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Gledaj (TV) i uči? Važnost (utjelovljenog) kulturnog kapitala u objašnjenju klasične i digitalne medijske pismenosti

Krešimir Krolo orcid id ; Odjel za sociologiju, Sveučilište u Zadru, Hrvatska

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Glavni je cilj ovog rada ustanoviti mogu li različite dimenzije kulturnog kapitala utjecati na razinu klasične i medijske pismenosti na podatcima prikupljenim 2022. godine u sklopu projekta "Medijsko obrazovanje je važno" (N = 1033). Unutar Bourdieuova teorijskog okvira, kao nezavisne varijable operacionalizirane su tri dimenzije kulturnog kapitala: objektificirani, utjelovljeni i institucionalizirani kulturni kapital. Utjelovljeni kulturni kapital predstavljen je kroz ukus u TV programima, a objektificirani kulturni kapital kroz broj knjiga u kućanstvu, dok je institucionalizirani kulturni kapital definiran kao postignuta razina obrazovanja ispitanika. Klasična medijska pismenost operacionalizirana je kao kritičko čitanje medijskih poruka, dok je medijska pismenost u digitalnom okruženju operacionalizirana kao stvaranje online digitalnog sadržaja. Obje su te varijable korištene kao zavisne varijable u analizi. Nakon provedene faktorske analize glavnih komponenti (PCA), provedena je i hijerarhijska regresijska analiza kako bi se utvrdilo ima li kulturni kapital objašnjavajuću moć za obje dimenzije medijske pismenosti. Rezultati upućuju na statistički značajnu ulogu objektificiranog kulturnog kapitala u objašnjavanju klasične medijske pismenosti, iako ostaje upitnom statistička snaga tog objašnjenja. Medijska pismenost u digitalnom okruženju nije pokazala statistički značajnu povezanost s nijednom od triju dimenzija kulturnog kapitala. Međutim, dodatna analiza upućuje na važnost digitalnih vještina kao snažnijeg čimbenika u objašnjavanju klasične i medijske pismenosti u digitalnom okruženju. Sveukupno, digitalni kapital predstavlja relevantniji čimbenik razlikovanja od klasičnoga kulturnog kapitala korisnika u suvremenom medijskom okruženju. Ti podatci upućuju na zaključak kako se medijska pismenost primarno oblikuje kroz različite oblike digitalnog kapitala, no svejedno se uloga televizijskog sadržaja ne bi trebala isključiti iz razvoja budućih programa medijske pismenosti.

Ključne riječi

klasična medijska pismenost; medijska pismenost u digitalnom okruženju; kulturni kapital; digitalne vještine

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Podaci na drugim jezicima: engleski

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The concept of media literacy initially aimed to increase competencies in critically interpreting media messages. However, within the context of a platform society (van Dijck, Poell and De Waal, 2018), media literacy deals with challenges related to accessing media and critically understanding media messages. Watching television, listening to the radio, and reading a magazine were less about accessing media technology and more about how the audience was dealing with the quality of messages. In the age of the mass media environment, technical competencies required less skilled knowledge in navigating the structure of the medium (i.e., switching TV channels, changing radio stations). Therefore, there was no emphasis on access and skills regarding the use of media technologies (DiMaggio et al., 2004;Zillen and Hargittai, 2009;Van Deursen and Van Dijk, 2014;Van Dijk, 2017). On the other hand, the relationship between the audience and mediated messages has become more complex with the growing integration of digital communication into everyday life. Early internet diffusion was all about the issue of access, whether it was access to an internet connection or owning personal computers. The most common denominator regarding the growing inequalities in internet communication was “the digital divide” (Ragnedda and Muschert, 2013;Warschauer, 2003;van Dijk, 2020). In contrast, the subsequent stages of internet access started to ask more frequent questions regarding users’ digital skills (Scheerder et al., 2017;Blank and Lutz, 2018).

