THE NARRATIVE IMITATED UNION OF BELIEF AND EXPERIENCE (NIUBE) MODEL: EXPLORING THE INFLUENCE OF CULTIVATION EFFECT AND RETROSPECTIVE IMAGINATION INVOLVEMENT IN SHAPING MERITOCRATIC BELIEFS By He Xian A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Information and Media – Doctor of Philosophy 2024 ABSTRACT This study investigated the influence of Retrospective Imaginative Involvement on people's perceptions. Specifically, it examined how individuals' experiences with the Black Lives Matter and MeToo movements, combined with their consumption of media narratives from the sitcom 'Friends' and the Marvel Cinematic Universe, have shaped their beliefs about social stratification. Grounded in Self-Determination Theory, the research seeks to examine how individuals' life experiences influence their engagement with media narratives and subsequent perceptions of stratification systems. The study employed self-report measures to assess media consumption, RII engagement, and perceived meritocracy to delve deeper into the complex interplay of factors influencing individuals' perceptions. By examining the relationships between life experiences, media consumption, and RII engagement, this study provides insights into how individuals engage with media narratives differently based on their needs and experiences, and how these differences shape their understanding of stratification systems. This study contributes to the literature by 1) testing the expansion of RII scales’ applicability, 2) testing the Self- Determination Theory’s compatibility with the cultivation literature, and 3) proposing a new model regarding how individuals engage with media narratives based on their experiences to shape their understanding of stratification systems – The Narrative Imitated Union of Belief and Experience (NIUBE) Model. Copyright by HE XIAN 2024 TABLE OF CONTENTS CHAPTER 1: INTRODUCTION ................................................................................................... 1 CHAPTER 2: LITERATURE REVIEW: NARRATIVE, BELIEF, AND EXPERIENCE ........... 4 CHAPTER 3: OPERATIONALIZATION: MERITOCRACY, SOCIAL MOVEMENT, AND SHOW BUSINESS ....................................................................................................................... 15 CHAPTER 4: DATA AND METHOD ....................................................................................... 32 CHAPTER 5: RESULTS .............................................................................................................. 40 CHAPTER 6: DISCUSSION AND THEORETICAL IMPLICATION .................................... 107 BIBLIOGRAPHY ....................................................................................................................... 121 APPENDIX A: TABLES ............................................................................................................ 132 APPENDIX B: MERITOCRACY, MEDIA EXPOSURE, RII ITEMS (FRIENDS) ................ 172 APPENDIX C: MERITOCRACY, MEDIA EXPOSURE, RII ITEMS (MCU) ........................ 183 iv CHAPTER 1: INTRODUCTION Media plays a pivotal role in shaping the public's perception of the world, with meritocratic narratives being particularly prevalent in American news and documentaries. These narratives often convey system-justifying messages, subtly influencing public opinion (Appel, 2008; Stavrositu, 2014). Furthermore, entertainment media, including genres like comedies and adventure films, tend to promote morals centered on self-reliance and individual effort as key to success. These themes are often interwoven with class-centric undertones, suggesting a strong link between personal merit and social advancement (Freeman, 1992; Haggins, 1999; Marchetti, 2022). The influence of these meritocratic narratives extends beyond just immediate framing and priming effects. It aligns closely with the principles of cultivation theory, suggesting a deeper and more sustained impact on perception. Cultivation theory posits that frequent exposure to recurring themes in media leads to the formation of similar perceptions of social reality among viewers, particularly those who are heavy consumers of media content (Gerbner, Gross, Morgan, & Signorelli, 1994; Iyengar, 1990). Mediated information provides essential exposure for understanding different social classes (Bullock, Fraser Wyche, & Williams, 2001). Mediated information is crucial in shaping the understanding of different social classes. Research indicates that the way media portrays the poor and the affluent significantly influences viewers' attitudes toward these groups. This effect is especially pronounced in individuals who have limited real- life contact with people from different social strata (Giles, Reid, & Harwood, 2010; Roberts, 2002). Furthermore, within the cultivation literature, this is a branch that connects the narratives and experience – the resonate effect literature, which suggests that individuals are more likely to be influenced by media messages that confirm their experiences (Gerbner, Gross, Morgan, & 1 Signorielli, 1980). For example, people living in a crime-ridden area who watch lots of TV perceive crime to be even higher than people who watch the same level of TV but do not live in a crime-ridden area because the TV messages resonance with their reality (Shrum & Bischak, 2001). Where personal experiences are lacking or not immediately relevant, media portrayals can have a stronger impact on our perceptions and attitudes. Conversely, where personal experiences are intense or recent, they can either augment or diminish the media's influence, depending on how closely they align with media content (Schnauber & Meltzer, 2015). Retrospective imaginative involvement, referred to below as “RII,” may also be relevant to cultivation theory, as it is positioned to account for one of the psychological links between experience and narratives observed by the resonate effect literature. RII describes people's cognitive engagement with a story after it has ended and focuses on how people process narratives and think about them asynchronously (Ewoldsen, Busselle, Sethi, & Slater, 2021). RII, as coined by Ewoldsen et al. (2021), describes people's cognitive engagement with a story after it has ended and focuses on how people process narratives and think about them asynchronously (Ewoldsen et al., 2021). It is one of the key ways that people intrinsically motivate themselves to seek out and engage with narratives when their fundamental needs are jeopardized according to the Temporary Expanding the Boundaries of the Self (TEBOTS) model (Slater, Johnson, Cohen, Comello, & Ewoldsen, 2014). The role of life experience in RII is significant, as it may provide the raw material for reflection and imagination may provide the foundation that enables people to make connections between events and experiences (Siemens, 2005). As such, both RII and the resonating effect highlight the importance of a person's real- life experiences and beliefs in shaping how they interpret and are influenced by mediated narratives (Slater, 2007; Tamborini, Bowman, Eden, Grizzard, & Organ, 2010). 2 With this dissertation, I propose incorporating RII into the intersection between stratification beliefs and the cultivation literature to better understand how narratives influence perceptions of social stratification by examining the mechanism under the context of “Friends” and Marvel Cinematic Universe. I expect this research will advance the literature in the following ways. First, it expands the cultivation literature by incorporating and examining the role of TEBOTS and RII in the process. Second, it examines the RII scales’ reliability by expanding its applications to additional contexts. Finally, this research establishes the foundation for how experience, narrative, and belief are interconnected, which would be the inception of a new theoretical model – The Narrative Imitated Union of Belief and Experience (NIUBE) Model. 3 CHAPTER 2: LITERATURE REVIEW: NARRATIVE, BELIEF, AND EXPERIENCE The media plays a major role in shaping how people make sense of the world. For example, the cultivation theory explains how people’s perceived reality is influenced by systemic and constant mass media consumption, which proposes a plausible correlation between exposure to common message topics and perceptions of social reality. Understanding how we process and interpret narrative is key to grasping our perception of reality. For example, while watching a crime drama, we create a mental framework filled with characters, locations, and plotlines that influence how we perceive similar scenarios in real life. These models are not just static images but dynamic constructs that evolve with each episode or story, helping us make sense of complex narratives over time. Research suggests that these models are intricately linked to our real-world perceptions. By understanding these mental processes, we gain insight into the powerful role narrative plays in shaping our understanding of the world around us. 2.1 Cultivation Theory and Resonate Effect Studies have found that media's priming effect on how people understand inequality (Hauser & Norton, 2017), but when it comes to examining how media shapes people’s perception in the long term, the media effects literature draws heavily from the cultivation tradition. Repeated exposure to specific media content can lead to chronic accessibility (Ewoldsen & Rhodes, 2019; Roskos-Ewoldsen, Klinger, & Roskos-Ewoldsen, 2007), where certain ideas become more easily and frequently activated from memory, subsequently influencing judgments and behaviors more persistently. Coppini et al. (2018) discovered news consumption priming inequality-related content does not shape people’s perceived inequality adequately. However, inequality-themed content in entertainment programming is more vivid and close to people’s life experiences. Consistent with cultivation theory, these findings suggest that if media consumption is systemic 4 and constant, such exposure influences how people perceive reality. In particular, cultivation theory is based on the notion that viewers' opinions are influenced by the frequency with which they consume media. According to the Accessibility Principle, the information that immediately springs to mind first is the information that constitutes the narrow percentage of available information retrieved and therefore is the information most likely to be employed in forming a judgment (Carlston & Smith, 1996). Intense media exposure can make concepts more accessible than mild media exposure, and this accessibility, or ease of memory retrieval, affects people's views of how social reality works. (Ogles & Hoffner, 1987). Furthermore, the Heuristic/Sufficiency Principle, which suggests people tend to expend the least amount of resources necessary to process information, is concerned with what information is obtained throughout the judgment-making process. According to this premise, when humans make judgments, they generally do not search memory for all relevant information to the decision but instead recall just a limited portion of the available information (Wyer Jr & Srull, 2014). Further, people generally do not consider the source of the example they locate during judgment construction, either because they lack the desire to attend to source attributes or because they cannot recollect the source information (Petty & Cacioppo, 1986). Therefore, heavier viewers can access concepts presented in media more frequently than light viewers, especially if such notions are portrayed more extensively on television than in real life. A step further, Iyengar (1990) has also suggested that the frequency with which specific topics are covered in the media creates an accessibility bias. This accessibility bias, in turn, has been found to impact a variety of judgments, including problem salience, rating of politicians' performances, and voting habits. 5 There are studies on how media consumption shaped the process of how people make sense of the stratification system (Coppini et al., 2018; Erbring, Goldenberg, & Miller, 1980). In fact, research has indicated media’s relevance to certain aspects of how people make sense of the stratification system they live in – media is an effective way that people can confirm their experience with others. Public portrayals of the poor and the affluent can affect in-group and out-group attitudes by people from various social backgrounds (Bullock et al., 2001). Consistent with A. Young’s fieldwork (2006), Roberts (2002) found that people had to rely on media to build a portrait of members from other social groups due to their restricted contact with them. Exposure to mass-mediated information is essential for understanding members of different social classes (Giles et al., 2010). Nonetheless, media analyses on this subject have focused extensively on framing the lower class and associated enthusiasm for redistributive policies (Hackett, 2001; Hancock, 2004; Limbert & Bullock, 2009), whereas a few fairly recent studies have examined media’s effect on how overall stratification perception works (Coppini et al., 2018; Kendall, 2011). In television content in the United States, the upper class is portrayed the most often and favorably. The underdogs, on the other hand, are often neglected or depicted unfairly in entertainment material. According to Kendall’s (2011) study, entertainment media reinforces negative perceptions about low-income residents while promoting positive stereotypes of higher-income people. Popular American television shows like Grey's Anatomy and Law & Order portray poor people as drug users, abusive, and mentally ill. When accounting for the variance of perception shaped by the cultivation effect, Gerbner et al. (1980) coined two approaches to refine this theory: mainstreaming and resonating. The mainstreaming approach suggests disparate groups develop a common outlook of reality through exposure to the same content, even if those whose direct experience with the issue in media may 6 disagree dramatically with the media’s depiction. On the other hand, the resonate approach, which is relatively understudied, suggests those whose life experiences are more consistent with the media are also more likely to be influenced by the media message because the media’s depiction simply confirms their experience. Where personal experiences are lacking or not immediately relevant, narrative in media portrayals can have a stronger impact on our perceptions and attitudes. Conversely, where personal experiences are intense or recent, they can either augment or diminish the media's influence, depending on how closely they align with media content (Schnauber & Meltzer, 2015). Accompanying this connection between media consumption and life experience, numerous models have been proposed in the field of social cognition research to account for how humans receive, retain, and use social information. Despite its compelling implications for understanding the nuances of media influence, resonance has not been as thoroughly explored as mainstreaming (Calzo & Ward, 2009; Simmons, 2017). This gap may be due to the complexities of isolating and measuring resonance effects, which require detailed analyses of individual viewer experiences and environments (Liu et al., 2023). Mainstreaming presents a more straightforward narrative about the power of television to shape society's collective consciousness, making it an appealing subject for empirical investigation (Kothur & Pandey, 2023). Resonance offers critical insights into the differential effects of media on individuals and groups, highlighting the importance of personal experience in media influence. As media landscapes evolve and become increasingly personalized through digital platforms, understanding resonance could provide valuable perspectives on how media shapes perceptions among diverse audiences. Therefore, cultivating a more balanced research agenda that includes both mainstreaming and resonance could enrich our understanding of the complex relationship between media consumption and perception of reality. 7 2.2 TEBOTS & Retrospective Imaginative Involvement The Temporary Expanding the Boundaries of the Self (TEBOTS) may provide the theoretical foundation for one of the psychological links between experience and media narratives observed in the resonate effect literature (Slater et al., 2014). People frequently face threats to the self due to what is happening in their realities and defending the self from these challenges can be psychologically demanding. TEBOTS theorizes that when these fundamental needs are jeopardized, the self motivates a person to seek out and engage with narratives to transcend the self. The model suggests that the effort to define, regulate, and present oneself in daily life, along with the frustrations of fundamental human needs for agency, autonomy, and affiliation, create a psychological impetus for engagement with narratives. According to TEBOTS, narratives offer a unique opportunity for self-expansion, allowing individuals to experience life beyond the usual constraints of social roles, individual capabilities, time, and location (B. K. Johnson, Slater, Silver, & Ewoldsen, 2016). This process of temporarily expanding the self’s boundaries through narratives enables people to vicariously experience capabilities, relationships, and worlds different from their own. Essentially, narratives provide a psychological space where the self can be transcended and reimagined in ways that are not bound by the limitations of one's real-life circumstances. Furthermore, this ability to go beyond the self is termed boundary expansion and is believed to be a primary reason for engaging with narratives in TEBOTS. Interaction with a narrative offers a way to escape daily threats to the self—at the very least—and potentially allows for experiencing fundamental needs in novel ways. TEBOTS expands on the Self-Determination theory and emphasizes that people's actions are often limited by their realities and contends that when their needs are threatened, they turn to narratives as a means to temporarily satisfy these needs (Ewoldsen et al., 2021). 8 People’s life experience provides the foundation which reflection and imagination can be built upon, and this foundation is significant because it is how we make connections between events and experiences via RII (Siemens, 2005). Furthermore, people’s life experience is the foundation for their needs for relatedness, autonomy, and competence, and their ability to satisfy these needs is the justification of their positive self-perception according to the Self Determination Theory (Ryan & Deci, 2017). Life experiences significantly influence people's heuristic beliefs about reality. These experiences, by providing readily accessible information, enable individuals to process and interpret reality heuristically (Schwarz, 2013). For example, differences in exposure to diverse social situations or environments can lead to varied beliefs about societal fairness and stratification ties (A. A. Young, 2006). This highlights how personal and contextual life experiences shape an individual's heuristic understanding of the world and societal dynamics. As such, both RII and the resonating effect highlight the importance of a person's real-life experiences and beliefs in shaping how they interpret and are influenced by mediated narratives (Slater, 2007; Tamborini et al., 2010). This highlights its connection with resonate effect literature, which suggests that individuals are more likely to be influenced by media messages that confirm their experiences (Gerbner et al., 1980). RII describes people's cognitive engagement with a story after it has ended and focuses on how people process narratives and think about them asynchronously (Ewoldsen et al., 2021). RII operates as people's cognitive engagement with a story after it has ended by focusing on how people process narratives and think about them asynchronously (Ewoldsen et al., 2021; Green, Brock, & Kaufman, 2004). One of the theoretical foundations of RII is the Model of Narrative Comprehension and Engagement (Busselle & Bilandzic, 2008), which serves as a foundation for discerning how the initial 9 processing of a story can influence retrospective narrative engagement, the particular narrative aspects that audiences are most prone to dwell on, and other asynchronous entertainment experiences related to these narrative components. The model posits that people form three unique mental representations of a story: the character model, the situation (or story events) model, and the story world model. It suggests that during asynchronous narrative engagement, individuals are likely to reflect upon these narrative elements as well. However, such reflective thinking hinges on recalling specific narrative components from memory to be considered. Slater, Ewoldsen, and Woods (2018) created an 8-item RII scale primarily centered on narrative characters, their actions, relationships with other characters, and behavioral characteristics. Subsequently, a 27-item scale was developed to measure RII, encompassing narrative components such as characters, the fictional universe (the world where the story takes place), story events, and backstory (Ulusoy, Sethi, Baldwin, Grady, & Ewoldsen, 2022). Backstories RII engagement is particularly intriguing. Backstories play a crucial role in maintaining narrative coherence. They help in filling the gaps in a character's story, providing explanations for their behaviors and choices. These earlier events within the same narrative timeline are known as backstories. If expressly presented within the narrative, backstories are often revealed gradually or through flashbacks, providing context and depth to the characters and the overall plot, thereby enhancing the audience's understanding of the narrative and character motivations. Fanfiction authors commonly utilize backstories that are not expressively presented within the narrative to deepen the understanding of characters, their emotions, and motivations (Garcia, 2016). We often remember their most-liked characters and scenes, quote memorable lines of dialogue with “Friends”, and participate in various fan activities beyond their initial interaction with the story (Jenkins, 2012). Furthermore, backstories can be seen as a critical 10 component in understanding the synchronization of beliefs and experiences through media narratives. When individuals engage with a narrative, especially through RII, they often seek coherence and continuity. Backstories provide this by linking past events to present behaviors or future outcomes. This need for narrative coherence is particularly pronounced in media narratives that span multiple episodes or series. Audiences seek consistency and logical progression in character development and plotlines. Backstories serve as a bridge, connecting various narrative elements and ensuring a seamless flow of the story. They add depth and realism to the narrative, making it more engaging and believable. This exploration is vital not just for understanding media consumption patterns but also for insights into how narratives shape and are shaped by audience perceptions and experiences. The role of backstories in narrative engagement is a complex interplay of creativity, psychological needs, and media literacy. As such, it presents a rich area for academic inquiry, offering potential insights into the broader dynamics of media engagement and narrative processing. Moreover, studies on fanfiction and fan communities have shown that audiences frequently reflect on events both preceding and succeeding the core narrative (Sethi, Grady, Ulusoy, Baldwin, & Ewoldsen, 2022). Despite this, the exploration of backstories as a method of narrative engagement remains under-researched. In the context of narrative processing, it remains to be seen if regular media consumers (apart from those who write fanfiction) consider the backstory as a key element in their asynchronous interaction with narrative content. Enhancing a sense of autonomy, the decision to engage in RII, especially for purposes such as expanding a backstory, adding detail to the narrative, or creatively modifying the plotline through imaginative engagement, can be especially comforting for media users who experience feelings of powerlessness in their personal lives (Sethi et al., 2022). Given the importance of 11 backstories in narrative engagement and the role of RII in shaping these engagements, there is a clear need for more extensive research in this area. Current studies have primarily focused on fanfiction and specific fan communities, but the broader implications for general media consumers are yet to be fully explored. 2.3 Theoretical Model Building on the existing literature, this dissertation examines what role RII plays in the process of how people’s experiences and long-term media use shape their beliefs about the stratification system. Based on the literature, I expect the conceptual model would function as such: Figure 1 Conceptual Model In short, this model depicts a process that brings balance to one’s self via multiple cycles of heuristic and systematic processing1 of narratives and experiences until they reach reconciliation 1 When humans make judgments, they generally do not investigate memory for all relevant information to the decision but instead recall just a limited portion of the information accessible (Wyer Jr & Srull, 2014). The heuristic processing describes where people would not frequently consider the source of the example they locate during judgment construction, either because they lack the desire to attend to source attributes or because they cannot recollect the source information (Petty & Cacioppo, 12 to form a unified belief. This model suggests mental activities like RII are the drivers in this belief system (re)shaping process, as it is how they treat narrative intending to maintain coherency within themselves. The cultivation effect on people’s perception of reality can somewhat serve as the proxy for the pre-existing belief, as it can be indicative of aspects of reality that people would likely to believe in (Gerbner et al., 1994; Iyengar, 1990). When experience-caused inconsistencies appear, it creates a need to reformulate beliefs, which can take the form of engaging RII to do just that. RII engagement, by its nature, is not a one-time deal but a repeated cycle of psychological activities across time until it resolves the inconsistency. In this dissertation, I propose the Narrative Imitated Union of Belief and Experience (NIUBE) Model. This model can provide additional insights into the cultivation and resonating literature, as it sheds light on two routes that work to reshape people’s beliefs: the Outer Route depicts how media and life experiences shape people’s beliefs directly and heuristically, whereas the Inner Route accounts for the mental process underlying the outer route which involves more systematic processing. The Outer and Inner Routes of the NIUBE model relate to how narratives and experiences shape beliefs. The Outer Route represents heuristic processing, where narratives and experiences directly shape beliefs without deep cognitive engagement. Conversely, the Inner Route involves systematic processing, where belief formation is influenced indirectly through more profound psychological engagement, such as RII. This engagement plays a crucial role in belief formation, especially when individuals encounter experiences that contradict their existing beliefs. The activation of the Inner Route, through RII, leads to an 1986). Systematic processing, on the other hand, is adopted when it is critical to assess the credibility of the information and has been found to mitigate the impact of heuristics as people process systematically, they can be more likely to remember experiences beyond the first ones that appear in memory, to analyze the recovered information, and therefore to identify and dismiss information from untrustworthy sources than when they operate heuristically (Chaiken, Liberman, & Eagly, 1989). 