054 0.140*** 0.048 0.010 0.017 0.058 0.009 0.008 0.031

0.080** 0.031 0.045 0.108*** 0.162*** 0.001 0.012 0.046 0.040 14.00%

8 story

9.90%

10.90%

0.034 0.035 0.035 0.007 0.033 0.113** 0.084** 0.029 0.007 0 0.071* 0.036

0.089 0.048 0.002 0.016 0.071 0.053 0.028 0.040 0.020 0.077* 0.099** 0.028

0.002 0.066* 0.053*

0.003 0.100*** 0.027

3.20%

5.20%

Source: TBS 2000 Significance levels: *p< 0.05; **p< 0.01; *** p < 0.001. a Dummy variables: reference is ‘age 30–540 . b Dummy variables: reference is ‘employed’. c Dummy variables: reference is ‘family with children’. d Dummy variables: reference is ‘no religion’.

paid labor and household and care-giving affect the preference for ‘serious information’ media negatively. Those aged 55 and over have significantly higher scores than respondents aged 30–54. Unemployment increases the score on factor 2 relative to being employed6 and belonging to a family with children increases the score 6

As Table 3 shows, on six of the eight dimensions, the unemployed are overrepresented. That this variable has only a positive effect on factor 2 is due to the fact that, in this case, the relationship with unemployment cannot be explained by the other variables in the model. The point is that we are faced here with a group which is highly educated and has a strong interest in politics; these are traits which usually do not go with unemployment. In the case of an audience segment which has a high proportion not only of unemployed but also of less educated people without much interest in politics (as in the case of factor 5, which comprises most unemployed), the relationship between media use and unemployment can be attributed to these traits and we do not find an autonomous unemployment effect in Table 4.

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relative to having a partner but no children or being single. Being Catholic affects interest in serious information negatively. Combining popular national newspapers and public broadcast media (factor 3) is most common among people with just below average schooling levels and a strong interest in politics. Both characteristics significantly affect the score on the ‘popular and public’ factor. In addition, it is again the older group that is most inclined to do this, especially the pensioners. Often, they are members of mini-households (partner, no kids), although this characteristic does not affect this preference taking into account the age and labor market position of this group. Catholics differ significantly from non-religious people; controlling for all other characteristics of this group, being a Catholic negatively affects the factor score for ‘popular and public’. Factor 4 (woman) is, of course, most popular among women. Number of hours in paid labor negatively affects the preference for women’s magazines and free papers, whereas belonging to the age-group 55 and over or being Catholic or Protestant have a positive effect. Singles have a smaller chance of appreciating these print media than people from a family with children (Table 4), although their share in this audience segment does not differ that much from the sample’s grand mean. Apparently, within the group matching the profile belonging to factor 4, especially women with a family and children spend a lot of time on these reading materials. For the lovers of commercial radio and television (factor 5), a negative schooling effect can be discerned. The male-female ratio is about 50–50. Cultural occupational status and political interest show both low scores (Table 3) and negative effects (Table 4). This group is relatively young (over a third is aged below 30) and this is also evident from Table 4 that shows a positive effect of belonging to the category aged 12–29 as compared to those aged 30–54. Furthermore, only being a Protestant has a negative impact, probably because of the dissipated content of the commercial media supply. According to Table 3, those with high scores on the factor representing the use of the PC, reading hobby magazines, and using the Internet for serious information (factor 6: ‘PC, hobby’) are much more likely to be men than women, relatively young, have slightly above average schooling levels, and work longer hours than the groups belonging to the previous five factors. Also, they have above-average cultural and economic occupational status while spending less time on household chores and care-giving. All these characteristics also have an independent significant effect on the score on factor 6, except for the cultural occupational status. In all cases, except for economic occupational status, this effect is negative. That this also holds for the educational effect might seem surprising considering the observation that the average schooling level for those belonging to the upper quartile for this factor is somewhat above average. Yet, we can assume that we are dealing here with a young audience that belongs to a more highly educated cohort, part of which is still enrolled in school. Within this group (with all its characteristics that have been controlled for in Table 4), it is not the highest educated portion that concentrates most vigorously on this repertoire. Factor 7, indexing the use of the Internet for other purposes (not serious information), is predominantly popular among middle-aged working men. Nevertheless,