Additionally, considering media literacy as practical knowledge for critically analyzing media messages has led to questions about whether other sociocultural factors play a role in distinguishing between those who are media literate and those who are not. For example, various scholars have questioned the role of education, socioeconomic status, gender, and the type of settlement in relation to media literacy (Aufderheide, 1993;Liubiniene and Thunqvist, 2015;Park, 2012) . At the same time, more sociologically structured approaches tend to use the concepts of capital, primarily cultural and social capital (Ragnedda and Ruiu, 2020). With the more profound embeddedness of digital communication in everyday social activities, these issues seem even more important as they also deal with the problems of inequality around access and skills used in the “platform society” (van Dijck, Poell and De Waal, 2018). The discussion started to centre around whether cultural capital as a standalone theoretical approach offers enough potency to explain traditional media literacy and digital literacy. This led to the establishment of a separate form of capital – digital capital (Ragnedda and Ruiu, 2020). The concept of digital capital extended the existing theoretical framework of cultural capital as a specific form of capital accumulated within the digital paradigm. Relying on Pierre Bourdieu’s concept of cultural capital (1984), the level of education as an institutionalised type of cultural capital was the most common denominator in various research projects (Clark, 2001;Aesaert and Van Braak, 2015). However, embodied and objectified cultural capitals were either missing or vaguely operationalised.

Therefore, the main goal of this paper is to introduce more robust measures for embodied and objectified cultural capitals as potential indicators of differences in traditional and digital media literacy. This will also help find out whether cultural knowledge is a better explanation for media literacy compared to digital tools and factors.

Definition of Media Literacy Within the Contemporary Media Environment

There are two main approaches to defining media literacy. The first deals with the issues of skills and knowledge or the combination of both. The second examines how family and the education system are embedded within the general framework of media literacy (Bilić, 2022: 7). For this analysis, media literacy is defined as “the ability to access, analyse and evaluate media messages that were created in various contexts” (Christ and Potter 1998 according toLivingstone and van der Graaf, 2008: 2926). This is similar to a definition by Hobbs (2019: 581) who states that “media literacy can be understood as knowledge, skills and life skills necessary to participate in contemporary society with the access, evaluation and creation of media messages in various forms". These definitions offer a valuable theoretical framework within the “old” media environment, where access and skills were less emphasised. However, in the digital environment of the platform society (van Dijck, Poell and De Waal, 2018), the issues of access and skills can potentially contribute to drastic differences regarding the outcomes of one’s media literacy.

Bilić (2022) summarises this ambiguity by offering an overview of the new challenges the digital media system brings in terms of media literacy. These challenges involve the expansion of skills and knowledge necessary for individuals to be competent and active participants in the structures of the platform society. This literacy includes not only access to and ownership of digital devices but also the more specific skills necessary for navigating the newfound complexities of the digital environment, like understanding the role of big data, algorithms and artificial intelligence (AI) in creating biases and structuring our perception of reality. Bilić (2022) also emphasises epistemological differences between media and digital literacy. On the one hand, media literacy relies heavily on theoretical inputs from semiotics, cultural studies or critical theories, serving as an essential tool for deconstructing and analysing media messages. On the other hand, digital literacy puts more weight on the usage and skills relating to media and technology.

Consequently, digital literacy relies more on theoretical approaches that see usage and skills as indicators of social distinctions and inequalities. Differences between usage and skills provide an essential insight into how an actual instrumentalisation of digital technologies creates structural gaps within and between societies. This difference becomes especially visible when considering the creation of new content, as it provides more opportunities for the individual to enhance their life chances and fosters participation in digital societies, becoming an increasingly important factor in social inclusion. In conclusion, digital literacy can be defined as a “more or less stable set of uses and practices regarding computer and digital tools and platforms, without necessarily understanding their design, functioning and finalities” (Frau-Meigs, 2012:19)

Therefore, media literacy can generally be reduced to three main dimensions: critical thinking, technical skills and content production. As mentioned before, this analysis will focus on critical thinking as a type of “traditional” media literacy and content production as an upgraded type of digital literacy. For clear distinction, the type of media literacy associated with critical thinking will be dubbed “traditional media literacy”, while content production will be dubbed “digital media literacy”.