13 examination and possible reconciliation of these contradictions, driven by a psychological need for coherence. Thus, while the Outer Route is constantly active, shaping beliefs through simpler processes, the Inner Route's activation is pivotal in the complex interplay of experience, narrative, and belief. This dissertation's exploration into the role of RII and the proposed NIUBE Model lays a foundational understanding of how personal experiences and media narratives interact to fortify and reshape individual belief systems. The NIUBE Model's bifurcated pathways – the Outer Route of direct influence from media and life experiences, and the Inner Route of mental reconciliation processes – offer a nuanced view of belief fortification and modification. As we transition to the next chapter, the focus will shift to designing a comprehensive research methodology aimed at empirically testing the NIUBE Model, which will seek not only to validate the theoretical constructs of the NIUBE Model but also to enrich our understanding of the dynamic interplay between media narratives, personal experiences, and the psychological need for belief coherence. The next Chapter shifts focus toward the practical application of these theories in particular contexts, aiming to empirically test the NIUBE Model by examining the influence of specific media narratives, such as the sitcom "Friends" and the Marvel Cinematic Universe (MCU), on perceptions of meritocracy in conjunction with recent social movements such as Black Lives Matter and Me too. These contexts would set the stage for a comprehensive analysis of how media content, intertwined with personal experiences and societal movements, contributes to the shaping and reshaping of individual belief systems. 14 CHAPTER 3: OPERATIONALIZATION: MERITOCRACY, SOCIAL MOVEMENT, AND SHOW BUSINESS As the first step to test the NIUBE model, this dissertation aims to crossectionally examine the influence of media consumption on perceptions of meritocracy, focusing on comedy and adventure genres represented by the sitcom “Friends” and the Marvel Cinematic Universe (MCU). It proposes refining RII backstory items to better fit the character from particular demographic groups. The study posits that viewers' experiences, such as exposure to racial or gender discrimination or movements like BLM or MeToo and their proxy measures in the form of social distancing, can challenge or reinforce their beliefs about meritocracy. The demographic background of viewers is expected to moderate this process, as compared to the dominant group, the subordinate group tends to engage in systematic processing via RII (i.e., activation of the Inner Routes) because this conflict poses a more direct challenge to their pre-existing belief system, as the dominant ideology was essentially forced-fed to them as a way to maintain the status-quo within the stratification system. 3.1 Perceived Meritocracy There are many stratification beliefs examined by scholars across different disciplines, but the debate over merit-based systems has intrigued social scientists for years. In contemporary society, the meritocratic narrative has been deeply embedded as a core value, particularly in Western cultures like that of the United States. This narrative posits that success and status are, or should be, the result of personal effort and innate ability. While Young (2017) initially viewed meritocracy negatively, it is now seen as desirable, even equivalent to the American Dream (de la Rosa & Lázaro, 2022; Ellis, 2017). Social stratification perception influences justice, fairness, social unrest, and support for policies addressing inequality (McCoy & Major, 15 2007; Whyte, 2010; Wu, 2009). Yet, despite all the research that sheds light on how meritocratic societies actually are, only a handful of studies have examined subjective evaluations of meritocracy, which I will call perceived meritocracy (see alsoDuru-Bellat & Tenret, 2012). I propose to examine an understudied issue: how to assess whether members of the public believe they live in a meritocratic society. Historically, researchers have defined and examined meritocracy differently. I define a meritocratic society as one where people get ahead because of their individual and honest efforts. Ideally, people’s family of origin, friends , ascribed characteristics, and willingness to circumvent rules should not be important for getting ahead. Detailed studies of perceived meritocracy are rare, but existing research consistently shows that Americans strongly believe they live in a meritocracy. For example, national surveys in 2009 and 2011 indicate that, on average, Americans think hard work and ambition are fundamental determinants of getting ahead (Economic Mobility Project, 2009, 2011). Furthermore, these beliefs have remained fairly stable over time. How much Americans vary in their perceptions of meritocracy is less clear. Barnes (2002) emphasized the uniformity of perceptions by showing that even respondents who lived in high-poverty areas believed that hard work and education were the most critical factors for getting ahead. Other studies, however, show that there can be substantial variation in perceptions even among people who share the same race, area, and social class (A. A. Young, 2006). Furthermore, overall perceptions of meritocracy can reflect differences in beliefs about meritocratic and non-meritocratic elements. While some Americans believe in the primacy of meritocratic elements (e.g. hard work), others believe more strongly in non-meritocratic elements (e.g., family wealth), some believe in both, and some do not believe strongly in either (Reynolds & Xian, 2014). 16 Research on stratification beliefs has examined several issues in-depth, including how people explain wealth and poverty (Matthew O. Hunt & Wilson, 2011). Another substantial body of research explores why people believe existing inequality is fair or how they think society ought to work (James R. Kluegel, Mason, & Wegener, 1995; Osberg & Smeeding, 2006). Finally, other studies examine how explanations of wealth and poverty vary across capitalist and post-communist countries in Europe (James R. Kluegel et al., 1995). While these studies cannot be used to make precise predictions about perceived meritocracy, they provide helpful theoretical tools for my work, including the theory of a dominant ideology (Huber & Form, 1973; James R. Kluegel & Smith, 1986). According to this theory, societies have a substantial agreement regarding how the stratification system works because the upper class can promote its views among other classes (James R Kluegel, Csepeli, Kolosi, Örkény, & Neményi, 1995). Most people in the U.S., for instance, see inequality as fair because they believe opportunities to get ahead are plentiful and social position is determined by individual factors (e.g., effort) rather than structural factors (e.g., coming from a rich family) (James R. Kluegel & Smith, 1986). This literature also provides the concept of a dual-consciousness. The dual-consciousness perspective suggests that although a dominant ideology strongly influences stratification beliefs, other beliefs can be layered on top of the dominant ideology. Which beliefs are added to the dominant ideology may reflect a person’s subgroup membership, the political and/or economic climate, and stratification-related experiences (M. O. Hunt, 2002, 2007; James R. Kluegel & Smith, 1986) . One of the goals of dissertation is to test the roles of the experience and media exposure to particular narrative in this dual-consciouness formation via RII. Motivated by the dual consciousness perspective, I conceptualize perceived meritocracy as a potentially complex collection of beliefs regarding what it takes to get ahead. A person’s 17 overall perception of meritocracy may reflect 1) a strong belief in the importance of both meritocratic and non-meritocratic factors, which is called the conflicted, 2) a strong belief in only one of those factors, which can either be the true believer in meritocracy or cynics or 3) a belief that neither is particularly important, which I called discouraged. When studying perceptions of how stratification systems actually work (as I do), authors often emphasize exposure. Hunt, for instance, explains racial/ethnic differences in beliefs about black/white inequality by writing, “among minorities, the accumulation of experiences of unfair treatment across the life course could render explanations of inequality more structuralist and less person-centered with increasing age” (2007: 396). Young also emphasizes exposure but notes that it is not always neatly aligned with race. He found that African American men from the same low social class and neighborhood had different beliefs about stratification, and explains that, “differences concerning their worldviews were based upon the degree to which these men were exposed to social institutions or individuals that provided them with vivid images of social power, authority, and social hierarchies across race and class lines” (A. A. Young, 2006: 116). Men who were isolated from the outside world believed more strongly in the importance of education and ability, but those who had more exposure to people outside their neighborhood placed more weight on non-meritocratic factors, including race and social ties (A. A. Young, 2006). Cech and Blair-Loy (2010) also emphasize exposure by arguing that women’s perceptions of gender inequality reflect their exposure to situations where men and women are treated unequally. Like Hunt and Young, they emphasize exposure and show that such exposure is not always neatly aligned with gender. As such, experiences play a pivotal role in the formation of an individual's worldview. Each encounter, interaction, and event people live through shapes their understanding and interpretation of the world. As people navigate life, these experiences 18 contribute to the set of beliefs, values, and attitudes we hold. They guide people’s perception of reality and influence their decision-making processes. These experiences don't just inform our worldview - they construct it, as well as reinforce it. An individual’s experience of inequality or stratification might resonate with certain messages or narratives they encounter in their societal milieu, in politics, or in the media. These resonating messages, in turn, might reinforce or modify their existing beliefs. There is absolutely no doubt these studies are in agreement regarding several meritocratic elements (e.g., effort and education). The more important these meritocratic elements are in a society, this society is considered more open and fairer. However, these scholars disagree regarding how to interpret the non-meritocratic element. This disagreement started the argument between Sanders (1997) and Breen and Goldthorpe (2001) regarding how to empirically identify what counts as a meritocratic ideal. Breen pushed for a total bell-shaped social mobility distribution chart. He assumes people’s individualistic attributes are generally distributed across the social classes, so the more people’s lifetime social mobility resembles the bell-shaped distribution, the stronger the indication of the presence of a meritocracy. Sanders pointed out that although Breen’s notion is correct, it should also account for the pre-existing effect of the social class, as smarter people might already be in the upper class, and so should their offspring. As such, the reproduction of the social class might not be in contradiction with meritocracy. As the literature develops, the field has somewhat given up on empirically proving a society as a meritocracy. Instead, the focus has been increasingly moved toward the subjective side. As the representative of these scholars, Duru-Ballet (Duru-Bellat & Tenret) relied on the importance of meritocratic elements for her definition. Nevertheless, Reynolds and Xian (Reynolds & Xian) tried twice to direct the literature in a more inclusive direction of the non-meritocratic element. 19 Regrettably, despite these efforts, the most recent trend led by Mijs (2021) has seen a reversion to earlier, less inclusive perspectives by focusing only on the meritocratic element. Overall, it is a consensus in the meritocracy literature that certain elements (i.e., effort and education) are at its core, whereas the interpretation and inclusion of non-meritocratic elements often took the center of the debate floor. Since studies have found that non- meritocratic factors such as class of origin (Breen & Müller, 2020), race (Saperstein & Gullickson, 2013), and gender (Grusky, 2019) do matter in terms of people’s achievement of upward social mobility at least in the U.S., this study takes the position that the examination of non-meritocratic elements should be included. Furthermore, as the U.S.-mediated narratives in general promote the meritocratic ideal (Gottdiener, 2020), own experience often challenges it. This conceptual inclusivity of non-meritocratic elements also sets an interesting point of examination of the intersection between the cultivation effect and RII, where we can examine whether and how people reconcile the contradictory experiences they encountered in real life with the ideology they are taught and grow up with. 3.2 Black Lives Matter and the Me Too Movement This seemingly equitable principle of meritocracy often masks systemic inequalities and biases, as it fails to account for the uneven playing field on which individuals start and continue their lives. This oversight has been starkly highlighted by the emergence and evolution of social movements like Black Lives Matter (BLM) and Me Too, which challenge the meritocratic narrative by exposing the systemic barriers faced by marginalized groups (Clair et al., 2019; Martin, 2018). The BLM movement is important because it pushes back against the notion that the U.S. is a fully functioning meritocracy (Taylor, 2016). While it doesn't deny that hard work and talent 20 can lead to success, it highlights that systemic racism (Silver, Goff, & Iceland, 2022) and inequality (Jones-Eversley, Adedoyin, Robinson, & Moore, 2017) can limit opportunities for Black individuals, making it harder for them to succeed compared to their white peers. The BLM movement has played a key role in bringing awareness to the systemic barriers that limit opportunities for Black people. The notion of meritocracy implies that people can succeed if they work hard enough, but this doesn't account for structural barriers that may prevent certain groups from having the same opportunities. BLM has amplified these issues, thereby challenging the simplistic view of meritocracy (M. Young, 2017). The Black Lives Matter movement, which gained momentum in response to the repeated instances of police brutality and systemic racism against African Americans, has significantly disrupted the meritocratic narrative (Martin, 2018). It brings to the forefront the harsh reality that for many Black individuals, societal structures and deeply ingrained biases hinder the actualization of meritocracy. Systemic racism, a complex and pervasive force, includes disparities in education, employment, housing, and the criminal justice system. These disparities starkly illustrate that for Black individuals, the same level of effort and talent often does not equate to the same level of success as it might for their white counterparts (Jones-Eversley et al., 2017). For instance, studies have consistently shown that African Americans face higher rates of unemployment and underemployment compared to whites, even when they possess similar, or even superior, qualifications (James, 2000; Nag, Arena Jr, & Jones, 2022). Moreover, the racial wealth gap, perpetuated by historical injustices and ongoing discrimination, further exacerbates these inequalities (Spinner-Halev, 2012). The BLM movement, by highlighting these issues, questions the fairness of a system that proclaims to reward merit when such rewards are often influenced by factors beyond an individual's control. 21 The Me Too movement also challenges the existing meritocratic structure by highlighting and challenging the systemic gender-based barriers to success. It has shed light on the stark gender disparities in various sectors (Borelli-Kjaer, Schack, & Nielsson, 2021; Lu et al., 2020), particularly corporate America, demonstrating that success in these fields has often been determined by more than merit alone. Originating as a response to widespread sexual harassment and assault, particularly in the workplace, Me Too has exposed how systemic gender biases and power imbalances obstruct a true merit-based system (Clair et al., 2019). The movement has revealed that women, regardless of their professional abilities or achievements, often face barriers to advancement and recognition due to gender discrimination and harassment. This reality is starkly visible in industries like technology and entertainment, where women have historically been underrepresented and, when present, frequently marginalized. The movement has brought to light numerous instances where women's career progression and opportunities were hindered not by a lack of talent or effort but by a hostile work environment and the actions of more powerful, typically male, counterparts (Schipani & Dworkin, 2019). Similar to BLM, this gender-based disparity is a clear indictment of the meritocratic narrative, as it illustrates that success is not solely the outcome of individual merit but is also significantly influenced by systemic gender dynamics. The impact of these movements on the collective consciousness has been profound. They have sparked a reevaluation of the notion of meritocracy, prompting individuals and institutions to reconsider how societal structures and biases impact the ability of marginalized groups to succeed (Clair et al., 2019; Kinderman, 2022; Martin, 2018). This reconsideration is crucial because the belief in a pure meritocracy can lead to a complacent acceptance of the status quo, under the assumption that those who do not succeed have simply not tried hard enough or are 22 lacking in ability. Such a view ignores the systemic barriers that can impede progress and unfairly penalize certain groups. By challenging this narrative, BLM and Me Too have opened up space for a more nuanced understanding of success and achievement, one that recognizes the role of systemic factors alongside individual effort and ability. Moreover, these movements have instigated broader societal changes. In the wake of BLM, there has been increased attention to policies that address racial inequalities, such as reforms in policing and criminal justice, affirmative action in education and employment, and initiatives aimed at closing the racial wealth gap. Similarly, Me Too has led to enhanced workplace policies against harassment, greater gender diversity in leadership positions, and a cultural shift that emphasizes the importance of respecting boundaries and consent. These changes reflect a growing acknowledgment that achieving a truly meritocratic society requires dismantling systemic barriers and ensuring that all individuals have a fair chance to succeed based on their merits. However, the challenge to the meritocratic narrative is not without its detractors. Some argue that these movements, by focusing on systemic barriers, undermine the value of personal responsibility and effort (Beckwith, 1999). They contend that emphasizing systemic inequalities can lead to a victim mentality, where individuals blame external factors for their lack of success rather than taking personal initiative (Carney, 2016). This perspective, however, fails to recognize that acknowledging systemic barriers is not about absolving individuals of responsibility but about creating a level playing field where personal effort and talent can truly shine. It's about recognizing that while personal responsibility is important, it operates within a broader societal context that can either facilitate or hinder individual success. As such, the BLM and Me Too movements represent a significant challenge to the traditional meritocratic narrative. By highlighting the systemic barriers faced by racial and 23 gender minorities, these movements have prompted a critical reevaluation of what constitutes merit and success. They argue for a more inclusive understanding of meritocracy, one that recognizes the role of systemic factors in shaping individual outcomes. This challenge is vital for building a more equitable and just society, where success is determined by genuine merit rather than by race, gender, or other extraneous factors. As these movements continue to evolve and influence public discourse, they hold the potential to reshape not only how society views success but also how it addresses the systemic inequalities that have long hindered true meritocratic achievement. 3.3 “Friends” and Marvel Cinematic Universe This popular sitcom “Friends” was running on the National Broadcasting Company’s (NBC) prime-time schedule for 236 episodes over 10 seasons from 1994 to 2004. “Friends” presents a version of New York City life that seems to align with the ideals of the American Dream – success and comfort achieved through seemingly minimal effort. The characters, despite their average jobs, afford spacious apartments in Manhattan, symbolizing a form of economic success that is highly aspirational (Sandell, 1998; Todd, 2011). The show's portrayal suggests that economic prosperity is easily attainable, reinforcing the notion of meritocracy, and representing the idea that success is solely the result of individual effort and talent. This depiction can cultivate a belief among viewers that economic success is within easy reach if one is charming, sociable, or lucky, downplaying the role of systemic issues or socio-economic barriers. The characters' career paths also reflect a sort of meritocratic ideal. They often achieve professional success despite apparent ineptitudes or minimal professional struggles, which aligns with the narrative of the American Dream - that anyone can succeed regardless of their background or challenges. 24 Marvel Cinematic Universe (MCU), is a multi-billion-dollar franchise and shared universe of superhero films and television series, based on characters from Marvel Comics. The MCU, a sprawling franchise of superhero films and television series, has also played a significant role in shaping societal beliefs, offering a more diverse and evolving narrative. Produced by Marvel Studios and distributed by various studios such as Paramount Pictures, Universal Pictures, and Walt Disney Studios Motion Pictures. It began with the release of "Iron Man" in 2008, which laid the groundwork for multiple ongoing phases. The MCU, while different in genre and tone from “Friends”, also impacts viewers' perceptions of meritocracy and the American Dream, albeit in more complex ways. Superhero narratives often emphasize individualism and exceptionalism, which is the core tenets of the American Dream. Characters like Tony Stark/Iron Man exemplify self-made success and innovation, resonating with the idea that personal ingenuity and effort lead to success. The MCU also presents characters from various socio-economic backgrounds, from the wealthy Tony Stark to the working-class Peter Parker/Spider-Man. This diversity can cultivate a belief in the possibility of success regardless of one's starting point, a key aspect of the American Dream narrative. However, it also juxtaposes different realities within the same universe, highlighting the complexities surrounding meritocracy and success. While initially reinforcing certain meritocratic ideals, the MCU also challenges them. Characters like Black Panther present a narrative that success and power can come from community and heritage, not just individual effort. This portrayal offers a more nuanced view of success, moving beyond the simplistic narrative of the self-made individual. “Friends” also subtly touches on many stratification-related issues such as race, class, and gender (Marshall, 2007). One of the critical areas where “Friends” has influenced societal beliefs is in its representation of race. The show's primary cast is predominantly white, and 25 minority characters are either underrepresented or portrayed through stereotypes (Marshall, 2007). This lack of diversity does not reflect the actual racial makeup of New York City, where the show is set. The underrepresentation of minority groups can lead viewers to subconsciously absorb the notion of a predominantly white society as the norm, overlooking the diversity that exists in real urban settings. Economically, “Friends” presents an idealized version of urban living. The characters, most of whom are in their 20s and 30s, live in spacious, well-furnished apartments in Manhattan, one of the most expensive cities in the world. This portrayal glosses over the financial struggles that most young adults in similar real-life situations face. The show's depiction of a carefree, financially stable lifestyle can cultivate an unrealistic expectation among viewers about the economic realities of urban living, potentially leading to a downplaying of the importance of economic class and struggles. “Friends” also reinforces traditional gender roles and societal beauty standards (Tiljander, 2008). The female characters are often seen in caregiving roles or as romantic interests, while the male characters frequently embody traits of hegemonic masculinity. Additionally, the show upholds conventional beauty standards, featuring characters who fit the societal ideal of attractiveness. This can cultivate harmful societal expectations around appearance and body image, impacting viewers' self-perceptions and expectations of others. For example, the primary cast of “Friends” is predominantly white, and minority characters are often underrepresented or portrayed through racial stereotypes (Cobb, 2018). By predominantly featuring white characters, the show perpetuates the notion of whiteness as the norm and sidelines diverse perspectives. Also, the characters in “Friends” live in spacious apartments in New York City, yet they rarely face economic hardships or job insecurities (Hicks, 2014). This is an unrealistic portrayal of their financial situation which downplays the importance of class struggles, presenting an idealized version of life in the city 26 that reinforces the status quo. Furthermore, the show also confirms traditional gender roles, highlighting how female characters are often relegated to the roles of caregivers or romantic partners. Additionally, the male characters are frequently shown adhering to hegemonic masculinity, which perpetuates stereotypes about men being emotionally closed off and dominant (Spangler, 2003). “Friends” upholds conventional beauty standards, featuring characters with slim, toned bodies. These unrealistic body images can contribute to harmful societal expectations around appearance and body shape (Gullage, 2014). MCU also subtly touches on many stratification-related issues. MCU has a history of sidelining female characters, often reducing them to secondary roles or love interests, resulting in a significant gender imbalance, with a majority of the films and series centered around male superheroes (Olufidipe & Echezabal, 2021). The MCU initially mirrored traditional gender roles prevalent in superhero genres, with a majority of its films and series centered around male protagonists, where female characters were often relegated to secondary roles or love interests. However, as the franchise has evolved, it has begun to address this imbalance, introducing more female protagonists and characters with significant agency (Gibson, 2023). This shift in narrative focus can cultivate a more balanced perception of gender roles in society, showcasing women in powerful, central roles. By centering the narrative around the fictional African nation of Wakanda, MCU also challenges the underrepresentation of black people in mainstream cinema and offers a powerful portrayal of African heritage and pride (Bucciferro, 2021). The MCU's portrayal of Black characters, particularly in films like "Black Panther," represents a significant departure from traditional mainstream cinema. The depiction of Wakanda, a fictional African nation, as a technologically advanced and culturally rich society, challenges the underrepresentation and stereotypical portrayal of Black people in media. This has the potential 27 to cultivate a more positive and nuanced perception of African heritage and Black people among viewers. The contrasting socio-economic backgrounds of characters like Tony Stark (Iron Man) and Peter Parker (Spider-Man) provide viewers with a diverse perspective on social class (Kohen, 2022). Stark, a billionaire with access to advanced technology, represents the upper echelons of society, while Parker, a high school student from Queens, embodies the everyday struggles of the working class. This contrast highlights the disparities and complexities of different social classes, potentially cultivating a more comprehensive understanding of socio- economic realities. As such, the operationalization of the NIUBE model in this study can be outlined as follows: Figure 2 Operationalization Model The operational model illustrates the dynamic interplay between media narratives, personal experiences, and the resultant beliefs about social structures, particularly meritocracy predicted by the NIUBE Model outlined in the previous Chapter. This nuanced model underscores the psychological quest for coherence as the driver behind the engagement with 28 media narratives and the integration of personal experiences. It highlights two distinct pathways through which beliefs are shaped: the direct heuristic impact of media and experiences, and the indirect systematic reconciliation occurring beneath the surface. In this model, the media exposure of “Friends” or MCU plays a significant role in shaping an individual's perceived level of meritocracy, predicting that prolonged engagement with these narratives can mold perceptions of stratification reality. Simultaneously, personal encounters with inequality, such as experience with BLM and Me Too, can also indicate one's beliefs about meritocracy. These represent the heuristic Outer Routes of the NIUBE model. At the heart of the model is the systematic process of RII, acting as a mediator interfaced with both the media narratives and personal stratification experiences. It serves as the psychological mechanism through which individuals assimilate or reinterpret information to maintain coherence within their belief systems. This reconciliation process is crucial, especially when individuals confront discrepancies between their existing beliefs and new experiences or information. The RII process can resolve these inconsistencies in two fundamental ways. One might involve retrofitting new information into existing beliefs, such as crafting a narrative that aligns with one's positive beliefs despite contradictory personal experiences. Alternatively, the process could involve a restructuring of the belief system itself to embrace new information, thus acknowledging the complexity and diversity of individual experiences over the simplistic categorizations derived from media characters or stereotypes. As the research journey progresses, this dissertation now pivots towards the empirical exploration of the NIUBE model. The next chapter serves as the bridge from the theoretical groundwork laid previously to the tangible examination of the model's predictions about the interplay of media narratives, personal experiences, and beliefs about socioeconomic structures. 