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the number of hours of paid labor has a negative effect, meaning that, within this group, those with fewer working hours spend more time on the Internet than those with an overloaded working week. The time spent on unpaid work also has a negative effect on the score for factor 7. In addition, we find negative effects for singles and religious people (except Catholics). The combination of videos, books, and de Volkskrant (factor 8: ‘story’) is most popular among women and people with higher levels of education and above-average occupational status (both economically and culturally). The independent effects of occupational status are, however, not significant. Yet, the amounts of time spent on paid and unpaid labor do affect the score on this factor negatively. Although this segment is rather busy in terms of the amount of paid labor carried out, within this segment, the people who work fewer hours have more free time to spend on the media belonging to factor 8. In addition, belonging to a household consisting of only one or two persons increases the score on this factor. The audience for videos, books, and de Volkskrant consists of many members of so-called mini-households. Being Protestant decreases the likelihood of belonging to the audience for factor 8.

6. Discussion The novelty of our approach resides in three things. First, with the help of two different techniques of analysis, we were able to ascertain eight dimensions that underlie the Dutch population’s media use in 2000. By considering which media items co-occur on a particular dimension, it is possible to draw conclusions on users’ media orientation. Second, we made a concrete suggestion on how HCA can be used to depict a stepwise breakdown of the media audience. Third, our approach showed which user traits affect preferences for media repertoires. Certain items form a repertoire because their users find that, together, these items are worth part of their leisure time. With the help of the background characteristics adopted for this analysis, we were able to identify groups that may be regarded as audience segments (the ‘audiences’ in the title of this piece), because, in addition to a certain sociodemographic profile, they share a specific repertoire. To uncover the dimensions, nineteen media items were used. Except for books and video (strongly positive on dimension 8), most media items can be characterized pairwise, in terms of serious or light information, legitimate or light entertainment. We are aware that this is a matter of degree and open to discussion as long as reading or viewing behavior fail to be measured at the level of articles in print media, television programs, etc. The expectations we ventured at the end of Section 2 were confirmed, as indicated in the foregoing section. Subscription costs and distribution mode explain why usually not more than one newspaper occurs per family. Each of the three kinds of newspapers (national-popular, national-quality, and regional) holds a central place on one of the first three dimensions which structure media use. Together they play a crucial role in the differentiation of three major audience segments, which have existed since the beginning of the twentieth century. On the ‘serious information’