Expanding the Role of Cultural Capital in the Understanding of Media Literacy

Research on the role of cultural capital in the field of news media literacy exhibits certain shortcomings. For example, cultural capital is usually considered a contributing factor only in the aspect of institutionalised dimensions (i.e., the level of education) and is rarely expanded to other parts of the cultural capital, especially embodied capital (Di Maggio and Hargittai, 2001;DiMaggio et al., 2004;Helsper and Reisdorf, 2017).1 Expanding the framework along the lines of the division of cultural capital as proposed by Bourdieu (1984) offers a higher resolution outlook at what constitutes differences between traditionally media literate individuals and those who are digitally creative. What is the relevant aspect of embodied cultural capital if we consider it a plausible factor of traditional media literacy? A critical argument can be found in the notion that embodied taste is usually structured around various preferences in arts and culture and is also extensively used as a predictor of social distinction and social stratification. Suppose embodied cultural capital can be used as a potent predictor for taste in art and various cultural practices and participation. Can it also serve as an explanatory variable for traditional and digital media literacy? One potentially powerful predictor can be found in taste in TV genres. For example, research by Bennett et al. (2009) concluded that the respondents most frequently separate TV content into two distinct categories. The first category is TV content with pedagogical value as it offers its audience content from which they can learn and obtain new knowledge. The other category is distraction or escapism, where TV content is most frequently used as a time filler. This disposition potentially represents an additional information and knowledge accumulation source that can “spill over” into other forms of capital or, in this case, traditional and digital media literacies. Different arguments can also be found in the research from the same author (Bennett, 2006), as the data points to the separation of the TV genres into three levels of legitimate taste. Low legitimacy is represented by content like quiz shows, soap operas, reality and talk shows, medium legitimacy through sitcoms, crime and culinary/gardening shows and high legitimacy through news, arts and culture, documentaries and dramas.2

Taking all these arguments into account, I have created a scale for TV content preferences and genres that people can enjoy through digital streaming platforms or traditional terrestrial/cable broadcasts. Additionally, it can be argued that this taste represents an immersion of the individuals into specific themes and narratives. This immersion can be divided between “light” entertainment, as illustrated with talent and reality shows, soap operas and glamour shows, or more “serious” content, usually represented by crime shows, science-fiction, fantasy or thrillers. The reason why this analysis assumes differences in taste in these two specific dimensions can be found in previous research (Tonković, Krolo and Marcelić, 2020;Tonković, Marcelić and Krolo, 2021;Marcelić, Tonković and Krolo, 2022;Krolo, Tonković and Marcelić, 2020;Bennett et al., 2009;Bennett, 2006) and in the argument that these TV productions offer specific content with different aims and goals. “Light” entertainment TV aims to provide content that requires less cultural competencies and codes. Therefore, it is considered to be more “democratic” when compared to TV content that is “serious”. Fiction programmes, especially those in foreign languages, because in Croatia dubbed movies are only reserved for children’s movies and animations, require proficiency in a foreign language and the knowledge and aspiration to be involved with the more complex relationships between storylines and characters. In other words, “light” entertainment will not raise critical questions. It will not appear to analyse complex sociocultural relationships between individuals and society. At the same time, fictional programming is heavily saturated with content that asks more complex questions with critical insight.3 Due to this relation, I conclude that fiction genres will probably provide more potent explanatory power for traditional media literacy.4

This argument can also be expanded into digital media literacy, especially considering skills related to content creation. While there are limited systemic examinations and research on the typology of digital media users via the role of (embodied) cultural capital (Leguina and Downey, 2021), substantial research has been conducted regarding the typology of users in various sociocultural contexts (Brandtzӕg et al., 2011). What can be extrapolated from these studies is a clear difference between users who “mess around” (Mizuko et al., 2013) with digital technology in a more creative and engaged manner and users who only observe. The users who only observe as disinterested spectators either have the necessary skills and knowledge to participate in content creation but lack the will or they are intrigued spectators who lack the skills and knowledge to be more digitally productive. Subsequently, Bourdieu’s structure of capitals was expanded with the concept of “digital capital” (Ignatow and Robinson, 2017;Halford and Savage, 2010), although this introduction was not met with unanimous approval (Ragnedda and Ruiu, 2020:30). Again, there were no apparent attempts to determine whether other forms of cultural capital, specifically embodied and objectified cultural capital, hold any explanatory power for the digital type of literacies.