29 The operational model, previously detailed, will be scrutinized through the lens of popular media entities such as the sitcom "Friends" and the MCU, paired with the personal lived experiences of inequality, as illustrated by movements like BLM and MeToo. 3.4 Goal and Expectations This dissertation is conceived as an exploratory study designed to empirically assess the validity of the NIUBE model. The primary objective is not to conclusively validate the model but to explore its theoretical foundations through empirical analysis. Both confirmation and refutation of the model's predicted pathways will be deemed valuable at this nascent stage, provided that the findings can be adequately explained and contextualized within the framework of the study. To this end, I have selected "Friends," a sitcom lauded for its portrayal of realistic interpersonal dynamics, and the MCU, a science fiction superhero franchise, as contrasting case studies. This deliberate choice aims to introduce variability in the data, enhancing our understanding of the NIUBE model's applicability across different media landscapes. Despite its exploratory nature, in the context of my operationalization model, I anticipate that the examination of Outer Routes will reveal their functionality across varied datasets. This expectation is grounded in their alignment with established theories within the realm of media effects literature. Outer Routes, as conceptualized in this research, represent the pathways through which media narratives influence audience perceptions and behaviors. The theory posits that these routes are not monolithic but vary in their effectiveness based on the nature of the content and the audience's predispositions. Moreover, I foresee the Inner Route, representing the activation of RII in scenarios where there is a palpable threat to individuals' self-concepts. This prediction is based on TEBOTS, which suggests that when individuals perceive a threat to their ego, they react in a way that seeks 30 to preserve psychological coherence. Such ego threats are especially salient in situations that challenge deeply held beliefs or values. According to TEBOTS, these reactions are more pronounced in contexts where individuals' identities are intertwined with the beliefs being challenged. In particular, I hypothesize that threats to the self will be more frequently observed among individuals belonging to lower socio-economic status groups. This is because exposure to media narratives that highlight non-meritocratic elements of society—those suggesting that success and status are not solely the result of hard work and talent—poses a direct challenge to their belief systems. Individuals in lower-status groups are likely to encounter cognitive dissonance when confronted with narratives that contradict the meritocratic ideology. This dissonance arises from the clash between the reality depicted in the media and their personal experiences of social mobility, or the lack thereof. The rationale behind this expectation is rooted in Dominant Ideology Theory, which argues that societal norms and beliefs—particularly the belief in meritocracy—are more fervently upheld by those in lower socio-economic positions. This theory posits that the dominant ideology serves to justify and perpetuate existing social arrangements, even when they disadvantage those who subscribe to them the most. Thus, when media narratives expose the fallacies of meritocracy, they are more likely to destabilize the belief systems of lower-status individuals, thereby triggering RII mechanisms as these individuals struggle to reconcile their lived experiences with the prevailing ideological narrative. 31 CHAPTER 4: DATA AND METHOD This phase of the study navigated through the empirical terrains of media influence, scrutinizing how the consumption of "Friends" and the Marvel Cinematic Universe (MCU) shaped individuals' perceptions of meritocracy. It delved into how personal experiences with social movements resonated or clashed with media narratives, thereby catalyzing the process of RII. This internal reconciliation was positioned at the crux of the inquiry, serving as the fulcrum for balancing dissonant cognitions with one’s belief system. The subsequent Chapter dissected the RII process, exploring how individuals reconciled the disjuncture between media portrayal and personal experiences, whether through the assimilation of new narratives into their belief ecosystem or the evolution of their belief structures to encapsulate a broader spectrum of societal realities. This empirical expedition employed data gathered from a diverse pool of respondents, offering a comprehensive analysis that extended beyond mere theoretical speculation. 4.1 Respondents In the intricate design of this study, a rigorous respondent selection process was implemented to ensure the inclusion of relevant respondents in terms of their familiarity with the narratives. This approach was pivotal for an in-depth understanding of the impact of prolonged media engagement and personal experiences on belief systems concerning meritocracy within a hierarchically structured society. Following the approval from the Institutional Review Board, a comprehensive survey was conducted. In particular, surveys and responses were stored on Qualtrics, where the respondents were recruited and paid through Mturk.com. When respondents were recruited by Mturk.com, they were directed to the Qualtrics survey via a link embedded in their Mturk Worker portal. In total, two surveys were employed during the data collection process, one for “Friends” and one for MCU. The surveys have the same structure, 32 only tailored differences in wording related to either “Friends” or MCU as exhibited in Appendices H and I. Both surveys first obtained respondents’ consent pursuant to Institutional Review Board requirements. A screening question, placed after the consent form, required respondents to confirm their viewership of the relevant content, as indicated by a poster of the show or movie. If they were screened out at this point by presenting they never consumed the narrative, they would not be paid at all and their respondent eligibility would be recycled into the Mturk Worker pool to allow others to complete the survey. The respondent who completed the survey were paid $0.75 for their time and effort if they passed Qualtrics’ bot checks. I have also manually reviewed responses with responses that lasted shorter than five (5) minutes and rejected incomplete responses. All rejected responses were recycled back to the Mturk Worker pool. In the end, a total of 679 respondents for the "Friends" analysis and 723 for MCU were gathered between late October and early November 2023. After this initial screening, the numbers were narrowed down to 451 for "Friends" and 463 for MCU, as people who were not familiar with the narratives were screened out. Ultimately, 327 valid responses for "Friends" and 334 for MCU were retained for in-depth analysis, as those are the respondents who provided valid responses to all items to be used in the analysis. As indicated partially by the Descriptive Statistics in Table 4 conducted after and with various scales were validated, the demographic composition of the respondents from both datasets was notably similar. This included comparable mean ages (MCU: 34.27, "Friends": 34.84), gender proportions (MCU: 0.51, "Friends": 0.52), and minority statuses (MCU: 0.19, "Friends": 0.16). Additionally, a slightly higher self-ranked social level was observed in the "Friends" dataset (MCU: 6.03, "Friends": 6.18), with political ideologies evenly matched across both datasets (MCU: 3.98, "Friends": 3.98). 33 4.2 Measures Media Exposure. Morgan, Shanahan, and Signorielli (2014) have long recognized how people consume media has become fundamentally different compared to the era in which the theory was coined by Gerbner. The current TV landscape offers an unprecedented variety of content. Streaming services, along with traditional cable and satellite TV, have broadened the range of available genres, themes, and formats. This abundance of choice has led to a fragmentation of viewership. People's preferences have become more niche, with audiences spread thinly across a wide array of programs. To compare and capture this trend in the 21st century, the cultivation effects are measured at two levels, one at the general TV consumption, and one at the particular narrative consumption. Consistent with prior content and genre-based cultivation research (Bilandzic & Busselle, 2008), exposure to particular content, as well as a general TV program, was measured by asking respondents a series of 5-point scale how frequently and days in the week of which they watch the contents and TV. The surveys gathered respondents’ reported frequency (1 = Never, 5 = Always) of their TV and specific narrative consumption for the following time of the day and week: first wake up in the morning, afternoon, early at night, late at night before going to bed, during the day on Saturday, Saturday nights, during the day on Sunday, and Sunday nights. Three sets of media exposure items were collected, the first one is on General TV Use which is available in both datasets. The second one is on “Friends” and the third one is on MCU which is only available in their respective datasets. These items are first validated by Confirmatory Factor Analysis and then utilized in the Structural Equation Models, as well as incorporated into scales by taking their means and utilized in OLS Regression Models. 34 Character Backstory RII. The items used to measure Character Backstory RII were essentially based on RII scales utilized by Ulusoy et al. (2022). To further test the reliability of RII backstory scales, I revised their existing items to specify the black, female, and wealthy characters in “Friends” and MCU, instead of having participants report their RII engagement on any character. In particular, the surveys asked the following questions about how often respondents would do to understand certain characters better: 1) imagine a backstory associated with that character(s); 2) imagine a backstory associated with the formation of challenging circumstances to that character; 3) imagine a backstory associated with the formation of relationships associated with that character; and 4) imagine a backstory associated with those motivations of the character. These items are first validated by Confirmatory Factor Analysis and then utilized in the Structural Equation Models, as well as incorporated into scales by taking their means and utilized in OLS Regression Models. Perceived Meritocracy. The perceived meritocracy-related constructs use items from Reynolds and Xian (2014) and Xian and Reynolds (2017), which consist of a series of questions regarding people’s belief in different elements’ importance to get ahead in society. In particular, respondents were asked to what extent (1 = Strongly Disagree, 5 = Strong Agree) they would agree with the following statements: 1) people who work hard enough will definitely get ahead in life; 2) people who have a good education will certainly be able to advance in their career; 3) Ambition indicates success in life; 4) those who come from wealthy families are guaranteed to get ahead in our society; 5) for people with well-educated parents, I expect they shall be successful in our society, 6) having political connections is sufficient to advance a person's standing in the social hierarchy in our society; 7)knowing the right people will definitely help a person to get ahead in life; 8) people will advance in our society as long as they cheat; 9) being 35 born as a man will automatically advance standings in the social hierarchy in our society; 10) people who are born white will easily get ahead in our society; and 11) being born as a heterosexual will automatically advance standings in the social hierarchy in our society. Consistent with the prior study, these items were divided into two constructs, one is the perceived importance of meritocratic elements consisting of statements 1) to 3), whereas the other is the perceived importance of non-meritocratic elements consisting of the remaining statements. This bifurcation is important, as the perceived importance of meritocratic elements is substantially equivariant to the notion of the American Dream, which is the dominant ideology in the United States and thus the default worldview shared by society as a whole (Huber & Form, 1973; James R. Kluegel & Smith, 1986). The perceived importance of non-meritocratic elements is the challenging ideology contrary to the dominant ideology, which is the basis of the dual consciousness (Matthew O. Hunt & Wilson, 2011). Therefore, examining how these two related but contradicting beliefs formed interdependently is important for this cross-sectional inquiry, as it provides the critical context and premises of the psychological threats TEBOTS discussed which would otherwise be obtained via a longitudinal study design. These items are first validated by Confirmatory Factor Analysis and then utilized in the Structural Equation Models, as well as incorporated into scales by taking their means and utilized in OLS Regression Models. Stratification Experience. The surveys also collected information on respondents’ stratification experience. They asked respondents to what extent (1 = No Experience at All, 5 = Extensive Experience ) they know someone who is 1) a Black Lives Matter Victim, 2) a Me Too Accuser, or 3) a business or political leader. Finally, to compensate for the potential inadequacy of internal validity on these stratification experience measures, the Bogardus Social Distance 36 Scale (Wark & Galliher, 2007) was introduced as the proxy to capture respondent’s attitudes and experience with BLM and Me Too victims, as well as the Upper Class. A score of 1 is assigned to each option, asking the respondents what the closest degree of intimacy is that they would be willing to admit a member of the group mentioned above. For each group, the following is asked: 1) would you be willing to marry a member of this group? (1.0); 2) would you be willing to have a member of this group as your close personal friend? (2.0); 3) would you be willing to have a member of this group as your neighbor? (3.0); 4) would you be willing to have a member of this group as your colleague at work? (4.0); 5) would you be willing to have a member of this group as a citizen of your country? (5.0); 6) would you be willing to have a member of this group visit your country as a non-citizen? (6.0); and 7) would you be willing to have a member of this group be excluded from associating with your country in any way? (7.0) Demographics. The surveys also asked respondents to provide their demographic information in terms of their age, gender identity, racial identity, self-assessed social level, and political orientation. Age was obtained as respondents' age at the time of the survey, which is the year 2023. The survey allows respondents to identify as male, female, as well as others. The social level question asked respondents to place themselves on a scale between 1 (bottom) to 10 (top) with the following question: “In our society, there are groups which tend to be towards the top and groups which tend to be towards the bottom on the socio-economic spectrum. Below is a scale that runs from top to bottom. Where would you put yourself now on this scale?” The political orientation measures also asked respondents to place themselves on a scale of 1 (liberal) to 7 (conservative). 37 4.3 Analytic Strategy The analytic process commenced with confirmatory factor analysis (CFA) to ascertain the reliability of scales previously employed in measuring perceived meritocracy, media exposure, and RII of character backstories. This phase specifically examined the adaptation of media exposure scales to particular contents and the application of RII scales in the context of "Friends" and MCU, focusing on black, female, and wealthy characters. The specific scale items used are detailed in Appendices H and I, along with the questionnaires. This stage was critical for validating the data and measurements before testing the NIUBE model via the structural equation model (Schumacker & Lomax, 2004). After CFAs confirmed the scales to be used in the study, the analysis then proceeded to compare the "Friends" and MCU respondent groups using t-tests. This comparison was centered on the constructed scales and other predictors that would be later incorporated into the analysis. To evaluate the NIUBE model's applicability preliminarily, nested ordinary least squares (OLS) regression was employed. This approach analyzed the perceived meritocracy scales within each dataset. The initial model integrated media exposure, experience measures, and demographic controls, focusing on the Outer Route of the NIUBE model. The subsequent nested model included RII measures, with any observed changes between models suggesting potential mediation effects and the existence of the Inner Route of the NIUBE model (Karlson, Holm, & Breen, 2012). This stage was fundamental in laying the groundwork for the subsequent Structural Equation Model analysis. Finally, a structural equation model was conducted for each dataset with the maximum likelihood estimation technique (Jöreskog & Sörbom, 1993) and, focusing on meritocratic and non-meritocratic factors concerning RII of character backstories with the same operational structure as indicated in Figure 2, with latent variables examined with 38 CFAs as discussed above. This approach essentially is the two-step modeling approach recommended by Anderson and Gerbing (1988), where the analysis is conducted with nested models where the measurement model is conducted first and the null. The study also examined the moderating effects of demographic backgrounds—race, gender, social class, and age—on the model. This section scrutinized the differential engagement among minorities and whites, females and others, and lower social classes compared to others, relevant to the RII Backstory for Black, Female, and Wealthy Characters, and their respective social distances. Age was included as an independent moderator, separate from the characters and social distances, to further authenticate the model. A multi-group SEM approach was utilized (C. Lee & Hallak, 2018; Matthews, 2017; Memon et al., 2019), comparing models with freely estimated path coefficients to those with coefficients constrained to be equal across groups, to evaluate the moderation effect. 39 CHAPTER 5: RESULTS Embarking on the analytical journey outlined in the previous chapters, this Chapter marks the commencement of a rigorous empirical validation and exploration of the NIUBE model. This is a crucial step in the verification of the scales previously established in the literature for measuring constructs like perceived meritocracy, media exposure, and the nuanced RII of character backstories. This step is not merely procedural but foundational, ensuring the integrity and reliability of the scales that will serve as the bedrock for all subsequent analyses within the realms of "Friends" and the MCU narratives. Upon validating the scales via CFA to be utilized throughout the analysis, this chapter proceeds with t-tests to discern any statistical differences in responses from the two distinct datasets, laying the groundwork for a deeper nested OLS regression. It is through these nested models that the intricate pathways of the NIUBE model begin to reveal themselves, with media exposure and experience measures initially painting the Outer Route, and the inclusion of RII measures possibly unveiling the mediating Inner Route. The subsequent SEM analysis represents a synthesis of the CFA and additional structured paths, culminating in a series of SEMs tailored for each dataset. This sophisticated analytical process endeavors to dissect the interrelations between perceived meritocracy and the RII backstories of characters diverse in race, gender, and wealth. Moreover, the SEM analysis probes the potential moderating influences of demographic backgrounds on narrative engagement levels, utilizing a multi-group SEM approach to ascertain the moderation effects. The chapter thus serves as a testament to the empirical rigor applied to the operationalization of the NIUBE model. It is not only a presentation of results but also a validation of the conceptual underpinnings that guide this dissertation's inquiry into the complex dance between media narratives, personal experiences, and the psychological undercurrents that 40 shape and reshape individuals' perceptions of meritocracy. With the foundations firmly established, the chapter pivots towards the nuanced results of the CFA, setting the stage for a nuanced discussion on the perceived meritocracy and the empirical substantiation of the NIUBE model's predictions. 5.1 Confirmatory Factor Analysis – Media Exposure CFA is a statistical technique used to verify the factor structure of a set of observed variables. Regarding measurements for endogenous variables, the first set of CFA was conducted particularly to validate the media exposure measure in the context of general TV consumption, as well as to the “Friends” and MCU contents with each of their respective datasets (Hurley et al., 1997). Table 1 reports the CFA findings on the three media exposure latent variables as follows. Table 1 presents the results of three different models concerning Media Exposure Scales related to television viewing habits: General TV Use, “Friends”, and the Marvel Cinematic Universe (MCU). In the General TV Use model with the combined dataset, the estimates range from 0.84 to 1.00, with watching first thing in the morning (T1) serving as the reference indicators for the factor. The error terms are relatively high, with the lowest being 0.78 and the highest being 1.59, indicating a considerable amount of variance not explained by the model. For the “Friends” model, the estimates are slightly lower, ranging from 0.86 to 1.01, but all are significant, with the lowest error term being 0.38 and the highest being 0.60. This model's lower error terms suggest that it has a tighter fit in capturing the variance in TV-watching habits related to the show “Friends”. The MCU model shows a similar pattern of estimates, ranging from 0.79 to 1.01, with significant error terms that are again lower than those in the General TV Use model, ranging from 0.42 to 0.61. This indicates a better model fit compared to the General TV Use model. The fit indices tell a more nuanced story about the models. For the General TV Use 41 Table 1 Confirmatory Factor Analysis on Media Exposure General TV Use 1 Error Friends 2 MCU 3 Estimate Error Estimate Error Estimate 1.00 0.97 *** 0.88 *** 0.84 *** Measurement Watch First Thing in the Morning (T1) Watch in the Afternoon (T2) Watch Early at Night (T3) Watch Before Bed (T4) Watch during Saturday Daytime (T5) Watch during Saturday Night (T6) Watch during Sunday Daytime (T7) Watch during Sunday Night (T8) N Alpha RMSEA CFI TLI Chi2(20) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 12 for the associated correlation matrix 2 SeeTable 13 for the associated correlation matrix 3 See Table 14 for the associated correlation matrix 1.00 *** 0.92 *** 1.00 *** 0.96 *** 661 0.94 0.16 0.92 0.89 349 1.59 *** 1.12 *** 0.80 *** 1.16 *** 0.85 *** 0.78 *** 0.87 *** 0.90 *** 1.00 0.91 *** 0.88 *** 0.86 *** 0.52 *** 0.52 *** 0.55 *** 0.60 *** 1.00 0.90 *** 0.79 *** 0.88 *** 0.61 *** 0.48 *** 0.51 *** 0.59 *** 0.38 *** 0.42 *** 0.39 *** 0.51 *** 0.99 *** 0.99 *** 0.99 *** 1.01 *** 327 0.96 0.11 0.97 0.96 105.3 0.42 *** 0.45 *** 0.54 *** 0.48 *** 0.91 *** 0.84 *** 1.01 *** 0.95 *** 334 0.95 0.11 0.96 0.95 106.2 42 model, the RMSEA is 0.16, which is above the commonly accepted threshold for a good fit (0.05-0.10). The CFI and TLI are also below the threshold that typically indicates a good fit (0.95 or above), with values of 0.92 and 0.89, respectively. The Chi-squared value is quite high at 348.96, suggesting that the model may not fit the data well. Conversely, the “Friends” and MCU models show better-fit indices. Both have RMSEAs of 0.11, which are closer to the acceptable range, and both have CFI and TLI values that are above 0.95, indicating a good fit for the data. The Chi-squared values are also lower at 105.29 for “Friends” and 106.15 for MCU, further suggesting a more satisfactory fit compared to the General TV Use model. Confirming Morgan et al. (2014)’s suggestion that people’s consumption of media has become fundamentally different compared to the era in which the theory was coined by Gerbner. This finding supports that specific viewing habits related to these series are more consistently patterned across the sample than general TV viewing habits. As people's preferences have become more niche, with audiences spread thinly across a wide array of programs, the collective viewing habits of the general TV audience have become more varied and less predictable. The proliferation of high-speed internet and the ubiquity of mobile devices have gave modern viewers unprecedented control over their viewing choices. They are no longer passive recipients of network programming but active selectors of content. This autonomy has led to selective exposure, where viewers choose content that aligns with their interests, ideologies, or moods. This new mode of consumption contrasts sharply with the episodic nature of traditional TV viewing. It can create concentrated periods of engagement with specific content, leading to intense but sporadic viewing patterns. This behavior is particularly evident with narrative-driven series, where the continuous storyline encourages prolonged viewing sessions. In essence, the transformation in revising the media exposure measurement to content-based reflects broader 43 changes in media consumption and technology, highlighting a move towards a more personalized, viewer-centric approach. 