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dimension, national quality newspapers even play an exclusive role, implying that the repertoire is homogeneous (one medium type and one content type); the corresponding audience was referred to as ‘information seekers’ (Van Eijck and Van Rees, 2000). On the ‘regional and public’ and ‘popular and public’ dimensions, public television joins the regional and the national-popular newspaper, respectively. The repertoires of those scoring high on these dimensions may be called more heterogeneous, insofar as they intensively use various medium types. This kind of repertoire is both traditional (print and public television are among the ‘older’ media) and, compared with dimension 2, it might be characterized as middle-brow. The ‘regional and public’ and ‘popular and public’ segments are very similar in orientation; together they differ from the ‘serious information’ segment, as public television is an important component of that orientation. Their background characteristics (Table 3) are similar in several respects (both relatively old, many twoperson households, many pensioners, political interest above average), but there are also important differences. Among the ‘regional and public’ segment, people work longer, professional status is lower, and they are more often Catholic. This shows that each of the dimensions appeals to a different audience. In addition to the ‘serious information’ factor, three other factors correspond to fairly homogeneous repertoires, as each appears exclusively oriented towards a single medium type: dimensions 4 (women), 6 (PC hobby) and, most strongly, in the case of dimension 7 (the Internet). Only two of the eight repertoires, namely, those corresponding to factor 2 (serious information) and 5 (commercial, that is, light entertainment), show the highbrowlowbrow contrast Bourdieu assumed. They might be called more homogeneous than the other repertoires because they each focus on a single content type (serious information or light entertainment) derived from a single medium type (print or commercial broadcasting). For these repertoires, education, Bourdieu’s main indicator of cultural capital, has significant effects in the predicted direction; positive for serious information and negative for commercial radio and TV. The effects of political interest on these two dimensions support our interpretation of these dimensions as being opposed to one another on the serious information versus entertainment continuum. This, on its turn, seems to confirm Bourdieu’s theory. However, the analysis in the foregoing section indicates that six out of eight repertoires do not conform to Bourdieu’s axioms of homogeneity and homology. Analyzing the relationship between background characteristics and preferences for media repertoires, we found that in all cases the dimensions significantly differentiate between men and women and/or between age groups. Age and gender are important variables to understand media use. Traditional medium types (especially print media, but also public television) appear to be the exclusive domain of the elderly, while new media (internet) are chosen by the younger generations (mainly men). It seems that the relation between status and media use depends on age: younger people with low schooling levels prefer other media repertoires (the commercial repertoire) than older people with similar schooling levels (repertoire 3: popular and public). Time restrictions negatively affect time spent on almost all repertoires, perhaps with the exception of ‘popular and public’ and ‘commercial.’

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The dendrogram resulting from the hierarchical cluster analysis gives a clear indication of how the media audience can be divided into increasingly refined segments. At the first step, the audience is divided into a segment preferring a set of media, which for the most part provide serious information and a segment preferring a set that offers mainly middle and lowbrow entertainment. This second segment is interested in all radio and television, popular national newspapers, women’s magazines, and free home-delivered weeklies. Here, the distinction by content appears to be primary, but the distinction by medium types is often implied in this. All broadcast media belong to this segment; in the other segment the combination of an old and a new medium type (serious print and digital media) is more likely. In the following steps, content appears to dominate, but at the most detailed level, at the left-hand side of the dendrogram, we frequently find media of the same type within a content domain. With regard to the observed differences between these patterns, our analysis answers the question which media go together as the result of fitting a specific media orientation. The repertoires brought to light by our analysis are indicative of how an audience segment is oriented towards media. Researchers may characterize media orientations in terms of (more or less high) levels of clustering. The decision as to the level one decides upon depends on the research question one is considering. In general, we would recommend taking into account not only the structure and content of the chosen set of media items (positive selection), but also the items that are left out (negative selection). For this characterization it is particularly important to consider the stage of the selection process in which media items are removed from the set of possible (or still acceptable/admissible) options. By considering audience segmentation as a process, we were able to figure out whether content or medium structures such a segmentation. The results show that content and medium type are not independent: serious information is mostly gathered through folio media while broadcast media play a more important role in offering entertainment. At different phases in the segmentation process, different aspects of the media supply matter more. At the first step, all broadcast media fall into the same segment, to be subsequently divided into commercial versus public (content) and, after that, in e.g. regional versus national (also content). If print media go together, serious information is often involved. For digital, interactive media, the medium in itself does seem to play a large structuring role, probably because these media are relatively novel and require specific skills from their users.

Appendix A. Operationalization of items in media repertoires The original variables on which the media items are based indicate the number of quarters of an hour respondents spent on each of the titles selected during the week of diary registration. For all media variables, outliers were removed (see note 1). A number of items were left out of the analysis because less than 2.5% of the respondents used them: the free newspapers Metro and Spits; the category of youth magazines; the category of men’s magazines. The category of ‘compact discs, records