For the same reasons as with traditional media literacy, it is assumed that specific types of TV preferences will significantly correlate with the content creation dimension of media literacy. The first argument for this perspective can be drawn from the interconnectedness of globally oriented TV production and cosmopolitan values. Stronger preferences, especially for foreign fictional programming, can be in proximity with the immersion into the technology that produces and streams that content. The second argument relies on the interconnectedness of digital pioneering and innovation adoption with specific types of audiences and subcultures, especially in science-fiction, fantasy, and animation. (Menadue and Jacups, 2018;Jenkins et al., 2015). Considering the significant differences between the consumption of localised and global TV products (Tonković, Krolo and Marcelić, 2020;Tonković, Marcelić and Krolo, 2021;Marcelić, Tonković and Krolo, 2022;Krolo, Tonković and Marcelić, 2020) based on cultural preferences and tastes, I assume that there will also be a visible difference within this dataset. Respondents with stronger preferences for localised and domestic reality-spectacle content will display lower confidence in online content creation than those who prefer more foreign fiction TV programmes. Finally, the starting assumption is that there will be no manifest or latent information regarding the usage and skills revolving around digital media and technology, just as there is no content that critically addresses media messages and content production in general.

Research Questions and Hypotheses

The main goal of this paper is to establish a relationship between various dimensions of cultural capital and the selected measurement of media literacy. In doing so, I aim to gain a better understanding of the distinctions that structure inequalities regarding the literacies mentioned above. Therefore, the research questions and hypotheses are defined as follows:

Q1. Is there a correlation between various dimensions of cultural capital and traditional media literacy?

Q1H1. More books in the household explain a more critical perception of media content and messages (traditional media literacy)

Q1H2. A higher level of education explains a more critical perception of media content and messages (traditional media literacy)

Q1H3. Greater preference for foreign fiction and educational-informative TV programmes explains a more critical perception of media content and messages (traditional media literacy)

Q2. Is there a correlation between various dimensions of cultural capital and digital media literacy?

Q2H1. More books in the household explain increased online content creation within the context of digital media.

Q2H2. A higher level of education explains increased online content creation within the context of digital media.

Q2H3. Greater preference for foreign fiction TV genres explains increased online content creation within the context of digital media.

Q3. Is there a correlation between various aspects of digital literacy and media literacy?

The reasoning behind this research question can be found in the literature overview which establishes that media-literate individuals transfer knowledge from traditional media to the digital realm (Ragnedda and Ruiu, 2020). Additionally, the relationship between skills and the usage of digital media and technology in explaining both critical perspectives towards online and content in traditional media is straightforward and should be closely examined.

Q3H1. A higher level of information query online explains increased online content creation (digital literacy) and a higher critical perception of traditional media (traditional media literacy).

Q3H2. A higher level of critical perception of digital news content explains increased online content creation and a higher perception of traditional media (traditional media literacy).

Q3H3. A higher critical perception of traditional media (traditional media literacy) explains increased online content creation (digital media literacy).


The main approach involved tackling conceptual challenges and defining traditional and digital media literacy. This led to the creation of scales and tools to handle these matters. For example, the traditional framework of media literacy consisted of the individual’s capacity to critically estimate news messages regarding the message’s author, meaning, representation and social reality, and the self-evaluation of media literacy. The EU standard for measuring media literacy is an estimate of skills, critical thinking, and communication capabilities.

Digital media literacy, unlike media literacy, is structured around technical competencies on the scale of internet skills (Internet skills survey). These dimensions include management of basic operation skills, formal skills, searching for information online, communication skills, creative skills, and strategic skills (van Deursen et al., according toBilić, 2022:13). Similar dimensions have been used in other surveys (Ferrari, 2013).

The data used in this paper was generated from the survey conducted through the “Medijsko obrazovanje je važno” project (UP. Responses were collected in 2022 with the combination of an online panel (Computer-assisted web interviewing – CAWI) and face-to-face surveys (Computer-assisted personal interviewing – CAPI) on a two-stage stratified nationally representative quota sample (N=1033). With the CAWI method, 84% of the data was collected, while the remaining 16% was obtained through the CAPI method. (Bilić, 2022:14) The combination of the CAWI and CAPI methods was used to comply with COVID-19 safety measures and protocol restrictions.