5.2 Measurement Model This dissertation moves to integrate it with all remaining latent constructs into a single measurement model is a comprehensive approach to evaluating the measurement qualities of these constructs (Anderson & Gerbing, 1988). This method facilitates an overall assessment of the measurement quality of the theoretical concepts considered in the study. By amalgamating various constructs into one model, researchers can more effectively gauge the accuracy and reliability of the measurements used to represent theoretical concepts. This integration is particularly crucial for assessing the construct validity of these concepts, and it ensures each construct not only stands on its own merit but also contributes cohesively to the overarching theoretical framework. This holistic approach is instrumental in reinforcing the credibility and scientific rigor of the study, providing a robust platform for analyzing and interpreting the theoretical constructs under investigation. In contrast to its analytic cousin, exploratory factor analysis, CFA explicitly tests previously tested hypotheses about relations between observed indicators and latent constructs. Table 2 reports the results of the measurement model for the “Friends” dataset and Table 3 represents the result for the MCU dataset. In both CFAs, only covariances between latent constructs are estimated, constituting a saturated latent variable model where all latent constructs are freely estimated. As such, any misfit would be presented in the measurement model, rendering CFA as a precursor to SEMs. In the context of SEM, the free correlation among latent constructs suggests an exploratory approach where the researcher has not imposed any theoretical constraints on how the constructs might be related. This can be advantageous for 44 uncovering unexpected relationships or for modeling complex systems where theoretical guidance is lacking. However, it can also mean that the model might not offer clear insights into causal relationships due to the lack of directional hypotheses. In a saturated model, every possible relationship between the constructs is estimated, which means that the model has as many estimated parameters as there are data points. This typically results in a perfect fit, as the model can account for all the covariances among observed variables. However, this also means the model is just as complex as the data itself, which can limit its generalizability and interpretive power. In other words, the interpretation for the subsequent structural models depends on whether the measurement model fits. Table 2 Confirmatory Factor Analysis - Friends Measurement Perceived Importance of Meritocratic Elements (Alpha: 0.75) Perceived Importance of Effort (M1) Perceived Importance of Education (M2) Perceived Importance of Ambition (M3) Perceived Importance of Non-Meritocratic Elements (Alpha: 0.78) Perceived Importance of Weathly Family (N1) Perceived Importance of Parents' Education (N2) Perceived Importance of Political Connection (N3) Perceived Importance of Knowing Right People (N4) Perceived Importance of Sex (N5) Perceived Importance of Race (N6) Perceived Importance of Sexual Orientation (N7) RII Character Backstory Black Character (Alpha: 0.95) General (B1) Challenging circumstances (B2) Crucial Relationship (B3) Motivation/Choices (B4) Female Character (Alpha: 0.94) General (F1) Challenging circumstances (F2) 45 Estimate Error 1.00 0.69 *** 0.75 *** 0.48 *** 0.47 *** 0.48 *** 1.00 0.79 *** 0.75 *** 1.03 *** 1.33 *** 1.42 *** 1.43 *** 0.65 *** 0.63 *** 0.66 *** 1.20 *** 0.54 *** 0.48 *** 0.44 *** 1.00 0.96 *** 1.02 *** 1.05 *** 0.63 *** 0.66 *** 0.54 *** 0.54 *** 1.00 1.03 *** 0.59 *** 0.51 *** Table 2 (cont’d) Crucial Relationship (F3) Motivation/Choices (F4) Wealthy Character (Alpha: 0.95) General (W1) Challenging circumstances (W2) Crucial Relationship (W3) Motivation/Choices (W4) Media Exposure to Content (Alpha: 0.96) T1 T2 T3 T4 T5 T6 T7 T8 N RMSEA Note: * p<0.05 ** p<0.01 *** p<0.001. CFI = 0.97, TLI = 0.97. Chi2 (390) = 621.561 See Table 13 for the associated correlation matrix 1.01 *** 1.00 *** 0.54 *** 0.54 *** 1.00 1.01 *** 1.02 *** 1.02 *** 0.55 *** 0.67 *** 0.48 *** 0.48 *** 0.50 *** 0.52 *** 0.54 *** 0.59 *** 0.39 *** 0.42 *** 0.40 *** 0.52 *** 1.00 0.96 *** 0.88 *** 0.86 *** 0.98 *** 0.99 *** 0.98 *** 1.00 *** 327 0.04 In Table 2, each indicator demonstrates a significant loading on its corresponding latent construct, affirming the items as reliable indicators. The meritocratic factors—effort, education, ambition—alongside the non-meritocratic elements like family wealth, parental education, political connections, and societal variables such as sex, race, and sexual orientation, all show substantial loadings. Similarly, character backstory elements (pertaining to Black, Female, and Wealthy characters) are well-represented by attributes like general disposition, challenging circumstances, crucial relationships, and motivations or choices. This level of significance across factor loadings indicates a robust measurement model, setting a sound foundation for interpreting the constructs in the structural model. The CFA exhibits excellent fit as indicated by an RMSEA of 0.04, which is below the threshold of 0.05 for a good fit. The CFI and TLI values are both at 46 0.97, surpassing the conventional cut-off point of 0.95, suggesting that the high potential that observed data would align very well with the structure the NIUBE model predicted. These fit indices are crucial as they bolster the validity of the measurement model, enabling it to serve as a reliable basis for subsequent SEMs. A good fit is essential because it ensures that the structural relationships tested in the SEM are based on well-defined and empirically supported constructs, thereby increasing the likelihood of generating meaningful and accurate insights into the relationships among the variables of interest. Similar results were replicated by the MCU dataset as indicated by Table 3 as follows: Table 3 Confirmatory Factor Analysis - MCU Measurement Perceived Importance of Meritocratic Elements (Alpha: 0.71) M1 M2 M3 Perceived Importance of Non-Meritocratic Elements (Alpha: 0.79) N1 N2 N3 N4 N5 N6 N7 RII Character Backstory Black Character (Alpha: 0.94) B1 B2 B3 B4 Female Character (Alpha: 0.94) F1 F2 F3 F4 47 Estimate Error 1.00 0.77 *** 0.80 *** 0.51 *** 0.49 *** 0.52 *** 1.00 0.71 *** 0.80 *** 1.20 *** 1.41 *** 1.53 *** 1.62 *** 0.72 *** 0.64 *** 0.67 *** 1.12 *** 0.60 *** 0.45 *** 0.50 *** 1.00 1.05 *** 1.02 *** 1.01 *** 0.61 *** 0.53 *** 0.38 *** 0.45 *** 1.00 1.02 *** 1.02 *** 1.03 *** 0.60 *** 0.64 *** 0.38 *** 0.45 *** Table 3 (cont’d) Wealthy Character(Alpha: 0.94) W1 W2 W3 W4 Media Exposure to Content (Alpha: 0.95) T1 T2 T3 T4 T5 T6 T7 T8 N RMSEA Note: * p<0.05 ** p<0.01 *** p<0.001. CFI = 0.96, TLI = 0.95. Chi2 (309) = 741.595 See Table 14 for the associated correlation matrix 1.00 0.98 *** 0.96 *** 0.96 *** 0.55 *** 0.62 *** 0.56 *** 0.57 *** 0.58 *** 0.48 *** 0.51 *** 0.60 *** 0.41 *** 0.46 *** 0.54 *** 0.49 *** 1.00 1.05 *** 0.78 *** 0.87 *** 0.91 *** 0.83 *** 1.00 *** 0.94 *** 334 0.05 The CFA for the MCU data also shows that all factor loadings are significant at the p<0.001 level, indicating strong evidence that each item is a good indicator of its respective construct. Specifically, the factor loadings for the Perceived Importance of Meritocratic Elements (M1, M2, M3) range from 0.77 to 1.00, which suggests these items are perceived as important to a degree, with M1 as the reference indicator. For the Non-Meritocratic Elements (N1 through N7), the loadings range from 0.71 to 1.62, with some factors like race (N6) and sexual orientation (N7) receiving higher importance ratings. The Character Backstory factors for Black, Female, and Wealthy characters (B1-B4, F1-F4, W1-W4) all have loadings above 0.95, indicating that the respondents see all these elements as relevant to the characters' narratives. The Media Exposure to Content construct over time points T1 to T8 also shows strong and consistent factor loadings, suggesting a stable construct over time. The model fit indices indicate a good 48 but not perfect fit, with RMSEA at the upper threshold of acceptability (0.05), and CFI and TLI slightly below the ideal threshold (0.96 and 0.95, respectively). These values suggest that the model fits the data reasonably well, which sets the stage for the subsequent SEM analysis. These CFA across two datasets robustly validate the latent constructs under study, which encompass perceptions of meritocratic elements, non-meritocratic elements, RII character backstories, and media exposure to content. The significant and consistent factor loadings affirm that the individual items within each construct are reliable indicators, accurately reflecting the constructs they are meant to measure. This level of validation is critical for advancing from abstract theoretical concepts to practical, quantifiable scales. Consequently, these well-defined scales can now be confidently employed in OLS regression analyses, serving as either dependent or independent variables. Their proven reliability and validity through CFA enhance their utility in empirical research, providing a solid basis for further exploration of related hypotheses. Furthermore, these findings are particularly consequential. The validated measurement models offer a strong foundation upon which complex causal pathways can be constructed and tested. The acceptable fit indices from the CFAs, which suggest that the models adequately capture the data's underlying structure, give the green light to proceed with SEM without the added concern of measurement inaccuracies. This paves the way for investigating intricate relationships within the data, advancing both the practical and theoretical understanding of the constructs. Notably, these constructs now stand as refined tools for disentangling the nuanced interplay between individual attributes and societal perceptions, contributing valuable insights into the ongoing discourse on social stratification, character portrayal, and media influence. 49 5.3 Descriptive Statistics and T-Test As the measurement model validated scale items used in the previous study, most of the latent variables above were constructed as the mean of the relevant factors, except perceived meritocracy. I repeated Reynolds and Xian (2014)’s perceived meritocracy scale construction. Namely, assessing the perceived importance of meritocratic and meritocratic elements involves summing up the relevant variable scores and expressing them with a maximum of 100. To determine the overall belief in meritocracy, the score for the perceived importance of non- meritocratic elements is subtracted from the meritocratic element. This results in a scale ranging from -100 to +100, where -100 signifies a belief in only non-meritocratic factors for success, and +100 indicates a belief in solely meritocratic factors. A zero score suggests equal importance of both factors or a view that neither type of factor is important for success. This approach mirrors Robinson (2009) method of exploring people's views on the causes of poverty, whether due to individual or structural factors or a combination. This overall metric is valuable as it offers a consolidated view of the extent to which people perceive the United States as a meritocratic society. A t-test was performed for each variable and scale, comparing responses from the “Friends” and MCU datasets to highlight any differences, as indicated by Table 4. As indicated above, the perceived social distance from Black individuals, females, and the upper class is measured through self-reported scores where a lower score indicates a closer perceived social distance and a higher score signifies a greater sense of remoteness. Additionally, the table assesses personal experiences with victims of significant social movements such as the Black Lives Matter (BLM) and Me Too movements, as well as interactions with the upper class. The scores again follow a similar pattern, with lower scores indicating no experience and higher scores indicating personal experience with members of these groups. The "Controls" section 43 includes demographic and sociopolitical variables that could influence the primary measures of the study. Age is presented as an actual value in the year 2023. Gender is a binary variable, with females coded as 1. Minority status is also binary, categorizing respondents as either a minority (1) or White (0). Social Level is a self-assessment of social class on a scale from 1 to 10, and Conservative is a self-ranked political ideology scale ranging from 1 (liberal) to 7 (conservative). The mean score for overall meritocracy in the MCU dataset is lower (3.03) compared to the “Friends” dataset (4.47), suggesting that respondents associated with the “Friends” dataset perceive a higher level of meritocracy. When looking at the importance of meritocratic elements, both datasets score similarly high (MCU: 69.66, “Friends”: 69.83, indicating a general belief in merit-based success. For non-meritocratic elements, the means are also quite close (MCU: 66.64, “Friends”: 65.36), with slightly higher importance placed on these elements in the MCU dataset. The mean scores for general TV content consumption (MCU: 4.58, “Friends”: 4.58) and specific content related to “Friends” or MCU (MCU: 3.06, “Friends”: 3.05) are almost identical, suggesting a similar level of engagement with television content among respondents of both datasets. This may also be reflective of the data collection timing, as it occurs immediately after the passing of one of the main cast in “Friends”, Matthew Perry. This could have led to a peak consumption of the series, at least amongst the respondents here. The mean score for overall meritocracy in the MCU dataset is lower (3.03) compared to the “Friends” dataset (4.47), suggesting that respondents associated with the “Friends” dataset perceive a higher level of meritocracy. When looking at the importance of meritocratic elements, both datasets score similarly high (MCU: 69.66, “Friends”: 69.83, indicating a general belief in merit-based success. For non-meritocratic elements, the means are also quite close (MCU: 66.64, “Friends”: 65.36), with slightly higher importance placed on these elements in the MCU dataset. The mean scores 44 for general TV content consumption (MCU: 4.58, “Friends”: 4.58) and specific content related to “Friends” or MCU (MCU: 3.06, “Friends”: 3.05) are almost identical, suggesting a similar level of engagement with television content among respondents of both datasets. This may also be reflective of the data collection timing, as it occurs immediately after the passing of one of the main cast in “Friends”, Matthew Perry. This could have led to a peak consumption of the series, at least amongst the respondents here. The "RII Scale" shows some differences in character backstories with mean scores indicating that the “Friends” dataset tends to have lower scores for black character backstories (MCU: 4.57, “Friends”: 4.29) but slightly higher scores for females (MCU: 4.64, “Friends”: 4.47) and wealthy character backstories (MCU: 4.38, “Friends”: 4.28). The t-values and p-values indicate whether there are statistically significant differences between the two datasets for each variable. A p-value below 0.05 typically indicates a statistically significant difference. In this table, most variables do not show significant differences, except for the "Black Character Backstory" under the RII Scale. Significant differences are noted especially in the backstory for black characters, with a lower mean in the “Friends” dataset and a statistically significant t-test result (p = 0.02). This could have resulted from the systematic overlooking of blacks in “Friends”, as well as MCU’s racial emphasis in the reason years, which in concert made MCU’s black character more salient. In "Stratification experience," respondents from both datasets report moderate social distances from Black individuals (MCU: 3.08, “Friends”: 3.21), females (MCU: 3.19, “Friends”: 3.34), and the upper class (MCU: 3.61, “Friends”: 3.83), with the “Friends” dataset showing a slightly higher perceived social distance in all three categories. Experiences with BLM victims (MCU: 3.53, “Friends”: 3.50), Me too victims (MCU: 3.66, “Friends”: 3.68), and the upper class (MCU: 3.35, “Friends”: 3.47) are also 45 reported to be similar across both datasets, indicating a comparable level of personal experience with these groups. 46 Table 4 T-Test of Common Variable across Friends and MCU dataset, Descriptive Statistics Variables Perception Overall Meritocracy Perceived Importance of Meritocratic Elements Perceived Importance of Non- Meritocratic Elements Media Exposure General TV Content RII Scale Black Character Backstory Female Character Backstory Wealthy Character Backstory Stratification Experience Social Distance from Black Social Distance from Female Social Distance from Upper Class 3.61 Experience with BLM Victim 3.53 Experience with Me too Victim 3.66 Mean (MCU) Mean (Friend) t p Description 3.03 4.47 0.92 0.36 Subtract Perceived importance of Non- meritocratic element from Perceived importance of meritocratic elements 69.66 69.83 0.11 0.91 Average of M1 through M3 multiplied by 100 66.64 65.36 -1.00 0.32 Average of N1 through N7 multiplied by 100 4.58 3.06 4.57 4.64 4.38 3.08 3.19 4.58 3.05 4.29 4.47 4.28 3.21 3.34 3.83 3.50 3.68 0.07 0.94 Average of T1 through T8 on General TV Use -0.14 0.89 Average of T1 through T8 on Friends or MCU -2.28 0.02 Average of B1 through B4 -1.44 0.15 Average of F1 through F4 -0.72 0.47 Average of W1 through W4 0.99 0.32 closest self reported social distance = 1, most remote self reported social distance = 7 1.05 0.29 closest self reported social distance = 1, most remote self reported social distance = 7 1.61 0.11 closest self reported social distance = 1, most remote self reported social distance = 7 -0.35 0.73 No experience with this group = 1, Experience with this group = 5 0.21 0.83 No experience with this group = 1, Experience with this group = 5 53 Table 4 (cont’d) Experience with Upper Class 3.35 3.47 1.33 0.18 No experience with this group = 1, Experience with this group = 5 Controls Age Female Minority Social Level Conservative 34.27 0.51 0.19 6.03 3.98 34.84 0.52 0.16 6.18 3.98 0.77 0.44 Age in 2023 0.44 0.66 Female = 1, other = 0 -1.31 0.19 Minority (Black, Latino, Asian, etc.) = 1, White = 0 0.91 0.36 Self-ranked social class. Bottom = 1, top = 10 0.04 0.97 Self-ranked political ideology. Liberal = 1 , conservative = 7 N 334 327 54 Although there were no major and apparent differences across the “Friends” and MCU datasets, there could be notable differences between their audience bases. Fans of "Friends" generally appreciate the sitcom genre's comfort, humor, and the relatable, albeit idealized, portrayal of life's milestones. This interest extends to a broader appreciation for narrative simplicity and character consistency, where the primary draw is the characters' relationships and growth. MCU fans are typically drawn to the action-adventure and fantasy genres, appreciating the complex storytelling, world-building, and visual spectacle. The interconnected stories across movies and TV series require a deeper engagement with the narrative universe, appealing to those who enjoy piecing together information and predicting future developments. "Friends" viewers often engage with the show in a comfort-viewing capacity, where episodes are watched and re-watched without necessitating sequential order. This kind of viewing is facilitated by the show's availability on streaming platforms, allowing audiences to dip in and out of seasons at their leisure. The sitcom format lends itself to casual viewing, making it a popular choice for background noise or a familiar companion during downtime. MCU content consumption, conversely, is characterized by a more scheduled and anticipatory approach. Fans often prepare for new releases by watching previous films and series in a particular order to understand the continuity and evolving storyline. This behavior underscores a more active and engaged form of media consumption, where understanding the broader narrative context enhances the viewing experience. With the aforementioned variables, the inquiry moved on to a series of OLS regressions on the three outcome variables measuring perceived meritocracy. The models in Table 5.1 examine perceptions of meritocracy in the “Friends” dataset, and the models in Table 5.2 examine perceptions of meritocracy in the MCU data. The regressions for each dataset are 55 interrelated. The dependent variable in the first set of models (i.e., Model 1 and 2) for each dataset is the difference between respondents’ scores on the scales of meritocratic and non- meritocratic elements, which are the dependent variables in the other two sets of regressions (i.e., Model 3 and 4 as one set, whereas Model 5 and 6 as another set). Because the three sets of models use the same sample, the coefficients in the initial set of models for each dataset can be reproduced by subtracting the coefficients in the third set of models from the second set of models. Furthermore, the statistical tests in the initial set of models are equivalent to testing whether the coefficients in the other two sets of models for that dataset are different from each other. By constructing the models in this fashion, the analysis reveals why each variable in the initial model has the observed effect. For a full discussion of this methodology, see Edwards (1995). 5.4 Nested OLS Regressions Nested regression models are a sequence of regression models in which each successive model includes all of the predictors of the previous model plus additional predictors (Karlson et al., 2012). This approach is used to assess the impact of adding new predictors to the model – whether they provide significant additional explanatory power and how they influence the effects and significance of predictors already in the model. For instance, by comparing the R-squared values across nested models, how much additional variance in the dependent variable is explained by adding new predictors can be assessed. An increase in R-squared suggests that the new variables offer incremental explanatory power. If coefficients remain relatively stable across models, it suggests that the relationships are robust to the inclusion of other variables, whereas conversely, large changes might indicate that those relationships are conditional on other factors (Kohler, Karlson, & Holm, 2011). If the addition of new predictors significantly 56 changes the coefficients of variables already in the model or a variable that is significant in one model may become non-significant after adding new variables in a nested model, this may indicate that the new variables are accounting for some of the effects previously attributed to the other variables, indicating potential for the existence of mediation effect. In this analysis, Models 1, 3, and 5 are the baseline models testing the Outer Route of the NIUBE Model, whereas Models 2, 4, and 6 are the nested models that added only RII variables to the regression equations to explore the potential mediation effect as indicated by the Inner Route of NIUBE Model. Table 5.1 are set of the nested OLS regression on perceived meritocracy scales conducted with the “Friends” dataset, as described above. The F-test is used to compare each restricted model (Models 1, 3, and 5) with its corresponding unrestricted model (Models 2, 4, and 6, respectively). Model 1 vs. Model 2 (Overall Perceived Meritocracy) and Model 3 vs. Model 4 (Perceived Importance of Meritocratic Elements) both reported an F statistic of 0.05. This would suggest that the additional parameters in Models 2 and 4 do not significantly improve the fit of the model compared to Models 1 and 3. However, Model 5 vs. Model 6 (Perceived Importance of Non-Meritocratic Elements) reported an F statistic is 4.46, and it is significant at the p<0.001 level. This means that the additional RII measures in Model 6 provide a significantly better fit to the data than Model 5, according to the F-test. Certain predictors exhibit significant associations across different facets of meritocracy, where findings in Models 1, 3, and 5 generally confirm the literature’s expectation that media exposure and experience are relevant to belief formation. In Model 1, media exposure to “Friends” (4.63, p < 0.01) was found with a statistically significant positive relationship with the overall meritocracy, indicating that exposure to the show “Friends” is associated with a higher 57 belief in meritocracy. Respondents reported a statistically significant negative relationship on the association between overall meritocracy and Social Distance from the Upper Class (-1.45, p < 0.05), suggesting that more social distance from the upper class is associated with a lower belief in meritocracy. In Model 3, media exposure to “Friends” (6.58, p < 0.001) was also found with a statistically highly significant positive relationship, indicating that watching “Friends” strongly correlates with the belief that meritocratic elements are important for success. Moreover, there is a statistically significant positive relationship between the perceived importance of meritocratic factors and Experience with the Upper Class (2.83, p < 0.05), meaning that experiences with the upper class are associated with a greater emphasis on the importance of merit-based success. Respondents with higher social levels also report a higher score in their belief in the meritocratic elements (1.06, p<0.05)。 Finally in Model 5, the result indicates that greater social distance from females is associated with less perceived importance of non-meritocratic elements in success (-1.20, p < 0.05). Furthermore, it also suggests experiences with BLM victims (1.80, p < 0.05). and Me Too Victim (3.95, p < 0.001) are associated with greater recognition of the importance of non-meritocratic elements in success. The inquiry of the Inner Route within the NIUBE model is focused on the change between models. As the result indicated, media exposure to “Friends” has a positive coefficient (4.63 in Model 1 and 4.44 in Model 2), both statistically significant, suggesting that watching “Friends” is associated with a higher perception of meritocracy. The slight decrease in the coefficient with the addition of more variables might suggest that other variables in Model 2 account for some of this effect. Social Distance from the Upper Class shows a negative association with perceived meritocracy, which remains stable across Models 1 and 2, indicating a robust relationship. However, the R-squared values do not change (both 0.09), indicating that 58 Table 5.1 Nested OLS Regression on Meritocracy Scales on Friends Media Exposure General TV Friends Stratification Experience Social Distance from Black Social Distance from Female Social Distance from Upper Class Experience with BLM Victim Experience with Me too Victim Experience with Upper Class Demographics Age Female Minority Social Level Convervative RII Scale Black Character Backstory Female Character Backstory Wealthy Character Backstory intercept N F (3, 310) Overall Perceived Meritocracy Perceived Importance of Meritocratic Elements Model 1 Model 2 Model 3 Model 4 Perceived Importance of Non- Meritocratic Elements Model 6 Model 5 -1.80 4.63 ** -1.82 4.44 * -1.08 6.58 *** -1.32 4.27 * 0.73 1.95 0.49 -0.17 0.58 1.30 -1.45 * -0.29 -2.04 0.91 0.22 0.42 0.55 0.73 -0.93 -5.33 327 0.56 1.36 0.52 0.10 -1.48 * -0.39 -2.05 0.87 0.22 0.32 0.48 0.74 -0.94 0.40 0.16 -0.28 -5.45 327 0.05 -0.67 1.51 1.91 2.83 * 0.09 2.34 1.88 1.06 * -0.39 23.47 *** 327 59 0.32 0.27 -0.60 1.14 2.12 2.35 0.09 2.26 1.27 1.03 * -0.28 -0.91 0.75 2.85 * 21.95 *** 327 0.05 -0.06 -1.20 * -0.24 -1.09 * 0.78 1.80 * 3.95 *** 1.93 0.88 1.54 4.17 *** 1.48 -0.13 1.91 1.33 0.33 0.54 28.80 *** 327 -0.13 1.94 0.79 0.28 0.66 -1.31 0.59 3.13 ** 27.40 *** 327 4.46 *** Table 5.1 (cont’d) R2 Note: * p<0.05 ** p<0.01 *** p<0.001. 