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and cassettes’, also with a low score, was removed for being insufficiently specific with regard to its content. The category ‘advertorial weeklies’ (ADWEEK), that is, weeklies in newspaper format, distributed once a week home-to-home in most urban regions and containing, besides advertisements, municipal news, has been retained. We have been reluctant to join together kinds of media into a single item. If we did so, this occurred on the basis of correlations or because media represent alternatives (e.g. De Telegraaf and Algemeen Dagblad, two instances of popular newpapers). Higher levels of aggregation were already inherent in the original data set, except for hobby magazines. The category of popular national newspapers (Popnewsp) consisted of de Telegraaf and het Algemeen Dagblad. ‘Regional newspaper’ consists of all regional dailies and Het Parool. Opinion magazines comprises: Elsevier, HP De Tijd, Intermediair, Opzij, and Vrij Nederland. The denominational newspapers (Relinwsp) are Trouw, Reformatorisch Dagblad, Nederlands Dagblad. Because of their high correlation, NRC Handelsblad and het Financieel Dagblad were combined under the label NRCFIN. In the light of correlation analysis, de Volkskrant remained a distinct variable. In the coding of the 2000 Time Budget Survey, three different kinds of magazines were subsumed under one label (‘hobby magazines’): Ariadne Wonen, Computer idee, Computer totaal, Doe Het Zelf, Eigen huis en interieur, Knip, Mijn tuin, Sport internationaal, VT wonen, ‘other hobby/computer/sports magazine’. Women’s magazines include: Avantgarde, Cosmopolitan, Elegance, Flair, Libelle, Margriet, Mijn Geheim, Nouveau, Party, Prive, Story, Viva, Vriendin, Yes, and ‘other women’s magazines’. This aggregation permits to limit the total number of variables, which otherwise would have made the results more difficult to interpret. We omitted from the analysis the category of rtv magazines and that of ‘various other magazines’ which does not allow for a more precise identification. Both television and radio are divided into public and commercial tv and radio (TVNETPUB and RADIOPUB, TVCOM and RADIOCOM). In addition, the variable local television (TVLOCAL) is used. The idea of differentiating between older (RTL 4 and 5) and more recent (the remaining) commercial television networks was examined and then abandoned as it failed to improve the analysis. The variable Book Reading was based on an interview question that asked respondents when and if they had finished reading a book for entertainment. Responses were divided into three categories: (a) more than three months ago, (b) 1–3 months ago, and (c) less than a month ago. Although it was not possible to specify pc and video by nature of content, pc and video were maintained as separate media variables. Internet is differentiated by the type of information one uses: information for serious purposes (INTSER) and other information (INTOTHER) Leisure time is defined ex negativo as time that is not spent on paid labor, household, child rearing, or education. Agglomeration schedule [allowing] to ground the adoption of 4 clusters The agglomeration schedule included here shows the coefficients belonging to the dendogram. They permit inferring the distance between the clusters which are joined in a particular step. From the dendrogram one may conclude that joining four

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K. van Rees, K. van Eijck / Poetics 31 (2003) 465–490 Table A1 Agglomeration Schedule hierarchical cluster analysis Step:

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Combined clusters: Item(s) cluster A

Item(s) cluster B

3 4 7 5 9 2 1 3,10 12 6 4,17 6,12,18 2,8 5,14 1,13 3,10,11,2,8 1,13,4,17,15 Result step16

10 17 19 14 16 8 13 11 18 12,18 15 7,19 3,10,11 9,16 4,15,17 5,14,9,16 7,19,12,18,6 Result step17

Distance betw. clusters A & Ba

Difference with previous step

1299.03 2614.08 4112.52 5664.41 7217.29 8773.89 10 374.78 11 987.55 13 687.70 15 414.95 17 142.94 18 974.89 20 807.81 22 698.42 24 595.85 26 833.04 29 153.14 31 699.43

1315.05 1498.44 1551.89 1552.88 1556.60 1600.89 1613.77 1699.15 1727.25 1728.099 1831.795 1833.392 1890.961 1897.043 2237.819 2320.310 2545.529

a This coefficient represents the distance between the two most widely separated items from the clusters which are combined in a step, and rendered as squared Euclidean distance.