Table 1. Structure of the sample
GenderN%N after ponder% after ponderPopulation data
(adapted from Bilić, 2022: 15)


Independent variables

Cultural capital

Multiple dimensions of cultural capital were used to clearly define the role of cultural capital in explaining traditional media and digital media literacy. For example, cultural capital operationalised along the lines of the work of Pierre Bourdieu (1984) was divided into three main parts: objectified, embodied, and institutionalised. Objectified cultural capital was measured through the variable representing the number of books in the household5, while embodied cultural capital was assessed based on taste in TV genres and programmes. Next, institutionalised cultural capital was measured as the respondents’ education levels. The number of books in the household and the level of education were measured as unique face-value items (“How many books do you have in your household?” and “What is the obtained level of your education?”). Television preferences were operationalised in the form of a 16-item scale with binary structured answers (“I like it” and “I do not like it”) with the added value in the form of “I do not know this genre”, which was later excluded from the analysis. Explanatory factor analysis with varimax rotation was used to determine the latent dimensions of the scale, while reliability was measured using with the Cronbach alpha coefficient. This resulted in three indexes: 1) TV preferences in news and education programmes with a total of five items: TV shows with news and politics, contact TV shows with daily political topics, TV shows about culture and science, agricultural shows and documentary programmes (M= 2.50, SD=1.51, Cronbach α =0.62); 2) TV preferences in domestic and reality-spectacle programmes, also with five items: talent and competition shows, lifestyle and glamour, culinary shows, reality TV and domestic and foreign soap operas (M= 2.44, SD=1.58, Cronbach α =0.68) and 3) TV preferences in foreign fiction programmes with seven items in total: Hollywood movies and blockbusters, foreign science-fiction (SF), foreign fantasy shows, foreign sitcoms, foreign crime shows, independent and art movies and, finally, animated TV shows and movies (M= 10.06, SD= 2.06, Cronbach α= 0.72 ).

Other variables regarding the usage, knowledge, and perception of online news content

The scale of internet usage in the past three months, with 14 items altogether, did not manifest a satisfactory level of reliability. Factor analysis showed the existence of four specific dimensions of internet usage, but for each of those dimensions, Cronbach α was too low to be used for further analysis. However, the internet orientation management scale consisted of eight items, such as “It is hard for me to find the website I am looking for”, “Online browsing is tiresome to me”, and “I am often confused by the design of websites.” The scale shows a high level of reliability as a unique one-dimension scale (M= 18.13, SD=5.83, Cronbach α = 0.88). This index was dubbed “information query online” in the regression analysis. The scale measuring the perception of differences in online news content consisted of six items that included questions like “Are you concerned about the validity of information from internet portals?”, “Are you concerned about the validity of information from search engines (Google or Bing)?”, and “Are you concerned about the validity of information from Facebook?”. Explanatory factor analysis with varimax rotation established one-dimensional characteristics of the scale. (M= 2.21, SD= 2.33, Cronbach α = 0.73).

Dependent variables

Considering that the definition of media literacies includes dimensions like the critical interpretation of media messages and content creation, those two dimensions were used as separate units of media literacy for this analysis. The critical dimension was dubbed “traditional media literacy” as it represents the form of literacy developed before the rise of the "network society" (Castells, 2010). Online content creation was dubbed “digital media literacy” as it assumes that productivity in content creation will mostly be visible within the technological affordances of the platform society (Van Dijck, Poell and De Waal, 2018).

Traditional media literacy – critical dimension

The critical dimension of media literacy was measured using an index of perception related to the message and content production of traditional media using a scale with a total of 13 items. It was used as a one-dimensional instrument with unique measuring qualities (M=54.6, SD= 6.07, Cronbach α = 0.76) with responses ranging from 1 = completely disagree to 5 = completely agree. It included items such as “Media owners are influencing the content that the media is producing”, “Media companies are choosing content that will attract a larger audience”, or “News affects people, whether they are aware of it or not” and “News is created in such a manner to attract attention.”

Digital media literacy – online content creation

The digital component of media literacy was measured using several scales and instruments to grasp the complexity of skills and usage of digital media and technologies. However, only online content creation was used as a dependent variable. The online content creation scale included items such as “I know how to create new content from existing pictures, videos or music materials”, “I know how to make basic adjustments to content that was created by someone else”, “I know how to design a website”, “I know which online content is subject to copyright”. Explanatory factor analysis with varimax rotation established one-dimensional characteristics of the scale (M=19.82, SD= 4.1, Cronbach α = 0.75).