0.09 0.09 0.34 0.35 0.34 0.37 60 the additional variables in Model 2 do not explain more variance in perceived meritocracy than the variables in Model 1. The potential mediation path from media exposure and experience through RII as predicted by the NIUBE model doesn’t seem to be supported here. However, the subsequent models would indicate otherwise as discussed below. Regarding the set examining the Perceived Importance of Meritocratic Elements (Models 3 and 4), the R-squared values showed a slight increase from 0.34 to 0.35, showing that the new RII variables added in these models contribute more to explaining the perceived importance of meritocratic elements. Between Models 3 and 4, there are two key changes to note. First, in Model 3, media exposure to '“Friends” has a significant and strong positive coefficient (6.58), indicating a substantial association with the perceived importance of meritocratic elements. However, in Model 4, this coefficient decreases to 4.27 but remains significant. This decrease, while it maintains its significance and direction, suggests that when additional RII Scale variables are included, the effect of 'media exposure to “Friends” is somewhat diminished. This reduction could imply that the newly added variables in Model 4 may be capturing some of the variation in perceived meritocracy that was initially attributed to media exposure to '“Friends” . It may also suggest the presence of a mediator—possibly one of the newly added variables—that explains part of the pathway between media exposure to '“Friends” and the perceived importance of meritocratic elements. Second, when moving from Model 3 to Model 4, the 'Experience with Upper Class' variable changes in its level of significance. This indicates that the relationship between this variable and the perceived importance of meritocratic elements may not be as direct as initially thought. As such, the findings here are consistent with the pathway that NIUBE would predict. 61 For the set examining the Perceived Importance of Non-Meritocratic Elements (Models 5 and 6), the R-squared value remains steady from Model 5 to Model 6 (both 0.34 to 0.37), suggesting that the additional RII variables introduced in Model 6 do slightly increase the explanatory power of the model compared to Model 5. Experience with Me Too Victim shows a strong positive association in Model 5 (3.95), which slightly increases in Model 6 (4.17), and remains significant. This stability suggests that experiences related to the 'Me too' movement have a consistent and robust impact on the perception of non-meritocratic elements, irrespective of the other variables in the model. However, a similar pattern was also found in Models 3 and 4 are also present here. In Model 5, media exposure to “Friends” has a positive coefficient (1.95), suggesting a relationship with the perceived importance of non-meritocratic elements, although it is not as strong as in the previous models concerning meritocratic elements. However, in Model 6, this coefficient decreases slightly and becomes non-significant (-0.17). This change suggests that the inclusion of additional RII variables in Model 6 may account for the effect previously attributed to media exposure to '“Friends”. It also could indicate that media exposure to '“Friends” may not have a stable influence on the perception of non-meritocratic elements when other factors are considered. Second, when moving from Model 5 to Model 6, the 'Experience with BLM Victim” variable changes in its level of significance. This indicates that the relationship between this variable and the perceived importance of non-meritocratic elements may not be as direct as initially thought. Furthermore, there was a large increase in 'Experience with Me Too Victim” from Models 5 and 6, indicating RII could have been a mediating and suppressing factor between this experience and the perceived importance of non-meritocratic elements. Regardless, the findings here are also consistent with the pathway that NIUBE would predict. 62 In Table 5.2, the nested OLS regression models investigate meritocracy scales within the context of the MCU (Marvel Cinematic Universe) dataset. As with the “Friends” dataset analysis, Models 1, 3, and 5 serve as the baseline models examining the Outer Route of the NIUBE Model, while Models 2, 4, and 6 include RII Scale variables, exploring potential mediation effects indicative of the Inner Route of the NIUBE Model. First of all, the F statistics across the models do not support that adding RII measures improved the models. In examining the Outer Route of the NIUBE Model within the MCU dataset, media exposure, and stratification experience variables stand out as significant predictors. 'General TV media exposure Scales' are positively associated with the perceived importance of meritocratic elements, suggesting that general TV viewing is linked to a belief in the value of meritocracy. Media exposure to MCU shows a positive relationship with both meritocratic and non- meritocratic perceptions, indicating that engagement with MCU content correlates with a belief in the significance of both merit-based and alternative success factors. For stratification experiences, Stratification experiences with BLM and Me Too victims initially indicate a negative association with overall perceived meritocracy, due to its positive association with the perceived importance of non-meritocratic elements. Experiences with the upper class consistently correlate with a higher perception of meritocracy, emphasizing the influence of social stratification on meritocratic values. At last, the social Level again is associated with more perceived meritocracy. The Inner Route of the NIUBE Model, focusing on potential mediation effects, is evidenced by the change in significance and magnitude of the Media Exposure to MCU variable upon the introduction of RII Scale variables. When RII variables are added, media exposure to MCU sees a decrease in its association with the perceived importance of meritocratic elements 63 Table 5.2 Nested OLS Regression on Meritocracy Scales on MCU Media Exposure General TV MCU Stratification Experience Social Distance from Black Social Distance from Female Social Distance from Upper Class Experience with BLM Victim Experience with Me too Victim Experience with Upper Class Demographics Age Female Minority Social Level Convervative RII Scale Black Character Backstory Female Character Backstory Wealthy Character Backstory intercept N Overall Perceived Meritocracy Model 1 Model 2 Perceived Importance of Meritocratic Elements Model 3 Model 4 Perceived Importance of Non-Meritocratic Elements Model 5 Model 6 1.72 0.46 1.28 -0.26 1.59 -0.93 1.27 -0.19 2.68 ** 2.93 * 2.50 ** 1.67 0.96 2.47 * 1.07 -0.26 1.08 -0.16 -0.20 0.00 0.91 2.60 -0.20 0.03 -0.11 -2.57 * -4.24 *** 3.33 * -0.21 -2.68 * -4.46 *** 2.75 * -0.44 0.14 -1.33 4.63 *** -0.54 0.00 -1.71 4.15 *** -0.33 2.72 *** 2.91 ** 1.30 -0.33 2.68 ** 2.75 ** 1.40 0.12 -2.78 -2.87 1.41 * -0.79 -3.01 334 0.12 -3.40 -3.34 1.33 * -0.79 -0.26 1.36 0.98 -3.44 334 0.05 0.23 -2.23 1.29 ** -0.54 29.53 *** 0.04 -0.55 -2.71 1.23 ** -0.52 -0.21 2.29 0.05 28.63 *** -0.08 3.01 0.64 -0.12 0.25 32.54 *** -0.07 2.84 0.63 -0.10 0.27 0.05 0.93 -0.93 32.07 *** 334 334 334 334 64 Table 5.2 (cont’d) F (3, 317) R2 0.16 Note: * p<0.05 ** p<0.01 *** p<0.001. 1.19 0.17 0.38 2.4 0.39 0.30 0.33 0.31 65 from Model 3 to Model 4, suggesting a mediating effect. However, the coefficient of media exposure to MCU remains stable and significant from Model 5 to Model 6, even with the inclusion of RII variables.This stability implies that while RII variables may mediate some relationships, the impact of media exposure to MCU on perceptions of non-meritocracy is more direct and less subject to mediation. These findings highlight the complexity of media influence and suggest that the way viewers process media content and its implications for social beliefs may involve intermediary variables as proposed by the NIUBE Model. The nested OLS regression analysis conducted on the “Friends” and MCU datasets reveals significant predictors that align with the Outer Route of the NIUBE Model. Notably, media exposure to '“Friends”, 'Experience with BLM Victim', and 'Experience with Me Too Victim' are consistent with the model's pathway predictions. Media exposure to '“Friends” is positively associated with meritocracy-related outcomes across different models, while 'Experience with BLM Victim' and 'Experience with Me Too Victim' demonstrate a notable shift from a negative association with overall perceived meritocracy to a positive association with the perceived importance of non-meritocratic elements. The Outer Route is generally supported by these results, indicating that media exposure to narrative and stratification experiences play a crucial role in shaping perceptions of meritocracy. However, the Inner Route of the NIUBE Model, which hypothesizes potential mediation effects via RII remains unclear. The nested regression models, which add RII Scale variables to explore these mediation effects, do not conclusively support this potential mediation path. For instance, while media exposure to MCU demonstrates a reduced association with meritocratic elements upon the addition of RII variables from Model 3 to Model 4, suggesting a potential mediating effect, its association with non- meritocratic elements remains stable from Model 5 to Model 6. This indicates that while the RII 66 Scale variables may influence certain relationships, they do not fully account for the observed effects, and the nested regression approach is not adequately equipped to test for mediation. Moving forward, the analysis would benefit from employing a structural equation model. SEM is a more comprehensive statistical technique that can model complex relationships between variables, including mediation and direct and indirect effects. This method could provide a more nuanced understanding of the pathways within the NIUBE Model, clarifying the roles of media exposure, stratification experiences, and RII Character Backstory in shaping perceptions of meritocracy and non-meritocracy. To better understand the inner route, one SEM was conducted for each dataset with the maximum likelihood estimation technique (Jöreskog & Sörbom, 1993) and, focusing on meritocratic and non-meritocratic factors concerning RII of character backstories with the same operational structure as indicated in Figure 2, with latent variables previously examined with CFAs. This approach essentially is the two-step modeling approach recommended by Anderson and Gerbing (1988), where the analysis is conducted with nested models where the measurement model is conducted first and the null model where all paths amongst latent variables are restricted. Figure 3 outlines the SEM model to be conducted with each dataset. As Figure 3 has depicted, all latent constructs are consistent with the measurement models in Tables 2 and 3, with only social distance variables introduced as exogenous observed variables into the model. The Outer Routes discussed above are represented as paths with curved lines, whereas the Inner Routes are paths associated with straight lines. All paths begin with either the latent construct of media exposure to content or the observed construct of Social Distance, and they all lead to one of the two endogenous latent constructs of perceived meritocracy, either directly or indirectly via 67 one of the associated RII Character Backstory latent constructs. Figure 3 Structural Equal Model Diagram 5.5 Structural Equation Model - Friends Table 6 represents the SEM result of the Friends dataset2. The direct estimate represents the direct relationship between one variable and another without the influence of other variables in the model, and the indirect estimate indicates the mediation relationship between the two variables (Muthén, 2011). The total effect is the sum of both direct and indirect effects and represents the overall association between the predictor and outcome variable (Mayer, Thoemmes, Rose, Steyer, & West, 2014). The combination of RMSEA, CFI, and TLI indicates a considerable improvement from the measurement model in Table 2 and an acceptable to good fit of the model to the data, 2 The results for the indicators of the latent variables are substantially similar to the measurement model presented previously, so they are omitted here. 68 suggesting that the model is a reasonable representation of the relationships among the observed variables. RMSEA is 0.07, which suggests a reasonable error of approximation. The CFI value is 0.92, and the TLI value is 0.91, which reinforces the indication that the model's fit is good. Regarding paths initiated from social distance, only Social Distance from females has a negative direct estimate with RII Backstory of Female (-0.08, p < 0.01), which suggests people who have a greater social distance from the female are less likely than others to engage RII on female character’s backstory. For their paths to perceptions, Social Distance from African Americans has a significant negative direct effect (-0.05, p < 0.05), suggesting that greater social distance from African Americans is associated with a lower level of perceived importance of non-meritocratic elements. However, Social Distance from the Upper Class has a significant positive direct effect (0.05, p < 0.05), which implies that greater social distance from the upper class is associated with a higher perceived importance of non-meritocratic elements. These findings again verified the Outer Routes of the NIUBE model which suggests that people process information gathered by their experience heuristically to form their belief about reality. However, the associated Inner Route of the NIUBE model is not activated here. Moving to the paths initiated by media exposure, media exposure to “Friends” reports a significant direct estimate, therefore, the total estimate across all RII constructs (i.e., Black Character at1.11, p < 0.001, Female Character 0.96, p < 0.001, and Weathly Character 1.14, p < 0.001). This provided empirical support for the predicted connection between cultivation theory and TEBOTS, in terms of people being more likely to engage in the systematic processing of narratives such as RII when they consume the narrative heavily. Regarding whether such mental exercise makes a difference in terms of people’s perception of stratification reality, the distinction between meritocratic and non-meritocratic elements within perceived meritocracy 69 relieved additional nuance of the mechanism in the play. Media exposure to “Friends” has a significant positive direct effect (0.33, p < 0.001) on the perceived importance of meritocratic elements, making the total effect significant (0.46, p < 0.001). The mediation effect is observed when media exposure to “Friends” also shows a significant indirect effect (0.13, p < 0.05) on the perceived importance of nonmeritocratic elements, leading to a significant total effect (0.24, p < 0.001). These findings suggest although content-related media exposure shapes both perceived importance in meritocratic and non-meritocratic elements, it did so in different ways. Consistent with the finding in the OLS model, there is again an observed cultivation effect directly to the perceived importance of meritocratic elements. However, this model suggests that this pathway to the perceived importance of non-meritocratic elements from media exposure to content is mediated by RII engagement, which provided empirical support that one of the Inner Routes of the NIUBE model is activated when reading it together with media exposure to content’s direct estimates to RII Backstory as previously mentioned. Consistent with the OLS finding in the previous section, RII the backstory of Wealthy Character has a significant positive direct effect (0.12, p < 0.05) on the perceived importance of non-meritocratic elements. This finding is particularly interesting, as it is consistent with TEBOTS and the Self- Determination Theory, as the process of forming such a dual consciousness inevitably involves a threat to people’s pre-existing beliefs, whereas the reiteration of the pre-existing beliefs does not present such a threat to people’s inner selves. As results indicated, RII is not activated when it comes to meritocratic elements, as these “Friends” audiences can process this content relatively at ease. When it comes to non-meritocratic elements, RII is activated to allow them to successfully merge the potentially contradictory belief regarding the importance of non- meritocratic elements onto their worldview. 70 Table 6 Structural Equation Model – Friends Path to Perceived Importance of Meritocratic Element From Direct Indirect Total RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.03 -0.02 0.17 -0.03 0.01 -0.01 0.00 0.00 0.00 0.00 0.00 -0.01 -0.03 -0.02 0.17 -0.03 0.01 -0.02 Cultivation Media Exposure to Content 0.33 *** 0.14 0.46 *** Perceived Importance of Non-Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.02 0.02 0.12 * -0.05 * -0.03 0.05 * 0.00 0.00 0.00 0.00 -0.00 -0.00 -0.02 0.02 0.12 * -0.05 * -0.03 0.04 * Cultivation Media Exposure to Content 0.10 0.13 * 0.24 *** 71 Table 6 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Media Exposure to Content Social Distance from Female Media Exposure to Content Social Distance from Upper Class Media Exposure to Content N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. See Table 13 for the associated correlation matrix -0.03 1.11 *** -0.08 ** 0.96 *** -0.03 1.14 *** -0.03 1.11 *** 0.00 0.00 -0.08 ** 0.96 *** 0.00 0.00 0.00 0.00 -0.03 1.14 *** 327 0.07 0.92 0.91 1228.64 72 In other words, the backstories of female, black, or wealthy characters somewhat filled the gap between reality and the non-meritocratic elements they sensed from the narrative. The findings here suggest that people are engaging in different types of psychological activities depending on the aspects of reality. When it comes to their dominant ideology of society, which is the American Dream or the perceived importance of meritocratic elements as how it is essentially called here, they would process relevant information obtained from the narrative heuristically – the cultivation effects directly link narrative consumption to the perception or the Outer Routes of the NIUBE model. However, in their process of forming the dual consciousness, which is essentially accepting a contradictory or at the minimum inconsistent set of beliefs to the dominant ideology they were taught or grew up with, they would have to engage in the systematic processing – mediation via RII or the Inner Route of the NIUBE Model, precisely because of these beliefs challenged their older selves. 5.6 Structural Equation Model - MCU Table 7 represents the result from the SEM analysis conducted with the MCU dataset3.The model fit indicators for the MCU although indicating a considerable improvement from the measurement model in Table 3, show a slightly less ideal fit compared to the model for "Friends". RMSEA is 0.08, which is at the upper limit of what is typically considered a reasonable fit, suggesting the model has an acceptable approximation error. CFI is 0.89, just below the 0.90 threshold often used to suggest a good fit, indicating a somewhat adequate fit to the data. TLI is 0.88, also below the 0.90 benchmarks, further indicating that the model fit is 3 The results for the indicators of the latent variables are substantially similar to the measurement model presented previously, so they are omitted here. 73 adequate but not as strong as it could be. The Chi-square statistic is 1394.07 with 475 degrees of freedom, which is relatively high and suggests that the model may not fit the data perfectly. Starting with the paths originating from media exposure to MCU, it once again reports a significant direct estimate, therefore, the total estimate across all RII constructs. Furthermore, the model indicates that it also has a strong, significant direct effect (0.30, p < 0.001) on the perceived importance of non-meritocratic elements, leading to a total effect of 0.41 (p < 0.001), indicating a robust relationship between content engagement and the perception of meritocracy. Meanwhile, it demonstrates also a significant direct effect (0.24, p < 0.001) on the perceived importance of non-meritocratic elements, implying a strong influence of narrative engagement on the perception of non-meritocratic elements in society. These significant effects suggest that content media exposure within the MCU has a strong influence on the perception of both meritocratic and non-meritocratic elements. This indicates that heavy consumption of MCU narratives is associated with how individuals perceive social stratification, potentially impacting their views on meritocracy and non-meritocracy. Furthermore, Social Distance from African Americans shows a positive direct effect (0.06, p < 0.05) on the perceived importance of meritocratic elements, suggesting that a greater social distance may slightly increase the perceived importance of meritocracy. The negative direct effect of Social Distance from Female on the RII Backstory of Female Character" (-0.06, p < 0.05) implies that those with greater social distance from females are less likely to engage with the backstories of female characters. Overall, these findings support the notion that narrative consumption is linked to perceptions of social reality. They suggest that the MCU may influence viewers' social perceptions in a manner consistent with cultivation theory and the proposed mechanisms within the NIUBE model, with direct effects illustrating the outer routes (heuristic processing) and the 74 Table 7 Structural Equation Model – MCU Path to Perceived Importance of Meritocratic Element From Direct Indirect Total RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.07 0.12 0.05 0.06 * 0.01 -0.04 0.00 0.00 0.00 0.00 -0.01 0.00 -0.07 0.12 0.05 0.07 * 0.00 -0.04 Cultivation Media Exposure to Content 0.30 *** 0.10 0.41 *** Perceived Importance of Non-Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.01 0.09 -0.07 -0.03 -0.01 0.01 0.00 0.00 0.00 0.00 -0.01 -0.00 -0.01 0.09 -0.07 -0.03 -0.01 0.00 Cultivation Media Exposure to Content 0.24 *** 0.00 0.25 *** 75 Table 7 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Media Exposure to Content Social Distance from Female Media Exposure to Content Social Distance from Upper Class Media Exposure to Content N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. See Table 14 for the associated correlation matrix -0.06 0.97 *** -0.06 * 0.95 *** 0.03 1.09 *** -0.06 0.97 *** 0.00 0.00 -0.06 * 0.95 *** 0.00 0.00 0.00 0.00 0.03 1.09 *** 334 0.08 0.89 0.88 1394.07 76 absence of indirect effects suggesting that inner routes (systematic processing) may not be significantly mediated by RII engagement in this context. The presence of mediation effects in the "Friends" model but not in the MCU model could be due to several factors. First, Cultivation theory suggests that long-term exposure to narrative shapes viewers' perceptions of reality. "Friends," with its long-run and episodic nature, may allow for deeper cultivation effects, where indirect mediations can develop over time. In contrast, the MCU, while extensive, is made up of less frequent, high-intensity blockbusters that might not allow for the same type of cultivation. Furthermore, "Friends" is a sitcom that often deals with everyday situations and social interactions that may resonate more directly with viewers' personal experiences and social realities. This might lead to a more nuanced processing of information where indirect paths and mediation effects are more likely to occur. The absence of mediation in the MCU model suggests its superhero fantasy nature may drive viewers away from engaging in the deeper, more reflective processing that would give rise to mediated effects. Instead, the MCU's impact on viewers' perceptions appears to be more direct and less contingent on additional cognitive or narrative processes. 5.7 Moderation by Race As such, in refining our understanding of the NIUBE model's inner route, as supported by prior analyses, I undertook further moderation analysis to delve deeper into the intricate dynamics within the model with the “Friends” dataset4. This involved the introduction of eight additional SEMs dividing respondents into the dominant and subordinate groups across four 4 Multigroup SEMs based onrace, gender, social leve, and age wwere also applied to the MCU dataset as a supplementary analysis. The outcomes closely mirrored those presented in Table 7, indicating a consistency in the findings across different datasets. Consequently, to maintain the focus and conciseness of the dissertation, these additional analyses have been excluded from the main text. However, detailed results are documented and can be made available upon request. 77 demographic dimensions (i.e., race, gender, social class, and age). The logic of this division is rooted deeply in the dominant ideology so any division separating respondents into dominant and subordinate groups would advance the analysis. Research has found that the dominant ideology, as a way the dominant group maintains the status quo and maintains their vested interest, is force-fed to the subordinate groups (Huber & Form, 1973; James R. Kluegel & Smith, 1986). In fact, the dominant ideology is more prevalent amongst the subordinate group, because they are usually isolated with limited experience of social mobility (A. A. Young, 2006). Mediated narratives like “Friends” could be the window for them to have a glance at how the stratification system beyond their circle functions. This presents a more vulnerable context for them to trigger systematic processing and, therefore, activation of the Inner Route of the NIUBE model. Therefore, the first set of models exclusively examines data from minority respondents, while the second focuses solely on responses from white respondents. This bifurcation allows for a more nuanced exploration of racial dynamics within the model. The moderation under gender context pivots on gender. The SEMs in this context are specifically differentiated based on female respondents, enabling an in-depth analysis of gender-specific trends and influences within the model. In the context of social class, the SEMs are segregated based on self-reported social levels of the respondents. One model concentrates on individuals who rated their social level at 5 or below, offering insight into lower socio-economic tiers. Conversely, the other model focuses on those who perceive their social status as above level 5, thus shedding light on the perspectives and patterns prevalent in higher social echelons. Finally, age would serve as the moderator independent of race, gender, and social class, where one model is conducted with respondents aged below 35, and the other model is estimated with respondents aged 35 or above. This multi- faceted approach ensures a comprehensive and detailed examination of the NIUBE model, taking 78 into account the diverse and potentially influential demographic factors that might affect the model's dynamics and outcomes. With race as the moderator, Table 8 compares the SEM results for minority respondents and white respondents in the “Friends” dataset5: 51 respondents identified themselves as one of the minority status (i.e., Black, Asian, Latino, etc.), whereas 276 of the respondents identified as White. Because of the limited number of minority respondents represented in this dataset, Table 8 must be interpreted with caution as it cannot be ruled out that the result for Whites respondents is merely a repeat of the original Table 6, due to the limited representations of Minority respondents in the dataset. Compared to the SEM result in Table 6, the model fit for the Minority is poor, with an RMSEA of 0.14, CFI of 0.71, and TLI of 0.68. However, the model fits hold for the white model, with an RMSEA of 0.07, CFI of 0.92, and TLI of 0.91, similar to the initial SEM results, indicating a reasonable representation for the White group. Consistent with Table 6, media exposure to “Friends” again reports a significant direct estimate, therefore, the total estimate across all RII constructs in both groups. However, Minority respondents report their media exposure to “Friends” has a significant total effect (0.33, p < 0.05) on the perceived importance of meritocratic elements, without a clear indication of whether it is primarily caused directly or indirectly. However, White respondents report their media exposure to “Friends” has a significant direct effect (0.30, p < 0.05), resulting in a significant total effect (0.47, p < 0.001) on the perceived importance of meritocratic elements. As such, the moderation model does not reveal additional nuance over the heuristic processing leading to the cultivated confirmation of the dominant ideology. However, Minority respondents report their media exposure to “Friends” 5 The results for the indicators of the latent variables are substantially similar to the measurement model presented previously, so they are omitted here. 79 has a significant direct effect (0.21, p < 0.05) on the perceived importance of non-meritocratic elements, whereas this association of White respondents’ media exposure to “Friends” is indirect (0.24, p<0.01). This finding is unexpected and could simply be a repeat of Table 6, but it is potentially revealing. This finding suggests although both Minority and Whites respondents’ perceived level of importance over non-meritocratic elements would increase while they watch more “Friends,” Minority would achieve this directly by heuristic processing the content whereas Whites would do so via systemic processing through RII. The dominant ideology theory cannot account for this finding, but this can make sense under the framework of self-serving attribution bias, where people attribute successes to their own but blame failure on external factors (Mezulis, Abramson, Hyde, & Hankin, 2004). As such, this finding may be indicative that it would be more difficult for Whites to accept the importance of non-meritocratic elements, as this essentially undermines the justification of their vested interests and the dominant status. As the notion of non-meritocratic elements is important and becomes more and more prevalent to them via their increased level of “Friends” consumption, it increasingly poses a direct threat to them personally, to the point that they engage in the systematic processing of this information via RII, which in the end formulated the unified consense with the importance of non-meritocratic elements they acknowledge in “Friends.” 