clusters into a smaller number is accompanied by a relatively long distance along the x-axis. This is confirmed by the coefficients. The last step before reaching the fourcluster solution, that is, step 15, where subsets 1–13 and 4–15 are joined, goes with a difference in coefficients of 1897.043 (see the column at the right in Table A1). When in step 16 the four-cluster solution is condensed by joining subsets 3–8 and 5–16, this difference score increases to 2237.819. The hierarchical cluster analysis displays a stepwise process that is covered from beginning to end, but a coefficient increase of this size means that the joining of sets 3–8 and 5–16 is statistically awkward. This also holds for the combination of sets 7–6 and 1–15, which goes with a coefficient’s increase of 2320.31. Yet, with a coefficient increase of 2545.529, the last step, where all items are combined, gives the most serious statistical trouble.

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Ganzeboom, H., de Graaf, P., Kalmijn, M., 1987. De culturele en de economische dimensie van beroepsstatus. The cultural and economic dimension of professional status. Mens en Maatschappij 62, 153–175. De Haan, Jos, 2001. Media en ICT: omgaan met een overvloedig aanbod. In: Breedveld, Koen, van den Broek, Andries (Eds.), Trends in de Tijd. SCP, Den Haag, pp. 75–94. Knulst, Wim, Kraaykamp, Gerbert, 1996. Leesgewoonten: Een Halve Eeuw Onderzoek Naar het Lezen en Zijn Belagers. SCP, Rijswijk. Knulst, Wim, Kraaykamp, Gerbert, 1998. Trends in leisure reading: forty years of research on reading in the Netherlands. Poetics 26 (1), 21–41. Kubey, Robert, 1996. On not finding media effects: conceptual problems in the notion of an ‘‘active’’ audience (with a reply to Elihu Katz). In: Hay, J., Grossberg, L., Wartella, E. (Eds.), The Audience and its Landscape. Westview Press, Boulder, CO, pp. 187–205. McQuail, Denis, 1991. Mass Communication Theory, 2nd Edition. Sage, Newbury Park, CA. McQuail, Denis, 1992. Media Performance: Mass Communication and the Public Interest. Sage, Thousand Oaks, CA. McQuail, Denis, 1997. Audience Analysis. Sage, London. Norusis, Marija J., 1994. Professional Statistics 6.1. SPSS Inc, Chicago. Peterson, R. A. 1992. Understanding audience segmentation: From elite and mass to omnivore and univore. Poetics 21 (4), 243–258. Van Eijck, Koen, van Rees, Kees, 1999. Patronen van printmediagebruik 1975-1995: Een latente-klasse analyse van veranderingen in lezerstypen. Tijdschrift voor Communicatiewetenschap 27, 125–151. Van Eijck, Koen, Van Rees, Kees, 2000. Media orientation and media use: Television viewing behavior of specific reader types from 1975 to 1995. Communication Research 27, 574–616. van Eijck, Koen, Knulst, Wim, van Rees, Kees, 2001. Van oude en nieuwe media. Economisch Statistische Berichten, 18 mei 2001, pp. 440–442. Van Rees, Kees, Vermunt, Jeroen, Verboord, Marc, 1999. Cultural classifications under discussion. Latent class analysis of highbrow and lowbrow reading. Poetics 26 (5–6), 349–365. Rosengren, K.E., 1996. Combinations, comparisons and confrontations: toward a comprehensive theory of audience research. In: Hay, J., Grossberg, L., Wartella, E. (Eds.), The Audience and Its Landscape. Westview Press, Boulder, CO, pp. 23–52. Weibull, L. 1992. The status of the daily newspaper. What readership research tells us about the role of newspapers in the mass media system. Poetics, 21/4, 259–282. Koen van Eijck is assistant professor at the Department of Leisure Studies, Tilburg University, The Netherlands. His research project concerns cultural participation and trends in time allocation. Van Eijck has published on the subjects of socialization, media use, and cultural consumption patterns. Kees van Rees is associate professor at Tilburg University, The Netherlands, and editor of Poetics. Current research areas include trends in cultural participation and media use, and resources and constraints affecting the operation of institutions in the literary field.