Statistical Analysis

In order to establish which factors contribute to explaining the level of traditional media and digital media literacy, hierarchical regression analysis consisted of three separate blocks of variables. For both dependent variables, the first and second blocks were the same as they consisted of sociodemographic variables (gender, age, type of settlement, socioeconomic status) and measures of cultural capital (number of books in the household, TV preferences and the obtained level of education of the respondents). The third block for the traditional media literacy regression analysis consisted of three digital literacy variables: information query online (knowledge), online content creation (skills), and the perception of differences in online and offline news content (critical perception). The block of digital media literacy variables in the form of content creation was used together with information query online and the perception of differences in news content.


Initial bivariate analysis showed a statistically significant correlation between independent and dependent variables (Table 2), which resulted in applying hierarchical regression analysis in order to determine the contribution of variables in explaining the dependent variables (media literacy and digital literacy).

Table 2. Correlation coefficients between media literacy, digital literacy and cultural capital
CULTURAL CAPITALTraditional Media LiteracyDigital Media Literacy
Objectified cultural capital
Number of books in the household0.360.135**
Embodied cultural capital
TV preferences domestic reality-spectacle-0.093**0.72
TV preferences news and education programme-0.390.54
TV preferences foreign fiction programme0.133**0.267**
Institutionalised cultural capital
Level of education0.112**0.091
Perception of differences in news content0.139**0.023
Information query online-0.206**-0.251**
** p<0.01

According to the results in Table 3. the explanation of the total variance is 16.7% for the medial literacy variable. In Model 1, the respondents' sociodemographic variable in the form of income shows strong predictability for media literacy, which remains significant in subsequent models (Model 2 and Model 3). Age, type of settlement, gender and social status showed no significant correlations with the criterion variable, and the entire block explained 7% of the overall variance. With the introduction of the set of cultural capital variables (Model 2), the percentage of total variance explained increased from 7% to 9%, where having fewer books in the household (no more than 25) displayed a contribution to the overall model (β= -.375**) as it remained significant in the third model as well. Although the overall contribution to the model is low (2%), it remains a relevant factor in explaining the critical approach to traditional media.6 Finally, the third model, consisting of various online skills and digital media usage, increased the contribution to the overall variance explained by 7.5% and therefore proved to be more relevant than cultural capital in explaining the critical approach to traditional media or media literacy in this case. Specifically, this is visible in the skills to search for relevant information online (β=.147) and the perception of differences in (online) news content (β=.264). Considering the hypothesis that this regression analysis tested, Q1H1 was the only proven statistically significant contributor to the overall regression model. In other words, only the objectified type of cultural capital in the form of books in the household has some explanatory power for the (traditional) media literacy variable.

Table 3. Regression model for traditional media literacy
Critical perception of traditional media (media literacy)
Independent variablesModel 1Model 2Model 3
Gender (ref= men)0.022-0.0280.010
Age (30–44) (ref=18–29)0.1220.1690.125
Age (45–49)0.0660.0790.077
Age (60–74)-0.017-0.027-0.035
Age (75 and above)0.009-0.015-0.007
Type of settlement (ref = rural)-0.062-0.097-0.113
Income of the respondents0.232**0.189**0.181**
Permanently employed (ref= retired)-0.030-0.0150.031
In school/studying0.1990.1700.134
Up to 25 books (ref= more than 200) -0.375**-0.324**
101–200 -0.174**-0.239**
Elementary school or less-0.0480.000
Three-year high school programme0.019-0.017
College education0.002-0.015
University level of education (ref= gymnasium)-0.018-0.005
TV preferences domestic reality-spectacle-0.018-0.054
TV preferences news and education programme0.0640.042
TV preferences foreign fiction programme0.000-0.058
Information query online 0.147**
Online content creation-0.008
Perception of differences in news content 0.264**
ΔR2 0.0220.76
* p<0.05, **p<0.01