80 Table 8 Structural Equation Model - Friends -Moderation by Race Path to Perceived Importance of Meritocratic Element Perceived Importance of Non-Meritocratic Element From Direct Indirect Total Minorty1 RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Cultivation Media Exposure to Content RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.03 0.19 0.02 -0.18 0.12 -0.13 0.15 0.01 0.07 -0.11 -0.04 -0.09 0.03 0.00 0.00 0.00 0.00 -0.05 -0.00 -0.03 0.19 0.02 -0.18 0.07 -0.13 0.17 0.33 * 0.00 0.00 0.00 -0.00 -0.02 0.01 0.01 0.07 -0.11 -0.04 -0.11 0.05 Cultivation Media Exposure to Content 0.21 * -0.03 0.18 * 81 Table 8 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Media Exposure to Content Social Distance from Female Media Exposure to Content -0.01 0.94 *** -0.27 * 0.96 *** 0.00 0.00 0.00 0.00 Social Distance from Upper Class Media Exposure to Content -0.12 1.03 *** 0.00 0.00 -0.01 0.94 *** -0.27 * 0.96 *** -0.12 1.03 *** N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 15.1 for the associated correlation matrix 2 See Table 15.2 for the associated correlation matrix 51 0.14 0.71 0.68 977.58 82 Table 8 (cont’d) Path to Perceived Importance of Meritocratic Element From RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Direct White2 Indirect Total -0.01 -0.12 0.25 * 0.01 -0.01 -0.00 0.00 0.00 0.00 0.00 0.01 -0.00 -0.01 -0.12 0.25 * 0.01 -0.01 -0.00 Cultivation Media Exposure to Content 0.30 * 0.17 0.47 *** Perceived Importance of Non-Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.02 -0.03 0.24 ** -0.04 -0.03 0.05 * 0.00 0.00 0.00 0.00 0.00 -0.00 -0.02 -0.03 0.24 ** -0.04 -0.03 0.04 * Cultivation Media Exposure to Content 0.01 0.24 ** 0.24 *** 83 Table 8 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Media Exposure to Content Social Distance from Female Media Exposure to Content Social Distance from Upper Class Media Exposure to Content N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 15.1 for the associated correlation matrix 2 See Table 15.2 for the associated correlation matrix -0.03 1.17 *** -0.06 0.99 *** -0.02 1.18 *** -0.03 1.17 *** 0.00 0.00 -0.06 0.99 *** 0.00 0.00 0.00 0.00 -0.02 1.18 *** 276 0.07 0.92 0.91 1082.39 84 5.8 Moderation by Gender Table 9 compares the SEM results for female respondents and male respondents in the “Friends” dataset6: First of all, the model fits are reasonable in both models, with an RMSEA of 0.08, CFI of 0.90, and TLI of 0.89 in the Female Model and an RMSEA of 0.07, CFI of 0.92, and TLI of 0.91 with the male models. Consistent with Table 6, media exposure to “Friends” again reports a significant direct estimate, therefore, the total estimate across all RII constructs in both groups. Furthermore, Female respondents report their media exposure to “Friends” has a significant direct effect (0.24, p < 0.05) and indirect effect (0.16, p<0.05) on the perceived importance of meritocratic elements, as well as only a significant indirect effect (0.11, p<0.05) on the perceived importance of non-meritocratic elements. Male respondents’ media exposure to “Friends”, on the other side, reported only a significant direct effect on both the perceived importance of meritocratic elements (1.01, p < 0.01) and non-meritocratic elements (0.39, p < 0.05). As such, the moderation by gender is supported by the result, which sheds light on the power dynamics between men and women by revealing how each gender processes information about social stratification differently. This differential processing is not merely a matter of cognitive style but is deeply entwined with the power disparities between genders in society. Women, identified as the subordinate group in these results, resort to the Inner Route of narrative processing more often than men. This suggests that women are engaging in a more analytic and in-depth examination of the narratives they consume. This could be interpreted as a response to their lived experiences of social mobility, which may differ significantly from those of men. 6 The results for the indicators of the latent variables are substantially similar to the measurement model presented previously, so they are omitted here. 85 Since women historically and contemporaneously experience barriers to social mobility, their more systematic approach to processing narratives might reflect an attempt to reconcile the meritocratic promises of these narratives with the reality of persistent gender-based obstacles. The reliance on the Inner Route by women might also represent a form of empowerment, a way to critically analyze and question the status quo that upholds the power imbalance. By engaging deeply with RII, women are potentially equipping themselves with a more nuanced understanding of social dynamics, which could be a precursor to seeking or advocating for change. In contrast, men's tendency to stay on the Outer Route of processing, characterized by a more heuristic approach, suggests a different relationship with power. As the dominant group, men might not feel as compelled to scrutinize the narratives of social mobility because the existing social structures often validate their experiences and align with the promises of these narratives. This heuristic processing could be indicative of the comfort that comes with power— the power to take for granted that the system works, at least for those who are already in a position of advantage. The results also highlight how women are less likely to process challenging ideologies heuristically, which implies that women are more inclined to critically evaluate narratives that question or oppose the dominant social order. In contrast, the dominant ideologies are processed heuristically by women, which might reflect the internalization of these ideologies. This points to the complexity of power dynamics; even as women may critique and analyze the dominant social narratives, the pervasiveness of these narratives makes them difficult to fully escape. The deep- rooted nature of the dominant ideology within women could be seen as a manifestation of the power these ideologies hold over the subordinate group, maintaining the status quo by influencing the belief systems of those it subjugates. Overall, these results suggest that the 86 gendered power imbalance is not only a feature of social structures but also a force that shapes the cognitive processes of narrative engagement. Women's systematic processing might be a cognitive countermeasure to the structural power differentials they face, while men's heuristic processing reflects the reinforcing loop between power and the acceptance of dominant narratives. 87 Table 9 Structural Equation Model - Friends -Moderation by Gender Path to From Direct Indirect Total Female1 Perceived Importance of Meritocratic Element Perceived Importance of Non- Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class 0.06 0.06 0.05 0.07 0.02 -0.08 * 0.00 0.00 0.00 -0.00 -0.01 -0.00 0.06 0.06 0.05 0.06 0.01 -0.09 * Cultivation Media Exposure to Content 0.24 * 0.16 * 0.40 *** RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.02 0.04 0.10 -0.03 -0.05 0.03 0.00 0.00 0.00 0.00 -0.00 -0.00 -0.02 0.04 0.10 -0.03 -0.05 0.03 Cultivation Media Exposure to Content 0.09 0.11 * 0.20 *** 88 Table 9 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Content Cultivation Social Distance from Female Content Cultivation Social Distance from Upper Class Content Cultivation N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 16.1 for the associated correlation matrix 2 See Table 16.2 for the associated correlation matrix -0.02 1.00 *** -0.10 * 0.85 *** -0.04 0.99 *** -0.02 1.00 *** 0.00 0.00 -0.10 * 0.85 *** 0.00 0.00 0.00 0.00 -0.04 0.99 *** 171 0.08 0.90 0.89 942.09 89 Table 9 (cont’d) Path to From Perceived Importance of Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Male and Others2 Indirect Total Direct -0.23 -0.47 * 0.26 -0.13 ** -0.02 0.07 0.00 0.00 0.00 0.00 0.03 -0.01 -0.23 -0.47 * 0.26 -0.12 ** 0.02 0.06 Perceived Importance of Non- Meritocratic Element Cultivation Media Exposure to Content 1.01 ** -0.48 0.53 *** RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.03 -0.24 0.17 -0.05 -0.04 0.06 * 0.00 0.00 0.00 0.00 0.02 -0.00 -0.03 -0.24 0.17 -0.05 -0.03 0.06 * Cultivation Media Exposure to Content 0.39 * -0.08 0.31 *** 90 Table 9 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Content Cultivation Social Distance from Female Content Cultivation Social Distance from Upper Class Content Cultivation N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 16.1 for the associated correlation matrix 2 See Table 16.2 for the associated correlation matrix -0.02 1.26 *** -0.07 1.13 *** -0.02 1.31 *** -0.02 1.26 *** 0.00 0.00 -0.07 1.13 *** 0.00 0.00 0.00 0.00 -0.02 1.31 *** 156 0.07 0.92 0.91 814.51 91 5.9 Moderation by Social Class The next set of SEM examines the potential role that social class plays as a moderator within the NIUBE model. Table 10 compares the SEM results for lower-class respondents and upper-class respondents in the “Friends” dataset7: 109 respondents reported they are currently located at a social level 5 and below, which is posited at the middle of the 10 levels provided in the questionnaires. 218 respondents identified themselves as currently located at a social level above 5. Compared to the SEM result in Table 6, the model fit for the lower-class model is slightly poorer than the original model in Table 6, with an RMSEA of 0.09, CFI of 0.87, and TLI of 0.86. However, the model fits hold for the upper-class model, with an RMSEA of 0.06, CFI of 0.92, and TLI of 0.91. Consistent with Table 6, Media exposure to “Friends” again reports a significant direct estimate, therefore, the total estimate across all RII constructs in both models. Furthermore, the pattern of Media exposure to “Friends” in the lower-class model is essentially the same here as it is in Table 6. However, although the upper-class respondents report their Media exposure to “Friends” has a significant total effect on both the perceived importance of meritocratic (0.35, p<0.001) and non-meritocratic (0.27, p<0.001) elements, it is not clear if this is primarily due to its direct or indirect effect. 7 The results for the indicators of the latent variables are substantially similar to the measurement model presented previously, so they are omitted here. 92 Table 10 Structural Equation Model - Friends -Moderation by Social Class Path to From Social Level as 5 or Below1 Indirect Direct Total Perceived Importance of Meritocratic Element Perceived Importance of Non- Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class 0.06 0.01 -0.02 -0.04 -0.09 0.07 0.00 0.00 0.00 -0.01 -0.00 0.00 0.06 0.01 -0.02 -0.04 -0.09 0.07 Cultivation Media Exposure to Content 0.57 *** 0.06 0.63 *** RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class -0.02 0.08 0.07 -0.09 ** -0.01 0.05 0.00 0.00 0.00 0.00 -0.02 -0.00 -0.02 0.08 0.07 -0.09 ** -0.03 0.05 Cultivation Media Exposure to Content 0.09 0.13 * 0.22 *** 93 Table 10 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Content Cultivation Social Distance from Female Content Cultivation Social Distance from Upper Class Content Cultivation N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 17.1 for the associated correlation matrix 2 See Table 17.2 for the associated correlation matrix - 0.11 1.07 *** - 0.23 *** 0.90 *** - 0.04 1.11 *** -0.11 1.07 *** 0.00 0.00 -0.23 *** 0.90 *** 0.00 0.00 0.00 0.00 -0.04 1.11 *** 109 0.09 0.87 0.86 935.36 94 Table 10 (cont’d) Path to From Perceived Importance of Meritocratic Element Perceived Importance of Non- Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Cultivation Media Exposure to Content RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Social Level Above 52 Indirect Total Direct -0.23 0.03 0.30 ** -0.01 0.05 -0.03 0.23 -0.08 -0.02 0.16 -0.02 -0.05 0.04 0.00 0.00 0.00 -0.00 -0.00 -0.01 -0.23 0.03 0.30 ** -0.02 0.05 -0.04 0.12 0.35 *** 0.00 0.00 0.00 -0.00 0.00 -0.01 -0.08 -0.02 0.16 -0.02 -0.05 0.03 Cultivation Media Exposure to Content 0.20 0.07 0.27 *** 95 Table 10 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Content Cultivation Social Distance from Female Content Cultivation Social Distance from Upper Class Content Cultivation N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 17.1 for the associated correlation matrix 2 See Table 17.2 for the associated correlation matrix 0.01 1.13 *** -0.00 1.01 *** -0.04 1.16 *** 0.01 1.13 *** 0.00 0.00 -0.00 1.01 *** 0.00 0.00 0.00 0.00 -0.04 1.16 *** 218 0.06 0.92 0.91 896.64 96 The moderation by social class, as indicated by the results, adds a layer of complexity to how individuals from different socioeconomic backgrounds process narratives around meritocracy. The distinction in cognitive processing between the upper and lower classes can be seen as a reflection of their respective experiences with and investments in the prevailing social order. For lower-class respondents, the heuristic processing of meritocratic elements may be indicative of their surrendering to the dominant ideology of meritocracy. This heuristic acceptance might stem from a deeply ingrained societal message brainwashed to them institutionally – one must give in to the meritocratic ideal. However, their lived experience, which likely includes systemic barriers to social mobility, may not align with this meritocratic narrative. As a result, they may engage in more systematic processing via RII when considering non-meritocratic elements of society that speak more directly to social mobility which they are foreign to. This systematic engagement with non-meritocratic elements suggests a critical analysis and a search for a deeper understanding of the structures that maintain class disparities. It may be a reflection of a desire to uncover and challenge the elements of the social system that contribute to their subordinate status. The power differential between the upper and lower classes, therefore, can be seen as not only a matter of economic disparity but also as a divergence in the cognitive approaches to understanding and justifying social hierarchies. Lower-class individuals, grappling with the dissonance between the meritocratic ideal and their reality, may scrutinize the narratives that account for structural inequalities. In contrast, upper-class individuals, whose is inclined to affirm the meritocratic ideal and acknowledge alternative ways to success, may either accept it without question or analyze it strategically to perpetuate their advantageous position. By contrast, the absence of a precise explanation for how upper-class respondents process this 97 information leaves room for speculation. It is plausible that upper-class individuals might process both meritocratic and non-meritocratic elements heuristically, given that the social system already works in their favor. Their social mobility and status are more secure may not feel the same impetus to engage critically with these narratives. Their position of privilege within the social hierarchy affords them the luxury of taking the meritocratic narrative at face value, as it serves to justify and maintain their status. The need to critically examine the meritocratic narrative or to deeply understand the mechanisms of social stratification is less pressing when the narrative of success based on merit justifies the vested benefit. 5.10 Moderation by Age The final set of SEM examines the potential role that age plays as a moderator within the NIUBE model. Table 11 compares the SEM results for respondents aged below 35 and respondents aged 35 or above in the “Friends” dataset8. 181 respondents reported them as of age below 35, which is the approximate mean age in this dataset based on Table 4. 146 respondents reported they are older than 35. Consistent with the previous moderation models, the significant difference lies again in the indirect effects of media exposure to content. For the group below 35, media exposure to content has a strong indirect effect on the perceived importance of meritocratic elements, while for the group aged 35 or above, the indirect effect is not significant. The absence of a significant indirect effect among the older group may suggest that their perception of meritocracy is less influenced by the nuanced or mediated RII character backstories compared to younger viewers. The presence of indirect effects of Media exposure on the perception of meritocratic elements among the younger group (below 35) can be 8 The results for the indicators of the latent variables are substantially similar to the measurement model presented previously, so they are omitted here. 98 understood as part of a developmental and cognitive journey in the context of social learning and belief formation. Like women to men, young people’s experience of the stratification system is limited compared to older people. Younger individuals are generally in a life stage where they are actively learning, integrating new information, and forming their worldviews. This formative process involves not just direct experiences but also the integration of indirect cues from the surrounding social context, including media narratives and peer influences, even on meritocratic elements. Thus, the indirect effects in the SEM results highlight a developmental journey in cognitive processing and belief formation. Younger individuals, due to their limited understanding of the stratification system, engage more thoroughly with media content that challenges their nascent belief in a meritocratic system, leading to a greater impact through indirect paths. In contrast, older individuals, with their beliefs more solidified, may not engage in such extensive systematic processing. For the older group (35 or above), the absence of significant indirect effects might suggest that these individuals rely more on heuristic processing when it comes to meritocratic elements. As the dominant group, they might not feel the need to engage in systematic processing, as the belief in meritocracy is likely already working in their favor. On the other side of the same token, for the younger group (below 35), the significant indirect effects of media exposure to non-meritocratic elements may indicate a more complex cognitive engagement. When faced with content that challenges their pre-existing meritocratic beliefs, such as narratives presenting non-meritocratic pathways to success, they are likely to engage in systematic processing. This is consistent with the inner route of the NIUBE model, which involves a deeper, more analytic approach to reconcile new information with existing beliefs. 99 Table 11 Structural Equation Model - Friends -Moderation by Age Path to From Perceived Importance of Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Direct Age below 351 Indirect Total 0.04 -0.10 0.34 * -0.07 0.06 0.01 0.00 0.00 0.00 -0.00 0.01 -0.01 0.04 -0.10 0.34 * -0.07 0.07 0.00 Perceived Importance of Non- Meritocratic Element Cultivation Media Exposure to Content 0.07 0.34 * 0.41 *** RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class 0.06 -0.05 0.26 ** -0.04 -0.02 0.04 0.00 0.00 0.00 -0.00 0.00 -0.01 0.06 -0.05 0.26 ** -0.05 * -0.02 0.03 Cultivation Media Exposure to Content -0.11 0.32 *** 0.21 *** 100 Table 11 (cont’d) RII Backstory Black Character Female Character Wealthy Character Social Distance from African- American Content Cultivation Social Distance from Female Content Cultivation Social Distance from Upper Class Content Cultivation N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 18.1 for the associated correlation matrix 2 See Table 18.2 for the associated correlation matrix -0.03 1.06 *** -0.06 0.94 *** -0.02 1.15 *** -0.03 1.06 *** 0.00 0.00 -0.06 0.94 *** 0.00 0.00 0.00 0.00 -0.02 1.15 *** 181 0.08 0.89 0.88 965.76 101 Table 11 (cont’d) Path to From Perceived Importance of Meritocratic Element RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class Direct Age below 352 Indirect Total 0.04 -0.10 0.34 * -0.07 0.06 0.01 0.00 0.00 0.00 -0.00 0.01 -0.01 0.04 -0.10 0.34 * -0.07 0.07 0.00 Perceived Importance of Non- Meritocratic Element Cultivation Media Exposure to Content 0.07 0.34 * 0.41 *** RII Backstory Black Character Female Character Wealthy Character Social Distance from African-Americans Female Upper Class 0.06 -0.05 0.26 ** -0.04 -0.02 0.04 0.00 0.00 0.00 -0.00 0.00 -0.01 0.06 -0.05 0.26 ** -0.05 * -0.02 0.03 Cultivation Media Exposure to Content -0.11 0.32 *** 0.21 *** 102 Table 11 (cont’d) RII BackstA18:H29 Female Character Wealthy Character Social Distance from African- American Content Cultivation Social Distance from Female Content Cultivation Social Distance from Upper Class Content Cultivation N RMSEA CFI TLI Chi2(475) Note: * p<0.05 ** p<0.01 *** p<0.001. 1 See Table 18.1 for the associated correlation matrix 2 See Table 18.2 for the associated correlation matrix -0.03 1.06 *** -0.06 0.94 *** -0.02 1.15 *** -0.03 1.06 *** 0.00 0.00 -0.06 0.94 *** 0.00 0.00 0.00 0.00 -0.02 1.15 *** 181 0.08 0.89 0.88 965.76 103 Younger viewers, still forming their ideological stances, must work through the dissonance between their taught meritocratic values and the alternative, often non-meritocratic realities depicted in "Friends." This processing can involve seeking additional information, reflecting on the content, and integrating it with prior knowledge, which can lead to a change in beliefs or the strengthening of existing ones. 5.11 Summary The analysis of the NIUBE model through the lens of different demographic factors using the "Friends" dataset has yielded insights into the processing of meritocratic and non- meritocratic narratives. These nuanced differences in narrative processing across race, gender, and social class become strikingly evident. The additional SEMs, designed specifically to parse the complex interplay of these categorical variables, have provided a layered understanding of how individuals from various demographic backgrounds engage with and internalize narratives of social stratification. The racial context of the analysis unveils a pronounced disparity in the processing of narratives between minority and white respondents. White respondents, in contrast, engage in a more complex, systematic processing through RII on non-meritocratic elements. This may indicate a deeper cognitive engagement with narratives that could potentially threaten their position within the social hierarchy, prompting a more reflective and possibly defensive stance. In terms of gender, the SEMs reveal a distinct divergence in the way men and women approach narratives of social mobility. Women's more frequent engagement with the systematic Inner Route suggests a deeper, more analytical processing of these narratives. This pattern may be indicative of an adaptive response to the gendered barriers they encounter, pointing to a critical interrogation of the social structures that underpin their lived experiences. Such engagement 104 could represent an empowering mechanism to challenge the prevailing power imbalances. Conversely, men's reliance on the heuristic Outer Route underscores a cognitive alignment with the existing social order, which typically affirms their experiences and validates the meritocratic narrative from which they benefit. The moderation by social class adds a further dimension to the analysis. Lower-class respondents show a tendency toward heuristic processing of meritocratic elements, potentially signifying their surrendering to the dominant ideology. However, their systematic processing of non-meritocratic elements via RII suggests a conscious effort to critically assess the structural barriers to social mobility. The upper-class respondents, while exhibiting significant effects in their processing of both meritocratic and non-meritocratic elements, leave room for interpretation regarding the directness or mediation of these effects. It raises the possibility that the upper class might engage in heuristic processing to uphold the narratives that justify their advantageous positions or that they might systematically dissect these narratives to strategically reinforce their socio-economic status. Adding to this multifaceted landscape is the age-based analysis. Younger individuals, socialized to believe in meritocracy and still forming their ideological stances, exhibit significant indirect effects of media exposure to content. This suggests a complex engagement, where systematic processing through the Inner Route of the NIUBE model is necessitated when media content conflicts with their pre-existing beliefs. Older individuals, representing a more dominant group with established views, show no significant indirect effects, implying a reliance on heuristic processing and confidence in their worldviews that is less susceptible to indirect media influences. Ultimately, these results paint a complex portrait of the intersection between demographic factors and narrative processing. They underscore that power disparities, whether based on gender, race, or class, extend beyond tangible socioeconomic differences into the 105 cognitive realm. These disparities influence not only how different groups perceive the narratives of social stratification but also how they internalize and respond to these narratives. The findings suggest that an individual's position within the social fabric significantly shapes their engagement with and interpretation of the stories that define and delineate the contours of societal hierarchies and opportunities. 