The results presented in Table 4 for the “Online content creation” or the digital literacy variable show more predictive value as the overall explanation of the total variance is 20%. Unlike the traditional media literacy variable, in the first block of the variables (Model 1), the sociodemographic variables did not contribute statistically significantly to the regression model (F=1.311, p=.214, R2=.017). However, self-employment proved to be a significant factor by introducing the digital skills and literacy variables into the equation, suggesting that content creation is possibly positioned within the broader spectrum of creative industries and technologies context. The second block, which included variables from objectified, embodied, and institutionalised cultural capital, increased the explanation of the total variance from 2% to 8%, but no statistically significant beta coefficients were reported (F=1.834, p=.015, R2=.081).7 Finally, the third block that was introduced (digital skills and usage) raised the explanation of the total variance by 12% (F=3.004, p=0.000, R2=0.20) with variables like the perception of differences in news content (β=.277) and information query online (β= -.282) showing statistically significant beta coefficients. Overall, this model proved that skills related to various aspects of digital and media literacy have a more substantial explanatory power than the multiple dimensions of cultural capital. However, cultural capital relates to digital literacy through online content creation. It can be postulated that it can also be exchanged for other forms of capital. Therefore, regarding the hypotheses surrounding the Q2, they can be partially accepted as positive findings but with visible limitations.

Additionally, the Q3 hypothesis displays stronger explanatory power for traditional media literacy and online content creation but with noticeable differences between the dimensions. For example, while the perception of differences in news content shows a positive correlation coefficient with online content creation as an extension of traditional media literacy with a critical approach, more technical skills in the form of information queries online are negatively associated with online creative content. Therefore, hypothesis Q3H1 is rejected, while hypothesis Q3H2 is accepted. Hypothesis Q3H3, on the other hand, showed no statistically significant correlation between the two variables and is therefore also rejected.

Table 4. Regression model for digital media literacy
Online content creation
Independent variablesModel 1Model 2Model 3
Gender (ref= men)-0.057-0.076-0.059
Age (30–44) (ref=18–29)-0.020-0.065-0.086
Age (45–49)-0.154-0.176-0.142
Age (60–74)-0.143-0.229-0.188
Age (75 and above)0.017-0.0470.005
Type of settlement (ref = rural)0.077-0.005-0.009
Income of the respondents-0.069-0.121-0.121
Permanently employed (ref= retired)0.1200.0300.112
In school/studying0.1050.0570.072
Elementary school or less-0.097-0.062
Three-year high school programme0.009-0.032
College education0.1200.094
University level of education (ref= gymnasium)0.0460.056
TV preferences domestic reality-spectacle 0.015-0.004
TV preferences news and education programme0.1170.056
TV preferences foreign fiction programme0.1550.126
Perception of differences in news content 0.277**
Critical perception of traditional media0.003
Information query online -0.282**
ΔR2 0.60.120
* p<0.05, **p<0.01

Discussion and Conclusion

The hierarchical regression analysis revealed several key findings. Firstly, both traditional media literacy and higher-tier digital media literacy, specifically online content creation, were influenced by cultural capital to some extent. However, this correlation was primarily explained by objectified cultural capital, while embodied cultural capital in the form of taste in TV genres did not show a significant statistical relation. Despite this, the combined cultural capital variables significantly contributed to explaining the total variance in the criteria variables, highlighting their importance. Secondly, the conventional measures of cultural capital did not strongly correlate with traditional and digital media literacy. In contrast, digital media skills and usage proved to be more influential factors. This suggests that digital capital could be considered a distinct measure of capital, at least in the context of traditional media and digital media literacy. Thirdly, the lack of a significant relationship between embodied cultural capital and traditional media literacy may be attributed to its presence mainly among the “digitally native” generation (1Prensky, 2001). This indicates that cultural capital may be saturated around more fragmented and diverse content consumption patterns, leading to notable intergenerational differences (Tonković, Krolo and Marcelić, 2020;Tonković, Marcelić and Krolo, 2021;Marcelić, Tonković and Krolo, 2022;Krolo, Tonković and Marcelić, 2020;Bennett et al., 2009). Furthermore, for older age groups in the sample, TV preferences were less predictive of traditional and digital media literacy, suggesting that TV as a medium may be less relevant for alternative learning and skill development among older people.

The regression analysis of digital media literacy revealed varying levels of relevance among the different variables. Unlike traditional media literacy, cultural capital, as represented by the number of books in the household, did not noticeably impact respondents' confidence in online content creation. This suggests that knowledge acquired from books has a lesser impact on the accumulation of digital skills and capital. Instead, the perception of differences in news content and online information queries proved to be statistically significant predictors of digital media literacy. However, an interesting contradiction emerged, as the perception of differences in news content showed a positive association with the index of online content creation. In contrast, online information queries exhibited a negative correlation. This disparity could be attributed to the nature of the online content creation scale, which primarily focuses on lower-tier activities such as status updates and reel creation. Conversely, more advanced usage of technologies, like website creation, appeared to be more relevant and influential. Additionally, while income did not show statistical significance, self-employment status played a role in the model. However, further data is required to substantiate the hypothesis that gig economy jobs significantly contribute to online content creation.