106 CHAPTER 6: DISCUSSION AND THEORETICAL IMPLICATION This dissertation proposed the NIUBE model. Grounded in cultivation theory, the model suggests that consistent exposure to media narratives can heuristically influence people's perceptions of social reality. When people encounter conflict between pre-existing beliefs and the narratives, they feel a strong need to make sense of it all. This need pushes them to mentally reconcile these stories into their own experiences, helping them to overcome their own limits and see beyond their current understanding. RII is one of the psychological exercises they can engage in to achieve this goal (Slater et al., 2014). Therefore, the NIUBE model outlines two pathways of belief shaping: the Outer Route, which involves the direct shaping of beliefs through media and experience, and the Inner Route, which involves the systematic processing of narratives and experiences that shape beliefs indirectly through psychological engagement such as RII. This dissertation advances the literature in several ways while providing additional empirical support and confirmations to the existing scales and theories. First, it validated the expansion of RII scales’ applicability regarding two additional contents, namely “Friends” and MCU. Although it only focused on the backstory aspect of the scales, this provided additional empirical support for the validity and reliability of the scales developed by previous scholars (Ewoldsen et al., 2021). It also provided additional empirical validation to the perceived meritocracy scales from previous studies (Xian & Reynolds, 2017). Furthermore, it confirms the cultivation effect based on content-specific measures and provides crucial updates to the classic theory of recognizing people’s narrative consumption behavior nowadays (Morgan et al., 2014). Finally, it proposed and tested a new NIUBE model regarding how individuals engage with media narratives based on their experiences to shape their understanding of stratification systems by incorporating Self-Determination Theory and Cultivation Theory via TEBOTS by 107 operation of RII, which delves into the rarely examined and infrequent phenomenon of the resonating effect within the literature of the cultivation tradition. By applying the NIUBE model to the study of media influences on perceptions of meritocracy, the dissertation aims to empirically test and validate this theoretical framework. It considers the resonance between media narratives, such as those from "Friends" and MCU, and personal experiences, especially in light of movements like Black Lives Matter and Me Too. Perceived meritocracy is a cornerstone of the American Dream, where success is viewed as a result of personal effort and innate ability (M. Young, 2017). However, there is debate over how society actually embodies meritocratic values, with some research indicating a strong American belief in meritocracy, while other studies show significant variation in these perceptions. Social movements like BLM and MeToo have challenged the meritocratic narrative by exposing the systemic barriers that marginalized groups face (Clair et al., 2019; Martin, 2018). These movements have initiated a critical reevaluation of what constitutes merit and success, influencing the collective consciousness and prompting individuals and institutions to reconsider societal structures and biases. "Friends" portrays a New York City life that aligns with the ideals of the American Dream, while MCU offers a more diverse narrative, with characters from different socioeconomic backgrounds (Kohen, 2022; Sandell, 1998). However, both narratives contribute to shaping societal beliefs, with "Friends" subtly touching on stratification-related issues and MCU challenging traditional gender roles and representing a powerful portrayal of African heritage and pride. This dissertation undertook a rigorous empirical assessment of the NIUBE model by testing and validating the measures of perceived meritocracy, media exposure, and RII within the context of "Friends" and the MCU. The research employs nested ordinary least squares 108 regression and structural equation modeling to examine the intricate relationships between media narratives, personal experiences, and the formation of beliefs about societal stratification. This approach underscores the psychological quest for coherence as a key factor in how individuals engage with media narratives and integrate their personal experiences. The model posits two pathways through which beliefs are shaped: the direct impact of media and experiences (Outer Routes), and the internal mental reconciliation processes (Inner Routes). The RII process serves as a mediator, helping individuals assimilate or reinterpret information to maintain coherence within their belief systems, crucial for reconciling discrepancies between existing beliefs and new experiences or information. 6.1 Reflection on Cultivation This dissertation also revealed a novelty in measuring and testing the cultivation effect in the form of a comparison of traditional TV media exposure measures to the revised measures focusing on media exposure to content. Morgan et al. (2014) have long recognized update to the cultivation theory was needed, as how people consume media has become fundamentally different compared to the era in which the theory was coined by Gerbner. Genre-based media exposure measures were also widely utilized and tested (C.-j. Lee & Niederdeppe, 2011; Morgan & Shanahan, 2010). This dissertation took a new approach by going a step further from genre to content, and the result has shown the promising potential and relevancy of these changes. The CFA findings offer a compelling exhibition of the efficacy of these two different measurement models of cultivation. In the General TV Use model, despite estimates ranging from 0.84 to 1.00, the notably high error terms (ranging from 0.78 to 1.59) signal a substantial amount of variance left unexplained by the model. This is further accentuated by less-than-ideal fit indices: an RMSEA value of 0.16 far exceeding the acceptable upper limit, coupled with CFI and TLI 109 values (0.92 and 0.89, respectively) falling below the desired threshold for a good fit, and a considerably high Chi-squared value. These indicators collectively point to the model’s inadequacy in effectively capturing the nuances of general TV viewing habits. In stark contrast, the models for “Friends” and the Marvel Cinematic Universe (MCU) demonstrate a more precise fit. The lower error terms in these models (0.38 to 0.60 for “Friends” and 0.42 to 0.61 for MCU) and more favorable fit indices – RMSEAs at 0.11, and both CFI and TLI comfortably above 0.95, along with significantly lower Chi-squared values – suggest that they more accurately encapsulate the specific viewing patterns associated with these series. The multivariate analysis also provides additional justification to favor the content- specific media exposure measure over the general TV measure. When it comes to predicting perceived social reality, the regression analyses underscore the superior predictive power of content-specific media exposure measures over general TV measures when it comes to perceptions of meritocracy. Specifically, the “Friends” and MCU media exposure scales show a consistent and significant positive impact on the perceived importance of meritocratic elements. For example, the media exposure to the “Friends” variable in Table 5.1 exhibits a particularly strong influence with a coefficient of 6.58 (p<0.001), underscoring the salience of specific programming in shaping meritocratic beliefs. Likewise, the media exposure to the MCU variable from Table 5.2 presents a positive coefficient of 2.93 (p<0.05), further reinforcing the argument. These findings highlight that the cultivation effects from specific shows like “Friends” and the MCU are more pronounced and more directly correlated with viewers' meritocracy perceptions than the broader patterns of general television viewing. Finally, the SEM results provide evidence of this new content-based media exposure measure’s relevancy in predicting people’s beliefs about reality, although the effectiveness varies across demographic groups, revealing that 110 media impact is not uniform but differs based on the audience's race, gender, and social class. Therefore, the data clearly demonstrate that the tailored narratives and character-driven stories from these specific shows resonate more effectively with audience beliefs and attitudes toward meritocratic principles, rendering general TV media exposure measures much less impactful in this context. These dichotomies starkly highlight the diminishing relevancy of general TV viewing measures in capturing audience behaviors. This is consistent with nowadays media prevailing consumption behavior, switching from traditional TV to streaming services, where content drives subscription and viewership (Schauerte, Feiereisen, & Malter, 2021; Snyman & Gilliard, 2019). 6.2 Scales Validations The result of this dissertation reveals that RII backstories scales, as evaluated through confirmatory factor analysis, stand out as a methodologically robust and theoretically significant tool. The justification for factors loading together is grounded in the psychological process of imagination and perception. When audiences engage with character backstories, especially in contexts like "Friends" and the MCU, they do not perceive characters in isolation. Instead, their mental processes naturally encompass various aspects, such as race, gender, and socioeconomic status, to construct a more holistic and realistic understanding of the characters. This multidimensional perception suggests that viewers tend to integrate diverse aspects of characters to form a more comprehensive and relatable narrative. Therefore, the loading of these factors together within the RII character backstories construct is validated by the natural tendency of audiences to imagine and understand characters in a multifaceted way that resembles reality. The significance of RII scales’ reliability is paramount, as it ensures that each item within the scale cohesively contributes to measuring the intended construct (Reuterberg & Gustafsson, 1992). 111 The scales' capacity to distinctly evaluate different character backstories also points to strong discriminant and convergent validity (Cole, 1987), ensuring that each scale uniquely captures diverse aspects of audience engagement and attitudes. Such discriminant validity is crucial for ensuring that each construct is uniquely represented, while convergent validity confirms that multiple items targeting the same construct are in harmony in their measurement approach. The results also offer important confirmations of perceived meritocracy scales. Like the RII scales, these statistical indicators collectively affirm the model’s accuracy in capturing the latent structure of the data, underscoring strong construct validity (M. Young, 2017). The concept of meritocracy is fundamentally about the belief that success and advancement in society should be based on individual merit, typically measured in terms of talent, effort, and achievement. The factors of effort, education, and ambition are intrinsically linked within this definition. The effort is a direct expression of individual exertion towards goals; education is often viewed as a tool for developing one’s talents and abilities, and ambition reflects the drive to achieve and succeed. These elements are conceptually similar as they all emphasize personal qualities and actions as the basis for success, aligning with the core tenet of meritocracy which values individual achievement. This is in contrast to factors like family wealth, which represent success derived from external, non-individualistic sources. The inherent similarity and interconnectedness of effort, education, and ambition validate their grouping within the meritocratic elements construct, as they collectively represent the personal attributes and actions central to the meritocratic ideal. The validation of these factors as a coherent construct is based on prior research that has explored societal beliefs about success (Xian & Reynolds, 2017). The loading of these factors together validates the complexity of societal beliefs, encompassing a spectrum of views on what constitutes success. 112 Overall, the justification for the factors loading together within each latent construct is rooted in the validation of previous research. This approach not only reinforces the theoretical foundations of the constructs but also ensures that the measurement model aligns with established understandings in the fields of sociology, psychology, and media studies. The model, therefore, provides a nuanced and research-backed representation of the latent constructs, despite the challenges posed by the restriction of correlations amongst latent variables to 0. In essence, these CFA results lay a robust foundation for further research in this domain. Nevertheless, there should be vigilance against overfitting remains a key consideration, emphasizing the need for ongoing validation and testing of the model across different contexts to affirm its broader applicability and relevance. 6.3 NIUBE Outer Route Inspired by the resonating effect and TEBOTS, this dissertation attempted to advance the literature by proposing a novel theoretical model to account for the mechanism of how narrative and experience shape the perception of reality by conjoining RII and cultivation theory. In its essence, the NIUBE model recognizes two routes by which perception can be shaped. The Outer Routes represent the heuristic processing aspect in perception shaping – the direct influence of life experience and the cultivation effect. The Inner Routes essentially proximate the systematic processing aspect in perception shaping – the mediation role that RII played within the process of Outer Routes. To illustrate the potential of this new theory, this dissertation tests the model operation under perceived meritocracy under the context of “Friends” and MCU. The examination provides a rich tapestry of insights into the intricate ways media influences societal beliefs and structures. In general, the NIUBE model provides a comprehensive understanding of the model's applicability and effectiveness in explaining the influence of media on perceived 113 meritocracy. Both OLS regression and SEM results indicated that both Outer Routes underscore the powerful role of media narratives in shaping beliefs. This highlights the complexity of perception formation, necessitating a consideration of both media exposure and tangible stratification experiences. As discussed above, the findings provided support for the effectiveness of content-based media exposure measures in predicting the perception of reality. For instance, the significance of the direct effect of Media exposure on the perceived importance of meritocratic elements in both “Friends” and “MCU ” models highlights how specific narratives directly influence perceptions. This is evident in how increased content consumption shaped respondents’ beliefs about their social reality, directly linking narrative exposure to belief formation. Interestingly, the result showed that increased consumption of “Friends” and MCU would lead to enhanced beliefs in meritocratic elements, whereas consumption of MCU content would lead to increased perceived importance of non-meritocratic elements, which is reminiscent of what the underlying message about society that both franchises contained. “Friends” portrays a specific set of cultural norms and values, often emphasizing personal success and individual effort. For instance, Ross and Chandler are both economically better off compared to Phoebe, due to their higher education. This portrayal can subtly reinforce the idea that meritocratic factors (like hard work and talent) are crucial for success. MCU, through its storytelling and character development, can also influence viewers' perceptions of meritocratic values like hard work and talent, as well as non- meritocratic factors such as background, fate, and external resources. The superhero genre, central to the MCU, often emphasizes extraordinary abilities and heroic deeds, highlighting meritocratic values such as individual effort, courage, and exceptional skills (Mills, 2013; Tuzi, 2005). This can lead viewers to value personal excellence and exceptionalism. However, 114 characters like Iron Man and Black Panther show how access to advanced technology and wealth can be significant advantages (Kohen, 2022). This aspect of the MCU might lead viewers to consider the importance of resources and economic background, factors not necessarily tied to personal merit. Finally, some MCU narratives involve themes of destiny or fate, such as Thor's royal heritage or Doctor Strange's destined role as the Sorcerer Supreme (D. Johnson, 2012). These elements suggest that some successes are preordained or beyond personal control, emphasizing non-meritocratic factors. Furthermore, the intricacies of experience and social distance, as illuminated through nested OLS regression analysis within the NIUBE model, also reveal their profound and direct influence on the perception of societal structures and provide support for as another Outer Route within the NIUBE model. The direct impact of stratification experiences, encompassing diverse exposure to various groups of people, including the upper class and marginalized communities like BLM and Me Too victims, is pivotal in molding respondents’ perceptions. For instance, experiences with the upper class have shown a correlation with a heightened emphasis on merit- based success, suggesting that direct interactions with affluent groups might reinforce the belief in meritocratic systems, possibly influenced by observed success stories that emphasize self- made achievements. Conversely, social distance, especially from upper-class groups, demonstrates a notable relationship with perceptions of meritocracy. A greater social distance tends to correlate with a diminished belief in meritocratic principles, potentially stemming from limited exposure to diverse success narratives or an external perception of societal elites that underscores privilege over merit (Batruch, Autin, & Butera, 2017; Waller, Ingram, & Ward, 2017). The dynamics of social distance are inherently complex, and shaped by a multitude of factors including socioeconomic status, cultural background, and personal experiences (Akerlof, 115 1997; Kinloch, 1973; Koçak, 2021; Triandis & Triandis, 1960). Vice Versa can be said about the social distance from disadvantaged groups such as blacks and females, where the closed distance from them would indicate limited exposure to success stories and perceived privilege importance over merit. These dynamics are critical in understanding how individuals perceive and value different societal success factors, balancing between meritocratic and non-meritocratic elements. 6.4 NIUBE Inner Route The findings offer modest yet noteworthy insights into the NIUBE model's Inner Routes. While the study acknowledges the role of the RII as a factor within the NIUBE model, particularly concerning media exposure, this aspect underscores the interactive nature of audience engagement with media. It suggests that under certain conditions, such as ego threats or the need to fill experiential voids, people do not merely consume media passively but rather engage in a way that can shape their beliefs and perceptions. This notion of increased involvement indicates that as individuals become more immersed in the content, they may become more receptive to the narratives and ideologies it presents. However, the impact of RII, particularly in the creation of backstories that link fictional worlds to the real world, is presented with a degree of caution. While the study finds that these backstories tend to align with the narrative's promotion of certain ideologies, such as meritocracy or its alternatives, this effect is not overly emphasized. Instead, it is noted as one of several ways media content can influence audiences. Furthermore, the research suggests the influence of media representations is somewhat consistent across different demographics, including race, gender, and social class, hinting at a broad but not overwhelming impact of media on societal beliefs. This universal aspect indicates that while media's influence is far-reaching, the significance of the RII within 116 this process is balanced and integrated within a wider context of media engagement and audience interaction. The activation of inner routes, characterized by systematic processing, is more evident amongst “Friends” viewers than MCU fans. This difference might be attributed to the nature of the MCU’s content, which, being fantastical and presented in a high-intensity blockbuster format, might not facilitate the same depth of media exposure and reflective processing as "Friends." The direct influence of MCU narratives on viewers' social perceptions suggests a less nuanced engagement with the content, possibly due to the less relatable nature of the narratives compared to the everyday situations depicted in "Friends." “Friends” has its touches on the characters' backgrounds, which vary in terms of economic and social status (Angelia & Soelistyo, 2022). This diversity, albeit not deeply explored, might influence viewers to consider how these backgrounds can impact one's opportunities and successes, pointing to non- meritocratic aspects of life (Sink & Mastro, 2017). This can reinforce the idea that external, uncontrollable factors play a crucial role in life's outcomes, alongside merit and hard work. Finally, “Friends” prominently features the benefits and influence of having a supportive social network (Chiou & Lee, 2008). The characters often rely on each other for opportunities, advice, and help. This can subtly suggest to viewers that social connections and relationships are significant in achieving success, emphasizing the role of non-meritocratic factors. This processing can occur when viewers engage deeply with this aspect of “Friends”, challenging their dominant ideology and forming a “dual consciousness” (Matthew O. Hunt & Wilson, 2011). The study reveals that media exposure to content significantly influences viewers' perceptions of meritocratic (i.e., dominant) and non-meritocratic (i.e., challenging) elements (Huber & Form, 1973; James R. Kluegel & Smith, 1986), with this influence mediated by RII 117 engagement. Such mediation suggests a reflective and critical engagement with the narrative, indicative of inner route activation. However, this activation varies based on demographic factors like race and gender, underscoring the influence of power dynamics. Women, as shown in the gender moderation analysis, are more inclined towards systematic processing in forming both meritocratic and non-meritcratic beliefs, indicating a though critical interrogation of all social narratives. This might be a response to the longstanding and persistent gender-based barriers they encounter (DiTomaso, Post, & Parks-Yancy, 2007; Newman et al., 2023; Parcheta, Kaifi, & Khanfar, 2013), suggesting a cognitive countermeasure to the structural power differentials. On the other hand, men, typically in a position of social advantage, tend to rely on heuristic processing, aligning with and affirming the existing social order that favors them (Libby & Rennekamp, 2012). Minority viewers heuristically process information related to the changing ideology of non-meritocratic elements, possibly due to a more immediate recognition of social realities that contrast with meritocratic ideals (A. A. Young, 2006). In contrast, white viewers, representing the dominant group, engage in more complex systematic processing via RII when it comes to this challenging ideology, potentially reflecting a deeper cognitive engagement necessitated by narratives that threaten their more secure social position (Ryan & Deci, 2017). In addition to the impact of race and gender on narrative processing in the "Friends" dataset, the dissertation also delves into how social class moderates the activation of inner routes, revealing distinct patterns between lower-class and upper-class respondents. This aspect of the analysis further underscores the influence of power dynamics in narrative engagement and processing. For lower-class respondents, the engagement with narratives in "Friends" showed a tendency toward heuristic processing of meritocratic elements. This pattern may reflect a resignation or conditioned acceptance of the dominant ideology of meritocracy. It suggests that 118 lower-class viewers might internalize the meritocratic narrative as a given reality as it was forced upon them structurally (Huber & Form, 1973; James R. Kluegel & Smith, 1986). However, when it comes to non-meritocratic elements, which are more directly relevant to their experiences of social mobility (or lack thereof), lower-class viewers engage in more systematic processing. This shift indicates a critical examination of the structural barriers and societal factors that might impede their social advancement, reflecting an inner route activation that seeks to reconcile the meritocratic promise with their lived reality of systemic constraints (Sethi et al., 2022). However, the result provided no support for RII’s mediation role for the path originating from social distance, whereas the results presented only sporadic support for the direct effects of the social distance measure without revealing any clear pattern. The lack of findings in all SEM models could indicate one of two issues, either social distance does not adequately measure the experience as mandated by the model, or the NIUBE model failed to predict experience would trigger RII. As such, further research should test the model again with more direct measures for experience to eliminate Type II errors rooted in measurement. Furthermore, as the RII measures were found effective and reliable in this research, additional revision is also required to better test the NIUBE model. The RII measures as of now only measure whether respondents engage in RII, whereas it would be crucial to learn about what kind of RII they are engaging. For example with the backstories under the examination of meritocracy in the current study, it would be interesting to know what backstories the respondents constructed for these characters. With only this information, we can inquire further whether these backstories are fortifying, weakening, or overturning the connection between the fictional worlds and their real worlds. In conclusion, this dissertation makes significant contributions to the field by empirically testing and partially validating the NIUBE model, which bridges cultivation theory and the 119 psychological processes behind media influence. The study's rigorous approach in applying nested ordinary least squares regression and structural equation modeling offers a nuanced understanding of how media narratives like "Friends" and the MCU shape perceptions of societal structures. By integrating Self-Determination Theory and Cultivation Theory through the operation of RII, this research provides a comprehensive framework for examining how individuals engage with media narratives in the context of their experiences, especially in understanding stratification systems. The findings underscore the complexity of belief formation, showing how media content and personal experiences converge to shape perceptions, influenced by factors such as race, gender, and social class. Importantly, the dissertation highlights the power dynamics at play in narrative processing, revealing how systematic and heuristic processing varies across different demographic groups, and how these processes are influenced by the viewers' position within the social hierarchy. This research not only validates existing scales and theories but also offers fresh insights into the evolving media landscape, emphasizing the need for ongoing adaptation and testing of theoretical models in diverse contexts. The NIUBE model, with its dual pathways of Outer and Inner Routes, thus stands as a significant contribution to the understanding of media effects, providing a robust platform for future explorations in the field. 120 BIBLIOGRAPHY Akerlof, G. A. (1997). 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The rise of the meritocracy: Routledge. 