In conclusion, the analysis indicates that embodied cultural capital had little relevance for traditional and digital media literacy. However, preferences for foreign fiction on TV did show a relatively high beta coefficient and contributed significantly to the model prior to the introduction of digital skills measures. These findings emphasise the importance of considering structural determinants in understanding media literacy within the platform society. Social groups with lower cultural capital are likely to exhibit lower media literacy within the Croatian population. Further analysis is needed to explore finer distinctions and potentially new forms of inequality that arise from usage and skills related to the contemporary media landscape.

Limitations of the Study and Future Recommendations

This study has certain limitations that warrant attention. Firstly, a qualitative approach involving focus groups and in-depth interviews would provide valuable insights into the role of embodied cultural capital in explaining traditional and digital media literacy. This methodological approach could establish a clearer relationship between specific cultural content and the development of skills and critical understanding of mediated messages. Secondly, creating a TV genres scale incorporating more nuanced distinctions between genres and subgenres would help highlight potential differences among respondents. Thirdly, introducing a scale that captures perceptions of content within each genre could enhance our understanding of how taste in TV genres relates to different aspects of media literacy. Fourthly, since proxy variables are used as an indicator for the two literacies, traditional and digital media literacies were reduced to just one component. Lastly, alternative quantitative methodologies, such as multiple correspondence analysis, should be considered to explore the relationship between different forms of cultural capital and both traditional and digital media literacy within the social field.

Despite these limitations, the analysis offers several policy implications. Firstly, media literacy is not solely acquired through formal education focused on these subjects but also through engagement with other cultural content that carries pedagogical value. Therefore, TV programmes that critically address or assess the role of digital media and technology in everyday life should be seen as additional tools for fostering critical discussions and learning. Such programmes can provide contemporary and relevant material for the target audience.


This research was part of the project “Medijsko obrazovanje je važno” (UP. co-funded by the European Social Fund (ESF) and the Croatian state budget.


The author declares no conflict of interest.


Ethical approval was issued by the Institute for Development and International Relations in Zagreb (IRMO) on 26 January 2022.


Anonymised data and analytical material are available from the author upon request.


[1] A higher level of education is correlated with more skills, knowledge and engagement with digital technologies and the media.

[2] However, this separation must be taken cum grano salis as it was extrapolated from data collected in the early 2000s. In the meantime, other research points to the clustering where main distinctions can be found between fictionalised genres and reality-spectacle (Tonković, Krolo and Marcelić, 2020;Tonković, Marcelić and Krolo, 2021;Marcelić, Tonković and Krolo, 2022;Krolo, Tonković and Marcelić, 2020).

[3] It is also worth mentioning that Kuipers (2006) established “fine“ distinctions regarding the taste in comedy content. Upper-class educated professionals, on average, tend to enjoy humor saturated with meta-narrative layers, while lower-educated working-class respondents often prefer slapstick humor. This may potentially extend to other genres. For example, crime shows and thrillers incorporating political and media narratives with stronger spy motives can provide more potential for information transfer into digital capital than crime shows dealing with corporal or property crimes.

[4] For a detailed description, see Bilić (2022).

[5] The variable “number of books in the household” has certain limitations. For example, Sieben and Lechner (2019) pointed out that this variable can only be used as a measure of objectified cultural capital. In this paper, it was used as such a measure and as an independent variable that can explain traditional or media literacies.

[6] It should also be noted that the difference between the variable “up to 25 books” and the variable “26–50” is probably due to the fact there are fewer responses in the 26–50 range compared to other dummy variables used in the model. The proportion of respondents in each book category can influence the estimated coefficients and their statistical significance.

[7] There are several possible explanations for why the contribution to the overall variance is 6% but no individual variable contribution is statistically significant. First, it is probable that, as a group, the variables make a contribution, but individual effects are weak. Second, these variables might interact with other variables from outside of the block leading to a significant effect on the dependent variable. Finally, one should also consider the possible limitations regarding the sample size, although this is less probable than the other mentioned explanations.



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