131 APPENDIX A: TABLES Table 12: Correlation Matrix for Combined Dataset 18 9 8 7 6 5 4 3 2 17 16 15 14 13 12 11 10 1 1 M1 1 2 M2 0.49 1 3 M3 0.51 0.43 1 4 N1 0.08 0.24 0.11 1 5 N2 0.31 0.39 0.34 0.28 1 6 N3 0.14 0.20 0.17 0.34 0.27 1 7 N4 0.03 0.13 0.10 0.33 0.14 0.23 1 8 N5 0.24 0.25 0.20 0.38 0.29 0.31 0.25 1 9 N6 0.22 0.24 0.22 0.41 0.30 0.29 0.39 0.56 1 10 N7 0.27 0.29 0.27 0.38 0.29 0.33 0.40 0.55 0.58 1 11 T1 0.37 0.31 0.32 0.12 0.24 0.23 0.25 0.27 0.35 0.36 1 12 T2 0.36 0.30 0.28 0.09 0.26 0.21 0.14 0.26 0.27 0.31 0.75 1 13 T3 0.34 0.32 0.25 0.09 0.23 0.18 0.10 0.24 0.26 0.31 0.61 0.66 1 14 T4 0.29 0.27 0.20 0.09 0.21 0.21 0.07 0.23 0.24 0.26 0.53 0.57 0.65 1 15 T5 0.38 0.29 0.28 0.10 0.26 0.21 0.17 0.27 0.30 0.33 0.66 0.68 0.68 0.58 1 16 T6 0.35 0.33 0.28 0.12 0.27 0.21 0.12 0.27 0.24 0.32 0.55 0.63 0.70 0.68 0.69 1 17 T7 0.38 0.31 0.30 0.12 0.25 0.19 0.20 0.27 0.28 0.32 0.67 0.67 0.68 0.58 0.78 0.67 1 18 T8 0.34 0.34 0.21 0.12 0.21 0.21 0.09 0.20 0.25 0.28 0.55 0.60 0.68 0.71 0.67 0.77 0.68 1 Note. N = 661. * p <0.05 132 Table 13: Correlation Matrix for Friends Dataset 8 5 6 7 4 3 2 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 327. * p <0.05 1 1 0.52 1 0.55 0.45 1 0.19 0.28 0.13 1 0.40 0.36 0.37 0.28 0.18 0.19 0.17 0.28 0.04 0.13 0.14 0.30 0.33 0.30 0.22 0.39 0.26 0.28 0.22 0.42 0.33 0.29 0.22 0.41 0.38 0.30 0.38 0.17 0.37 0.28 0.36 0.10 0.46 0.38 0.39 0.21 0.40 0.31 0.33 0.16 0.48 0.34 0.42 0.16 0.42 0.37 0.39 0.13 0.46 0.35 0.42 0.15 0.44 0.35 0.37 0.18 0.39 0.33 0.40 0.19 0.39 0.30 0.36 0.18 0.38 0.32 0.35 0.19 0.38 0.33 0.37 0.23 0.40 0.35 0.33 0.18 0.36 0.32 0.34 0.17 0.37 0.34 0.40 0.21 0.33 0.32 0.37 0.18 0.44 0.36 0.38 0.20 0.44 0.35 0.38 0.19 0.41 0.38 0.40 0.23 0.43 0.37 0.43 0.21 0.07 0.07 0.16 -0.01 0.11 0.07 0.15 -0.02 0.06 0.04 0.08 0.15 9 10 1 1 0.57 0.35 0.35 0.28 0.29 0.34 0.34 0.32 0.31 0.31 0.28 0.27 0.28 0.28 0.27 0.29 0.25 0.30 0.29 0.31 0.30 0.33 0.30 0.34 0.32 0.36 0.30 0.35 0.33 0.31 0.32 0.29 0.30 0.36 0.31 0.36 0.33 0.35 0.33 0.36 0.34 -0.02 0.01 0.01 0.03 0.09 0.07 1 0.30 0.15 0.30 0.31 0.31 0.27 0.29 0.29 0.25 0.26 0.27 0.29 0.23 0.31 0.32 0.28 0.31 0.33 0.32 0.36 0.40 0.36 0.38 0.33 0.33 -0.02 -0.03 0.06 1 1 0.22 0.26 1 0.26 0.32 0.58 0.28 0.40 0.52 0.36 0.36 0.35 0.24 0.26 0.22 0.19 0.23 0.33 0.23 0.25 0.26 0.27 0.25 0.25 0.22 0.20 0.28 0.18 0.25 0.25 0.20 0.24 0.24 0.22 0.24 0.25 0.25 0.22 0.28 0.22 0.24 0.30 0.24 0.26 0.28 0.24 0.16 0.31 0.25 0.18 0.28 0.21 0.18 0.27 0.21 0.18 0.23 0.20 0.25 0.32 0.20 0.27 0.29 0.23 0.28 0.33 0.22 0.28 0.29 0.22 -0.04 0.11 -0.01 -0.02 0.01 -0.03 0.09 0.16 0.16 133 11 12 Table 13 (cont’d) 13 14 15 16 17 18 19 20 21 M1 1 M2 2 M3 3 N1 4 N2 5 N3 6 N4 7 N5 8 N6 9 N7 10 T1 11 T2 12 T3 13 T4 14 T5 15 T6 16 T7 17 T8 18 B1 19 B2 20 B3 21 B4 22 F1 23 F2 24 F3 25 F4 26 W1 27 W2 28 W3 29 W4 30 SocDisBla 31 SocialDisFem 32 SocDisUpp 33 Note. N = 327. * p <0.05 1 0.76 1 0.73 0.73 1 0.70 0.66 0.70 1 0.79 0.74 0.73 0.67 1 0.75 0.73 0.74 0.73 0.79 1 0.77 0.75 0.72 0.70 0.83 0.76 1 0.71 0.71 0.68 0.77 0.76 0.81 0.79 1 0.67 0.59 0.56 0.58 0.60 0.60 0.61 0.59 1 0.66 0.61 0.57 0.57 0.58 0.62 0.62 0.61 0.80 1 0.67 0.59 0.59 0.61 0.59 0.60 0.59 0.59 0.82 0.81 1 0.68 0.62 0.60 0.59 0.60 0.62 0.63 0.61 0.84 0.82 0.84 0.61 0.56 0.55 0.54 0.55 0.58 0.54 0.55 0.71 0.73 0.76 0.64 0.58 0.59 0.59 0.59 0.60 0.58 0.55 0.76 0.73 0.78 0.60 0.57 0.54 0.57 0.54 0.60 0.57 0.58 0.74 0.76 0.74 0.61 0.61 0.56 0.57 0.53 0.58 0.56 0.56 0.73 0.73 0.75 0.67 0.59 0.61 0.62 0.63 0.65 0.63 0.62 0.75 0.70 0.75 0.70 0.64 0.65 0.61 0.66 0.65 0.64 0.63 0.74 0.70 0.74 0.71 0.63 0.63 0.64 0.65 0.69 0.66 0.64 0.74 0.74 0.75 0.69 0.64 0.64 0.66 0.67 0.67 0.67 0.64 0.76 0.75 0.76 0.31 0.22 0.20 0.21 0.27 0.28 0.25 0.26 0.16 0.17 0.19 0.25 0.24 0.24 0.25 0.25 0.23 0.27 0.24 0.10 0.09 0.10 0.21 0.10 0.12 0.10 0.23 0.13 0.21 0.17 0.13 0.19 0.18 134 22 23 24 Table 13 (cont’d) 27 26 25 28 29 30 31 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem 0.09 0.08 0.08 0.12 0.14 0.17 0.17 0.15 0.16 0.46 1 33 Note. N = 327. * p <0.05 1 0.75 1 0.76 0.81 1 0.75 0.78 0.80 1 0.79 0.78 0.79 0.80 1 0.76 0.74 0.76 0.72 0.75 1 0.75 0.71 0.74 0.72 0.73 0.82 1 0.78 0.74 0.76 0.76 0.76 0.84 0.83 1 0.78 0.73 0.77 0.75 0.75 0.83 0.80 0.83 1 0.23 0.17 0.16 0.25 0.21 0.23 0.25 0.22 0.22 1 SocDisUpp 0.15 0.17 0.16 0.15 0.14 0.13 0.12 0.11 0.12 0.30 0.27 1 135 Table 14: Correlation Matrix for MCU Dataset 8 7 6 5 4 3 2 1 1.00 M1 1 1.00 0.46 M2 2 0.48 0.40 1.00 M3 3 -0.03 0.19 0.09 1.00 N1 4 1.00 0.42 0.32 0.28 0.21 N2 5 0.24 1.00 0.20 0.16 0.40 0.10 N3 6 0.14 0.23 1.00 0.12 0.06 0.36 0.02 N4 7 0.28 0.35 0.25 1.00 0.21 0.19 0.38 0.14 N5 8 0.29 0.30 0.46 0.54 0.20 0.22 0.40 0.17 N6 9 0.28 0.30 0.39 0.57 0.29 0.30 0.36 0.22 N7 10 0.30 0.24 0.34 0.25 0.29 0.35 0.08 0.37 T1 11 0.29 0.25 0.23 0.18 0.31 0.32 0.04 0.40 T2 12 0.27 0.22 0.25 0.18 0.34 0.26 0.14 0.38 T3 13 0.31 0.23 0.28 0.23 0.35 0.31 0.08 0.34 T4 14 0.33 0.29 0.30 0.22 0.38 0.36 0.14 0.41 T5 15 0.25 0.21 0.24 0.16 0.35 0.30 0.04 0.44 T6 16 0.26 0.22 0.32 0.23 0.37 0.31 0.13 0.41 T7 17 0.33 0.19 0.32 0.18 0.41 0.29 0.07 0.40 T8 18 0.33 0.11 0.16 0.28 0.29 0.31 0.08 0.32 B1 19 0.31 0.19 0.17 0.27 0.30 0.31 0.10 0.34 B2 20 0.34 0.15 0.17 0.24 0.26 0.39 0.08 0.36 B3 21 0.33 0.15 0.15 0.26 0.31 0.34 0.16 0.33 B4 22 0.32 0.09 0.12 0.30 0.33 0.29 0.07 0.36 F1 23 0.31 0.14 0.14 0.33 0.30 0.31 0.06 0.37 F2 24 0.34 0.17 0.15 0.32 0.31 0.35 0.08 0.34 F3 25 0.37 0.16 0.14 0.34 0.34 0.35 0.11 0.38 F4 26 0.31 0.19 0.22 0.25 0.33 0.35 0.08 0.40 W1 27 0.31 0.12 0.18 0.25 0.35 0.39 0.04 0.43 W2 28 0.29 0.18 0.20 0.24 0.33 0.35 0.07 0.39 W3 29 0.27 0.12 0.17 0.27 0.28 0.37 0.05 0.36 W4 30 0.17 0.15 -0.03 0.07 0.09 0.11 -0.03 31 0.25 SocDisBla 0.11 0.06 0.12 0.02 0.17 0.14 0.07 32 SocialDisFem 0.18 0.13 0.03 0.08 0.07 0.07 0.08 0.04 0.04 SocDisUpp 33 Note. N = 334. * p <0.05 9 10 1.00 1.00 0.59 0.42 0.39 0.34 0.25 0.32 0.29 0.37 0.30 0.41 0.35 0.34 0.27 0.36 0.35 0.34 0.30 0.34 0.31 0.32 0.32 0.31 0.32 0.36 0.29 0.36 0.30 0.35 0.30 0.37 0.30 0.35 0.31 0.37 0.31 0.33 0.28 0.36 0.28 0.31 0.28 -0.02 0.05 0.06 0.00 0.07 0.02 136 Table 14 (cont’d) 11 12 13 14 15 16 17 18 19 20 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 334. * p <0.05 1.00 0.74 1.00 0.63 0.68 1.00 0.69 0.62 0.66 1.00 0.76 0.72 0.65 0.68 1.00 0.64 0.68 0.67 0.72 0.72 1.00 0.75 0.72 0.67 0.62 0.75 0.68 1.00 0.66 0.70 0.71 0.74 0.70 0.73 0.73 1.00 0.55 0.57 0.49 0.47 0.54 0.51 0.55 0.51 1.00 0.56 0.57 0.50 0.50 0.57 0.49 0.54 0.50 0.79 1.00 0.54 0.56 0.50 0.52 0.58 0.50 0.55 0.50 0.77 0.80 0.56 0.57 0.49 0.51 0.55 0.52 0.51 0.54 0.77 0.79 0.54 0.54 0.47 0.47 0.50 0.49 0.51 0.50 0.73 0.75 0.57 0.54 0.49 0.52 0.52 0.51 0.51 0.50 0.75 0.77 0.55 0.55 0.47 0.51 0.54 0.52 0.53 0.51 0.78 0.80 0.51 0.53 0.48 0.49 0.52 0.51 0.53 0.49 0.76 0.76 0.63 0.62 0.56 0.58 0.61 0.55 0.58 0.60 0.67 0.72 0.63 0.65 0.58 0.57 0.61 0.61 0.60 0.60 0.69 0.71 0.64 0.61 0.55 0.57 0.59 0.56 0.62 0.60 0.69 0.71 0.65 0.57 0.56 0.55 0.57 0.52 0.58 0.59 0.70 0.70 0.30 0.25 0.21 0.25 0.26 0.26 0.24 0.24 0.13 0.16 0.27 0.25 0.23 0.25 0.30 0.21 0.30 0.27 0.15 0.20 0.16 0.16 0.15 0.17 0.15 0.14 0.17 0.16 0.19 0.23 137 Table 14 (cont’d) 21 22 23 24 25 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 334. * p <0.05 1.00 0.79 1.00 0.72 0.77 1.00 0.74 0.73 0.78 1.00 0.77 0.78 0.81 0.78 1.00 0.77 0.76 0.80 0.79 0.85 1.00 0.68 0.71 0.73 0.73 0.74 0.71 1.00 0.70 0.71 0.68 0.70 0.71 0.74 0.79 1.00 0.71 0.73 0.70 0.71 0.73 0.74 0.81 0.78 1.00 0.69 0.68 0.71 0.69 0.74 0.70 0.80 0.79 0.78 0.12 0.16 0.15 0.14 0.15 0.10 0.23 0.23 0.20 0.17 0.20 0.14 0.13 0.16 0.13 0.25 0.19 0.26 0.21 0.18 0.17 0.19 0.16 0.17 0.20 0.20 0.17 138 Table 14 (cont’d) 31 30 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 334. * p <0.05 1.00 0.22 1.00 0.19 0.54 1.00 0.15 0.30 0.32 1.00 139 Table 15.1: Correlation Matrix for Friends Minority Respondents 1 2 3 4 5 6 7 8 9 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1.00 1 0.51 2 0.63 3 0.09 4 0.51 5 0.20 6 0.05 7 0.30 8 0.46 9 0.41 10 0.07 11 0.17 12 0.36 13 0.40 14 0.31 15 0.24 16 0.28 17 0.37 18 0.28 19 0.12 20 0.15 21 0.20 22 0.25 23 0.21 24 0.28 25 0.19 26 0.24 27 0.29 28 0.27 29 0.33 30 31 -0.13 32 SocialDisFem -0.05 -0.15 SocDisUpp 33 Note. N = 51. * p <0.05 1.00 0.60 0.33 0.61 0.47 0.18 0.35 0.42 0.36 0.09 0.06 0.15 0.10 0.20 0.14 0.17 0.25 0.18 0.14 0.10 0.08 0.27 0.13 0.25 0.15 0.07 0.06 0.03 0.08 -0.29 0.01 -0.08 1.00 0.22 0.51 0.27 0.14 0.10 0.37 0.14 0.06 0.14 0.21 0.09 0.27 0.07 0.13 0.04 0.18 0.06 0.13 0.11 0.17 0.13 0.23 0.16 0.13 0.26 0.19 0.19 -0.08 0.02 -0.17 1.00 1.00 0.28 1.00 0.36 0.42 1.00 0.33 0.22 0.46 1.00 0.17 0.31 0.43 0.14 0.55 0.13 0.13 0.42 0.23 0.48 0.30 0.29 0.19 0.26 0.27 -0.01 0.44 -0.02 0.00 0.24 0.30 -0.06 0.03 0.04 0.33 0.29 0.01 0.15 0.10 0.27 0.34 0.12 0.09 0.19 0.16 -0.02 0.28 0.00 0.10 0.35 -0.02 0.12 -0.03 0.00 0.29 -0.03 0.28 0.14 0.03 0.23 0.19 0.08 0.13 0.10 0.23 0.21 0.00 0.23 0.16 0.23 0.16 0.04 0.10 0.13 0.16 0.30 0.03 0.02 0.22 0.18 0.19 0.00 0.14 0.22 0.34 0.12 0.11 0.05 0.20 0.24 0.05 0.09 -0.03 0.05 0.06 0.15 0.20 0.09 0.29 -0.01 0.20 0.07 0.10 0.16 0.10 -0.03 0.11 0.14 0.04 0.06 -0.09 0.17 -0.05 0.11 0.09 0.24 0.00 0.02 0.07 0.07 0.18 0.05 0.11 0.07 -0.10 -0.13 -0.31 -0.17 -0.22 -0.19 -0.12 -0.17 -0.05 -0.11 0.25 -0.01 0.08 -0.00 0.09 1.00 0.44 0.11 0.25 0.40 0.17 0.26 0.17 0.25 0.13 0.19 0.11 0.10 0.12 0.22 0.18 0.25 0.22 0.09 0.20 0.10 0.17 -0.22 -0.20 -0.06 140 Table 15.1 (cont’d) 10 11 12 13 14 15 16 17 18 19 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 51. * p <0.05 1.00 1.00 0.38 0.78 1.00 0.29 0.67 0.75 0.38 0.57 0.54 0.37 0.72 0.80 0.17 0.81 0.73 0.29 0.70 0.78 0.26 0.63 0.60 0.41 0.47 0.43 0.31 0.46 0.40 0.37 0.59 0.49 0.31 0.45 0.43 0.34 0.55 0.50 0.43 0.50 0.52 0.34 0.43 0.50 0.37 0.37 0.44 0.23 0.57 0.43 0.23 0.57 0.49 0.18 0.66 0.52 0.27 0.51 0.44 0.29 -0.10 0.31 0.24 -0.22 0.13 0.18 0.05 -0.02 0.02 1.00 0.55 1.00 0.56 0.79 1.00 0.54 0.80 0.72 1.00 0.77 0.66 0.67 0.75 1.00 0.32 0.37 0.44 0.36 0.37 1.00 0.15 0.21 0.34 0.30 0.32 0.88 0.39 0.38 0.47 0.36 0.44 0.88 0.29 0.28 0.40 0.36 0.38 0.94 0.32 0.34 0.49 0.44 0.48 0.71 0.35 0.39 0.48 0.40 0.48 0.78 0.30 0.37 0.41 0.37 0.47 0.74 0.18 0.27 0.39 0.37 0.35 0.71 0.36 0.42 0.56 0.41 0.42 0.76 0.30 0.46 0.47 0.38 0.29 0.72 0.41 0.48 0.58 0.44 0.44 0.75 0.43 0.44 0.50 0.39 0.44 0.79 0.12 0.07 0.19 0.15 0.06 0.08 0.14 0.20 0.06 0.27 0.21 -0.26 0.05 0.02 0.01 0.06 0.15 0.01 1.00 0.68 0.71 0.72 0.71 0.56 0.40 0.23 0.34 0.34 0.39 0.40 0.35 0.38 0.47 0.51 0.46 0.50 0.19 0.07 -0.04 141 20 21 Table 15.1 (cont’d) 24 23 22 25 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 1.00 20 0.82 21 0.87 22 0.76 23 0.75 24 0.74 25 0.71 26 0.69 27 0.64 28 0.71 29 0.69 30 31 0.09 32 SocialDisFem -0.31 0.05 SocDisUpp 33 Note. N = 51. * p <0.05 1.00 0.89 0.75 0.79 0.74 0.70 0.72 0.68 0.78 0.75 0.11 -0.17 0.03 1.00 0.72 0.79 0.74 0.76 0.71 0.66 0.72 0.74 0.10 -0.25 0.01 1.00 0.83 0.89 0.81 0.70 0.67 0.72 0.63 0.07 -0.16 0.00 1.00 0.87 0.84 0.73 0.68 0.71 0.77 0.07 -0.14 0.04 1.00 0.85 0.67 0.69 0.68 0.65 0.06 -0.18 0.13 1.00 0.75 0.65 0.65 0.71 0.13 -0.20 0.02 1.00 0.85 0.87 0.89 0.22 -0.22 -0.05 1.00 0.90 0.81 0.30 -0.19 -0.14 1.00 0.86 0.26 -0.17 -0.15 142 Table 15.1 (cont’d) 31 30 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 51. * p <0.05 1.00 0.11 1.00 -0.21 0.34 1.00 -0.06 0.07 0.31 1.00 143 Table 15.2: Correlation Matrix for Friends White Respondents 4 7 6 8 3 2 5 9 10 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 1.00 0.51 1.00 0.52 0.41 1.00 0.21 0.28 0.12 1.00 0.37 0.30 0.33 0.28 1.00 1.00 0.18 0.13 0.16 0.26 0.30 0.20 1.00 0.03 0.12 0.13 0.28 0.12 0.25 0.27 1.00 0.33 0.29 0.24 0.43 0.27 0.31 0.35 0.58 0.21 0.25 0.19 0.45 0.28 0.39 0.42 0.53 0.30 0.27 0.22 0.44 0.32 0.31 0.34 0.36 0.43 0.35 0.42 0.20 0.31 0.25 0.23 0.21 0.40 0.32 0.38 0.11 0.34 0.29 0.20 0.32 0.48 0.43 0.40 0.23 0.30 0.32 0.22 0.25 0.40 0.35 0.35 0.15 0.26 0.29 0.23 0.26 0.51 0.36 0.43 0.19 0.27 0.24 0.19 0.26 0.45 0.42 0.44 0.16 0.31 0.26 0.23 0.24 0.48 0.38 0.45 0.18 0.31 0.25 0.24 0.24 0.45 0.37 0.41 0.19 0.24 0.30 0.24 0.25 0.41 0.37 0.44 0.19 0.32 0.27 0.21 0.28 0.44 0.34 0.41 0.19 0.35 0.30 0.22 0.33 0.42 0.37 0.39 0.19 0.33 0.30 0.26 0.29 0.42 0.38 0.40 0.23 0.34 0.29 0.16 0.30 0.42 0.36 0.36 0.21 0.35 0.25 0.20 0.29 0.38 0.36 0.37 0.22 0.37 0.23 0.20 0.26 0.38 0.35 0.43 0.23 0.38 0.24 0.20 0.23 0.35 0.36 0.40 0.20 0.44 0.25 0.26 0.35 0.48 0.43 0.42 0.23 0.39 0.31 0.27 0.32 0.46 0.41 0.39 0.23 0.42 0.28 0.27 0.36 0.43 0.46 0.43 0.26 0.38 0.26 0.28 0.32 0.45 0.44 0.47 0.24 0.36 0.10 0.15 0.19 0.03 -0.00 0.02 0.15 0.00 1 2 3 4 5 6 7 8 1.00 9 0.60 1.00 10 0.39 0.32 11 0.30 0.24 12 0.33 0.31 13 0.34 0.29 14 0.29 0.31 15 0.30 0.24 16 0.27 0.25 17 0.26 0.25 18 0.31 0.29 19 0.33 0.27 20 0.34 0.31 21 0.35 0.32 22 0.31 0.33 23 0.36 0.34 24 0.33 0.28 25 0.31 0.28 26 0.34 0.37 27 0.35 0.37 28 0.37 0.35 29 0.37 0.36 30 31 0.01 0.02 32 SocialDisFem 0.14 0.08 0.16 0.00 -0.01 0.00 0.01 -0.01 0.07 0.04 0.10 0.11 SocDisUpp 33 Note. N = 276. * p <0.05 0.11 0.07 0.13 0.18 0.05 0.20 0.09 0.14 144 11 12 Table 15.2 (cont’d) 14 15 13 16 17 18 19 20 21 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 276. * p <0.05 1.00 0.74 1.00 0.72 0.70 1.00 0.71 0.67 0.69 1.00 0.79 0.71 0.72 0.67 1.00 0.73 0.72 0.73 0.75 0.78 1.00 0.76 0.73 0.69 0.71 0.83 0.76 1.00 0.71 0.71 0.68 0.76 0.77 0.83 0.78 1.00 0.70 0.62 0.58 0.62 0.63 0.62 0.65 0.62 1.00 0.68 0.63 0.61 0.63 0.63 0.66 0.66 0.65 0.78 1.00 0.68 0.60 0.63 0.64 0.62 0.63 0.62 0.61 0.80 0.80 1.00 0.70 0.64 0.63 0.63 0.64 0.65 0.67 0.64 0.82 0.81 0.82 0.62 0.57 0.58 0.58 0.58 0.59 0.55 0.55 0.71 0.72 0.76 0.65 0.58 0.61 0.62 0.61 0.61 0.60 0.56 0.75 0.72 0.77 0.62 0.58 0.56 0.61 0.56 0.63 0.60 0.60 0.73 0.76 0.73 0.63 0.62 0.58 0.62 0.55 0.60 0.58 0.58 0.72 0.72 0.75 0.67 0.61 0.62 0.65 0.65 0.66 0.65 0.64 0.74 0.70 0.75 0.70 0.64 0.65 0.64 0.68 0.67 0.67 0.67 0.74 0.70 0.74 0.71 0.63 0.65 0.67 0.66 0.70 0.68 0.66 0.73 0.74 0.74 0.71 0.66 0.66 0.68 0.71 0.69 0.71 0.67 0.75 0.75 0.76 0.30 0.20 0.19 0.22 0.29 0.28 0.26 0.28 0.17 0.18 0.20 0.26 0.25 0.26 0.26 0.25 0.25 0.27 0.24 0.16 0.15 0.15 0.25 0.13 0.15 0.11 0.27 0.15 0.24 0.17 0.15 0.22 0.22 145 Table 15.2 (cont’d) 25 23 24 22 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 276. * p <0.05 1.00 0.75 1.00 0.75 0.80 1.00 0.75 0.76 0.78 1.00 0.78 0.77 0.77 0.79 1.00 0.76 0.74 0.76 0.73 0.75 1.00 0.75 0.71 0.75 0.72 0.74 0.81 1.00 0.79 0.74 0.76 0.77 0.78 0.83 0.81 1.00 0.78 0.74 0.76 0.77 0.75 0.81 0.80 0.82 0.25 0.19 0.17 0.28 0.22 0.22 0.23 0.20 0.15 0.12 0.12 0.17 0.20 0.23 0.22 0.20 0.18 0.20 0.18 0.15 0.17 0.17 0.18 0.17 146 Table 15.2 (cont’d) 31 30 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 276. * p <0.05 1.00 0.23 1.00 0.22 0.47 1.00 0.15 0.34 0.26 1.00 147 Table 16.1: Correlation Matrix for Friends Female Respondents 1 1.00 M1 1 0.47 M2 2 0.60 M3 3 0.10 N1 4 0.38 N2 5 0.10 N3 6 0.09 N4 7 0.19 N5 8 0.06 N6 9 0.23 N7 10 0.36 T1 11 0.36 T2 12 0.41 T3 13 0.36 T4 14 0.41 T5 15 0.42 T6 16 0.39 T7 17 0.40 T8 18 0.33 B1 19 0.34 B2 20 0.37 B3 21 0.35 B4 22 0.37 F1 23 0.31 F2 24 0.37 F3 25 0.30 F4 26 0.40 W1 27 0.38 W2 28 0.35 W3 29 0.41 W4 30 31 0.20 SocDisBla 32 SocialDisFem 0.07 -0.04 SocDisUpp 33 Note. N = 171 * p <0.05 2 3 4 5 6 7 8 9 10 1.00 0.31 0.21 0.25 0.29 0.30 0.22 0.21 0.28 0.26 0.22 0.26 0.20 0.20 0.30 0.28 0.33 0.30 0.39 0.35 0.33 0.42 0.40 0.38 0.33 0.35 0.02 -0.07 0.04 1.00 0.28 0.23 0.30 0.37 0.27 0.22 0.20 0.21 0.20 0.20 0.16 0.19 0.25 0.25 0.21 0.27 0.23 0.19 0.18 0.22 0.19 0.25 0.20 0.23 0.03 -0.00 0.17 1.00 0.23 0.30 0.47 0.52 0.41 0.31 0.36 0.39 0.30 0.42 0.35 0.35 0.37 0.35 0.37 0.27 0.27 0.28 0.33 0.34 0.42 0.44 0.39 0.09 -0.01 0.10 1.00 0.50 0.47 0.18 0.09 0.13 0.11 0.07 0.13 0.07 0.08 0.07 0.14 0.19 0.13 0.19 0.20 0.23 0.13 0.17 0.16 0.15 0.15 -0.00 -0.11 0.08 1.00 0.50 0.25 0.23 0.21 0.19 0.17 0.19 0.15 0.11 0.16 0.16 0.21 0.20 0.19 0.24 0.24 0.18 0.16 0.21 0.17 0.21 -0.06 -0.00 0.04 1.00 0.31 0.25 0.31 0.23 0.23 0.26 0.22 0.22 0.21 0.24 0.28 0.29 0.29 0.31 0.24 0.21 0.26 0.35 0.31 0.31 -0.01 -0.07 0.01 1.00 0.43 0.22 0.37 0.19 0.08 0.26 0.23 0.24 0.23 0.29 0.35 0.33 0.27 0.36 0.28 0.28 0.31 0.28 0.34 0.34 0.35 0.35 0.39 0.34 0.34 0.36 0.37 0.37 0.16 0.10 -0.05 1.00 0.08 1.00 0.35 0.35 0.16 0.29 0.22 0.31 0.11 0.29 0.11 0.36 0.18 0.35 0.43 0.16 0.43 0.09 0.38 0.18 0.32 0.15 0.43 0.09 0.41 0.07 0.42 0.09 0.38 0.14 0.41 0.18 0.37 0.23 0.42 0.22 0.41 0.24 0.35 0.16 0.33 0.17 0.42 0.27 0.38 0.18 0.40 0.22 0.43 0.20 0.42 0.23 0.46 0.20 0.27 0.10 0.20 -0.11 0.05 0.15 148 11 12 Table 16.1 (cont’d) 13 15 14 16 17 18 19 20 21 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 171 * p <0.05 1.00 0.78 1.00 0.72 0.73 1.00 0.71 0.65 0.69 1.00 0.80 0.76 0.73 0.65 1.00 0.74 0.75 0.74 0.74 0.79 1.00 0.80 0.79 0.70 0.67 0.85 0.76 1.00 0.71 0.72 0.65 0.75 0.76 0.81 0.78 1.00 0.62 0.53 0.44 0.51 0.49 0.54 0.53 0.51 1.00 0.63 0.56 0.49 0.51 0.52 0.54 0.54 0.54 0.83 1.00 0.63 0.54 0.53 0.55 0.51 0.56 0.55 0.53 0.83 0.82 1.00 0.63 0.57 0.53 0.52 0.54 0.57 0.57 0.55 0.86 0.84 0.86 0.55 0.52 0.46 0.48 0.47 0.54 0.49 0.49 0.69 0.71 0.76 0.56 0.53 0.51 0.50 0.49 0.54 0.49 0.46 0.72 0.69 0.77 0.56 0.54 0.45 0.52 0.45 0.54 0.50 0.50 0.73 0.71 0.75 0.56 0.55 0.49 0.53 0.49 0.54 0.52 0.48 0.69 0.71 0.75 0.59 0.51 0.51 0.58 0.51 0.61 0.55 0.55 0.70 0.67 0.73 0.68 0.61 0.60 0.59 0.60 0.62 0.61 0.57 0.73 0.70 0.75 0.70 0.60 0.57 0.63 0.62 0.65 0.63 0.59 0.72 0.73 0.74 0.68 0.61 0.58 0.64 0.61 0.66 0.61 0.59 0.74 0.74 0.76 0.37 0.26 0.24 0.28 0.34 0.31 0.28 0.29 0.18 0.19 0.25 0.25 0.27 0.24 0.28 0.24 0.26 0.27 0.22 0.02 0.01 0.04 0.22 0.14 0.08 0.09 0.23 0.12 0.22 0.17 0.11 0.18 0.18 149 Table 16.1 (cont’d) 24 23 25 22 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 171 * p <0.05 1.00 0.74 1.00 0.73 0.83 1.00 0.75 0.82 0.82 1.00 0.75 0.79 0.81 0.82 1.00 0.71 0.72 0.74 0.74 0.74 1.00 0.73 0.73 0.74 0.73 0.71 0.81 1.00 0.75 0.71 0.75 0.77 0.73 0.84 0.84 1.00 0.76 0.72 0.76 0.78 0.75 0.82 0.81 0.87 0.23 0.22 0.16 0.31 0.23 0.28 0.29 0.30 0.02 0.05 0.03 0.08 0.07 0.15 0.12 0.13 0.14 0.16 0.14 0.15 0.14 0.10 0.11 0.10 150 Table 16.1 (cont’d) 30 31 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 171 * p <0.05 1.00 0.26 1.00 0.10 0.46 1.00 0.09 0.34 0.25 1.00 151 Table 16.2: Correlation Matrix for Friends Male and Other Respondents 4 2 3 1 1.00 M1 1 1.00 0.56 M2 2 1.00 0.47 0.49 M3 3 0.20 1.00 0.34 0.27 N1 4 0.38 0.23 0.35 0.41 N2 5 0.18 0.28 0.26 0.20 N3 6 0.05 0.32 -0.01 0.19 N4 7 0.34 0.47 0.34 0.46 N5 8 0.34 0.48 0.33 0.45 N6 9 0.27 0.46 0.34 0.43 N7 10 0.33 0.21 0.38 0.41 T1 11 0.28 0.14 0.28 0.40 T2 12 0.40 0.26 0.42 0.53 T3 13 0.32 0.17 0.30 0.45 T4 14 0.41 0.25 0.41 0.57 T5 15 0.37 0.22 0.39 0.43 T6 16 0.40 0.24 0.42 0.54 T7 17 0.35 0.24 0.43 0.48 T8 18 0.39 0.20 0.35 0.46 B1 19 0.34 0.14 0.33 0.43 B2 20 0.27 0.18 0.30 0.39 B3 21 0.31 0.23 0.32 0.41 B4 22 0.31 0.20 0.34 0.42 F1 23 0.34 0.18 0.29 0.40 F2 24 0.39 0.14 0.29 0.36 F3 25 0.35 0.18 0.30 0.36 F4 26 0.35 0.21 0.39 0.49 W1 27 0.32 0.19 0.34 0.50 W2 28 0.38 0.25 0.39 0.47 W3 29 0.39 0.24 0.38 0.47 W4 30 -0.01 0.01 -0.12 31 -0.08 SocDisBla 0.08 0.07 0.03 32 SocialDisFem 0.16 0.10 0.16 0.12 0.16 SocDisUpp 33 Note. N = 156 * p <0.05 5 6 7 8 9 10 1.00 0.30 0.09 0.34 0.33 0.32 0.32 0.37 0.30 0.24 0.29 0.27 0.38 0.27 0.32 0.35 0.23 0.33 0.27 0.28 0.38 0.38 0.32 0.37 0.33 0.30 -0.07 0.02 0.07 1.00 1.00 0.15 0.29 1.00 0.29 0.34 0.64 0.26 0.37 0.56 0.36 0.19 0.52 0.20 0.08 0.35 0.16 0.13 0.53 0.25 0.13 0.40 0.34 0.10 0.44 0.25 0.06 0.44 0.15 0.05 0.43 0.23 0.11 0.41 0.24 0.12 0.43 0.23 0.06 0.41 0.18 0.12 0.42 0.28 0.14 0.41 0.20 0.06 0.42 0.28 0.10 0.36 0.23 0.09 0.31 0.23 0.04 0.32 0.18 0.14 0.46 0.19 0.11 0.42 0.22 0.13 0.48 0.23 0.15 0.43 0.20 -0.12 0.12 -0.01 -0.04 0.04 0.05 0.08 0.24 0.16 1.00 0.63 1.00 0.45 0.41 0.36 0.33 0.49 0.39 0.44 0.41 0.41 0.41 0.39 0.31 0.40 0.36 0.40 0.37 0.43 0.41 0.45 0.39 0.39 0.38 0.44 0.40 0.40 0.42 0.42 0.40 0.40 0.37 0.41 0.37 0.45 0.47 0.46 0.39 0.47 0.40 0.48 0.42 0.03 0.03 0.08 0.10 0.11 0.17 152 11 12 Table 16.2 (cont’d) 13 14 15 16 17 18 19 20 21 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 156 * p <0.05 1.00 0.73 1.00 0.75 0.73 1.00 0.70 0.69 0.71 1.00 0.77 0.70 0.74 0.69 1.00 0.74 0.69 0.74 0.72 0.77 1.00 0.72 0.70 0.73 0.73 0.81 0.75 1.00 0.69 0.68 0.70 0.79 0.76 0.80 0.79 1.00 0.72 0.66 0.70 0.66 0.71 0.67 0.70 0.67 1.00 0.70 0.66 0.68 0.63 0.65 0.71 0.70 0.70 0.77 1.00 0.71 0.63 0.66 0.67 0.66 0.64 0.61 0.65 0.80 0.79 1.00 0.71 0.66 0.68 0.66 0.65 0.67 0.70 0.67 0.82 0.81 0.81 0.70 0.62 0.67 0.61 0.65 0.65 0.60 0.62 0.74 0.76 0.78 0.73 0.64 0.69 0.68 0.70 0.67 0.67 0.66 0.81 0.76 0.79 0.65 0.62 0.64 0.63 0.64 0.67 0.66 0.69 0.75 0.82 0.72 0.65 0.67 0.66 0.61 0.56 0.62 0.61 0.65 0.76 0.74 0.74 0.73 0.65 0.72 0.65 0.73 0.68 0.70 0.68 0.81 0.74 0.76 0.71 0.65 0.70 0.62 0.71 0.68 0.67 0.70 0.75 0.70 0.71 0.72 0.64 0.70 0.65 0.67 0.71 0.68 0.68 0.76 0.76 0.76 0.69 0.65 0.72 0.67 0.73 0.67 0.72 0.69 0.77 0.75 0.75 0.23 0.15 0.13 0.12 0.17 0.22 0.20 0.20 0.13 0.14 0.10 0.26 0.23 0.25 0.22 0.27 0.20 0.29 0.29 0.21 0.20 0.19 0.20 0.06 0.18 0.11 0.24 0.14 0.21 0.17 0.15 0.19 0.19 153 Table 16.2 (cont’d) 24 25 23 22 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 156 * p <0.05 1.00 0.77 1.00 0.79 0.78 1.00 0.75 0.75 0.77 1.00 0.82 0.76 0.77 0.79 1.00 0.80 0.77 0.78 0.71 0.77 1.00 0.76 0.70 0.75 0.72 0.76 0.83 1.00 0.82 0.78 0.77 0.76 0.78 0.84 0.81 1.00 0.79 0.75 0.77 0.73 0.76 0.84 0.79 0.80 0.21 0.13 0.16 0.18 0.19 0.16 0.19 0.11 0.20 0.11 0.15 0.17 0.23 0.21 0.24 0.18 0.16 0.18 0.18 0.15 0.15 0.16 0.14 0.13 154 Table 16.2 (cont’d) 30 31 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 156 * p <0.05 1.00 0.16 1.00 0.24 0.46 1.00 0.15 0.25 0.30 1.00 155 Table 17.1: Correlation Matrix for Friends Respondents with Social Level 5 or Below 10 8 5 2 7 4 9 6 3 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 1.00 1 1.00 0.54 2 1.00 0.40 0.56 3 0.12 1.00 0.35 0.24 4 0.36 0.41 0.31 0.42 5 0.12 0.20 0.11 0.06 6 0.19 0.12 -0.07 0.07 7 0.18 0.34 0.32 0.43 8 0.18 0.44 0.38 0.31 9 0.26 0.35 0.33 0.38 10 0.48 0.26 0.32 0.55 11 0.41 0.15 0.23 0.50 12 0.38 0.24 0.41 0.54 13 0.30 0.26 0.40 0.50 14 0.44 0.16 0.28 0.56 15 0.33 0.11 0.28 0.45 16 0.46 0.17 0.30 0.53 17 0.38 0.16 0.30 0.49 18 0.46 0.20 0.30 0.45 19 0.44 0.23 0.35 0.46 20 0.42 0.24 0.33 0.46 21 0.43 0.21 0.30 0.40 22 0.39 0.25 0.35 0.51 23 0.34 0.23 0.30 0.41 24 0.40 0.29 0.30 0.40 25 0.35 0.21 0.27 0.39 26 0.38 0.23 0.33 0.49 27 0.37 0.18 0.30 0.45 28 0.39 0.24 0.36 0.43 29 0.38 0.23 0.36 0.43 30 -0.12 0.13 -0.07 0.01 31 -0.10 0.04 -0.04 -0.00 32 SocialDisFem -0.06 0.08 0.16 0.10 SocDisUpp 33 Note. N = 109 * p <0.05 156 1.00 0.21 0.05 0.44 0.40 0.38 0.37 0.38 0.36 0.29 0.28 0.29 0.35 0.23 0.43 0.39 0.37 0.38 0.46 0.44 0.50 0.49 0.43 0.48 0.38 0.37 -0.18 -0.20 -0.02 0.01 1.00 -0.02 1.00 0.03 0.11 -0.00 0.23 0.15 0.38 0.02 0.11 0.02 0.06 -0.02 0.05 -0.04 0.11 -0.06 0.07 -0.12 0.02 -0.03 0.06 -0.00 0.10 0.02 0.19 0.00 0.12 -0.01 0.10 0.01 0.13 -0.07 0.12 -0.05 0.10 -0.05 0.06 -0.02 0.03 -0.00 0.02 0.02 0.07 0.01 0.05 0.05 0.04 -0.20 0.04 -0.15 0.01 0.09 1.00 0.63 0.51 0.40 0.27 0.40 0.40 0.31 0.30 0.31 0.25 0.36 0.39 0.39 0.33 0.37 0.38 0.36 0.35 0.44 0.43 0.40 0.36 -0.13 -0.11 0.14 1.00 0.60 0.32 0.26 0.34 0.38 0.27 0.24 0.24 0.25 0.34 0.38 0.34 0.34 0.35 0.37 0.37 0.35 0.37 0.36 0.36 0.34 -0.20 -0.02 0.01 1.00 0.26 0.22 0.26 0.24 0.26 0.09 0.20 0.18 0.29 0.23 0.30 0.26 0.32 0.31 0.28 0.25 0.30 0.30 0.29 0.33 -0.15 -0.03 0.08 11 12 Table 17.1 (cont’d) 13 15 14 16 17 18 19 20 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 1.00 11 0.80 1.00 12 0.79 0.75 13 0.72 0.67 14 0.81 0.76 15 0.76 0.73 16 0.83 0.80 17 0.73 0.74 18 0.60 0.48 19 0.61 0.52 20 0.60 0.48 21 0.61 0.51 22 0.55 0.48 23 0.55 0.47 24 0.55 0.47 25 0.55 0.53 26 0.66 0.57 27 0.63 0.63 28 0.65 0.57 29 0.62 0.52 30 31 0.21 0.14 32 SocialDisFem 0.21 0.23 SocDisUpp 33 Note. N = 109 * p <0.05 1.00 0.76 1.00 0.75 0.69 0.80 0.79 0.79 0.73 0.73 0.84 0.53 0.52 0.55 0.52 0.55 0.54 0.55 0.55 0.55 0.54 0.55 0.56 0.50 0.57 0.52 0.55 0.64 0.62 0.66 0.58 0.61 0.66 0.57 0.63 0.08 0.13 0.21 0.21 0.10 -0.06 0.02 -0.03 157 1.00 0.79 1.00 0.90 0.82 0.76 0.82 0.49 0.52 0.50 0.54 0.53 0.54 0.51 0.59 0.50 0.51 0.52 0.56 0.48 0.53 0.46 0.55 0.60 0.66 0.59 0.62 0.59 0.66 0.62 0.61 0.17 0.17 0.24 0.18 0.06 -0.02 1.00 0.81 1.00 0.53 0.54 1.00 0.53 0.54 0.89 0.51 0.55 0.90 0.55 0.61 0.92 0.50 0.47 0.79 0.50 0.53 0.79 0.51 0.53 0.76 0.49 0.53 0.75 0.61 0.60 0.76 0.62 0.58 0.73 0.63 0.63 0.77 0.57 0.60 0.72 0.21 0.18 0.01 0.23 0.25 -0.06 0.07 0.01 0.05 1.00 0.87 0.92 0.76 0.78 0.79 0.76 0.76 0.75 0.78 0.75 -0.00 -0.08 0.05 21 22 Table 17.1 (cont’d) 25 24 23 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1.00 21 0.90 22 0.80 23 0.81 24 0.77 25 0.77 26 0.82 27 0.79 28 0.78 29 0.80 30 0.03 31 -0.03 32 SocialDisFem 0.07 SocDisUpp 33 Note. N = 109 * p <0.05 1.00 0.78 0.80 0.81 0.81 0.79 0.76 0.81 0.78 0.04 -0.04 0.01 1.00 0.85 0.86 0.82 0.80 0.72 0.78 0.76 -0.05 -0.12 0.04 1.00 1.00 0.87 0.90 0.86 0.77 0.81 0.73 0.81 0.81 0.82 0.79 0.83 -0.03 0.10 -0.13 -0.08 -0.01 0.02 1.00 1.00 0.82 0.86 1.00 0.76 0.89 0.86 0.83 0.88 0.81 0.79 0.07 0.09 0.07 -0.04 0.05 0.04 -0.04 0.02 -0.03 1.00 0.85 0.12 0.02 -0.03 158 Table 17.1 (cont’d) 31 30 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 109 * p <0.05 1.00 0.08 1.00 -0.02 0.46 1.00 -0.01 0.22 0.21 1.00 159 8 5 6 7 3 9 2 10 Table 17.2: Correlation Matrix for Friends Respondents with Social Level Above 5 4 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem 33 SocDisUpp Note. N = 218 * p <0.05 1 1.00 0.49 1.00 0.52 0.47 1.00 0.18 0.26 0.16 1.00 1.00 0.38 0.39 0.37 0.21 0.36 1.00 0.22 0.27 0.20 0.34 0.19 0.35 1.00 0.06 0.15 0.09 0.42 0.19 0.36 0.39 1.00 0.25 0.29 0.24 0.43 0.23 0.30 0.47 0.54 1.00 0.17 0.21 0.22 0.44 0.27 0.35 0.53 0.53 0.56 1.00 0.30 0.27 0.20 0.45 0.20 0.32 0.51 0.31 0.33 0.40 0.22 0.27 0.30 0.16 0.23 0.26 0.34 0.18 0.27 0.30 0.26 0.29 0.31 0.09 0.23 0.33 0.32 0.27 0.30 0.38 0.38 0.35 0.37 0.22 0.21 0.37 0.37 0.16 0.24 0.36 0.30 0.25 0.31 0.12 0.23 0.31 0.37 0.21 0.25 0.34 0.38 0.34 0.38 0.19 0.24 0.27 0.32 0.26 0.27 0.37 0.35 0.40 0.40 0.17 0.24 0.27 0.35 0.20 0.24 0.33 0.36 0.35 0.36 0.18 0.22 0.28 0.34 0.23 0.22 0.34 0.37 0.36 0.34 0.21 0.22 0.28 0.34 0.17 0.23 0.31 0.32 0.34 0.33 0.20 0.25 0.29 0.31 0.19 0.21 0.35 0.29 0.26 0.27 0.17 0.20 0.34 0.36 0.23 0.24 0.34 0.28 0.30 0.28 0.19 0.26 0.31 0.38 0.23 0.28 0.38 0.34 0.33 0.30 0.25 0.24 0.34 0.27 0.27 0.25 0.37 0.30 0.33 0.28 0.16 0.22 0.28 0.29 0.21 0.29 0.38 0.30 0.32 0.32 0.15 0.25 0.29 0.28 0.21 0.27 0.32 0.31 0.34 0.39 0.17 0.33 0.31 0.28 0.14 0.24 0.32 0.26 0.34 0.36 0.17 0.30 0.30 0.36 0.23 0.23 0.40 0.38 0.36 0.36 0.20 0.31 0.33 0.36 0.19 0.27 0.39 0.39 0.36 0.36 0.22 0.29 0.32 0.38 0.27 0.27 0.38 0.36 0.37 0.38 0.25 0.29 0.33 0.38 0.24 0.32 0.38 0.41 0.36 0.45 0.22 0.08 0.17 0.16 0.04 0.07 0.06 0.14 0.06 0.07 0.09 0.18 0.16 0.21 -0.02 0.08 0.06 0.01 0.01 0.06 0.03 0.10 0.25 0.09 0.17 0.10 0.10 0.03 0.08 0.07 0.15 160 11 12 Table 17.2 (cont’d) 13 15 14 16 17 18 19 20 21 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 218 * p <0.05 1.00 0.73 1.00 0.69 0.70 1.00 0.68 0.65 0.65 1.00 0.76 0.71 0.71 0.64 1.00 0.72 0.72 0.69 0.69 0.76 1.00 0.71 0.71 0.66 0.67 0.78 0.71 1.00 0.68 0.68 0.63 0.72 0.75 0.80 0.76 1.00 0.69 0.64 0.56 0.61 0.64 0.63 0.64 0.60 1.00 0.67 0.65 0.57 0.58 0.61 0.64 0.65 0.64 0.73 1.00 0.70 0.64 0.61 0.64 0.61 0.63 0.61 0.60 0.75 0.75 1.00 0.71 0.67 0.62 0.61 0.65 0.63 0.67 0.61 0.78 0.76 0.79 0.64 0.59 0.54 0.53 0.57 0.61 0.55 0.58 0.66 0.71 0.73 0.68 0.63 0.61 0.59 0.63 0.62 0.61 0.56 0.73 0.69 0.75 0.61 0.62 0.54 0.56 0.56 0.62 0.59 0.60 0.71 0.73 0.70 0.63 0.65 0.59 0.57 0.56 0.59 0.59 0.57 0.70 0.70 0.73 0.66 0.59 0.57 0.60 0.62 0.63 0.61 0.61 0.73 0.65 0.69 0.71 0.62 0.63 0.61 0.67 0.64 0.63 0.64 0.74 0.66 0.69 0.72 0.63 0.62 0.61 0.65 0.68 0.64 0.62 0.71 0.71 0.72 0.72 0.68 0.67 0.66 0.70 0.69 0.71 0.66 0.77 0.73 0.73 0.35 0.24 0.25 0.24 0.31 0.32 0.25 0.29 0.24 0.27 0.28 0.28 0.26 0.25 0.27 0.26 0.25 0.30 0.24 0.20 0.19 0.19 0.27 0.18 0.18 0.16 0.32 0.20 0.29 0.25 0.18 0.27 0.25 161 Table 17.2 (cont’d) 24 23 25 22 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 218 * p <0.05 1.00 0.73 1.00 0.73 0.77 1.00 0.71 0.73 0.75 1.00 0.76 0.75 0.74 0.74 1.00 0.73 0.69 0.72 0.68 0.71 1.00 0.73 0.69 0.71 0.71 0.71 0.80 1.00 0.76 0.71 0.72 0.72 0.71 0.80 0.80 1.00 0.77 0.71 0.72 0.73 0.72 0.79 0.79 0.82 0.34 0.29 0.27 0.32 0.29 0.30 0.34 0.25 0.18 0.19 0.21 0.24 0.25 0.24 0.24 0.22 0.22 0.24 0.25 0.22 0.24 0.19 0.20 0.19 162 Table 17.2 (cont’d) 30 31 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 218 * p <0.05 1.00 0.29 1.00 0.26 0.45 1.00 0.19 0.34 0.30 1.00 163 Table 18.1: Correlation Matrix for Friends Respondents with Age Below 35 5 6 7 8 9 10 2 4 3 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 1.00 0.52 1.00 0.52 0.44 1.00 0.21 0.34 0.13 1.00 0.34 0.36 0.40 0.29 0.12 0.14 0.09 0.27 0.11 0.25 0.18 0.31 0.28 0.30 0.19 0.38 0.30 0.28 0.25 0.39 0.27 0.30 0.20 0.40 0.30 0.31 0.32 0.07 0.35 0.25 0.30 0.03 0.39 0.39 0.38 0.17 0.35 0.27 0.29 0.07 0.38 0.36 0.36 0.07 0.32 0.31 0.31 0.07 0.39 0.34 0.35 0.08 0.40 0.32 0.29 0.14 0.35 0.33 0.34 0.11 0.39 0.33 0.30 0.10 0.29 0.32 0.25 0.12 0.39 0.37 0.29 0.18 0.37 0.34 0.28 0.11 0.29 0.30 0.29 0.11 0.38 0.32 0.35 0.15 0.34 0.31 0.36 0.12 0.37 0.37 0.30 0.12 0.42 0.38 0.33 0.13 0.38 0.42 0.35 0.17 0.44 0.38 0.39 0.15 0.00 0.08 0.14 0.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem 0.13 0.12 0.18 -0.02 0.00 0.06 SocDisUpp 33 Note. N = 181. * p <0.05 0.01 0.06 0.01 0.19 1.00 1.00 0.30 0.26 0.25 0.16 0.24 0.19 0.37 0.26 0.33 0.13 0.20 0.10 0.25 0.20 0.27 0.31 0.26 0.14 0.20 0.09 0.23 0.13 0.28 0.13 0.20 0.19 0.31 0.15 0.34 0.24 0.25 0.19 0.34 0.23 0.26 0.20 0.27 0.23 0.40 0.21 0.38 0.10 0.31 0.19 0.34 0.16 0.31 0.17 0.32 -0.03 0.02 1.00 0.29 1.00 0.37 0.60 0.49 0.49 0.39 0.23 0.28 0.15 0.29 0.23 0.29 0.14 0.31 0.14 0.16 0.17 0.25 0.07 0.23 0.10 0.27 0.21 0.18 0.26 0.24 0.26 0.23 0.28 0.15 0.29 0.19 0.23 0.23 0.27 0.21 0.22 0.30 0.30 0.30 0.26 0.29 0.31 0.30 0.28 0.05 -0.06 -0.06 0.04 -0.11 0.04 0.04 0.10 1.00 1.00 0.54 0.30 0.33 0.26 0.27 0.32 0.29 0.32 0.28 0.25 0.26 0.19 0.24 0.21 0.21 0.27 0.20 0.31 0.33 0.33 0.38 0.31 0.32 0.35 0.37 0.33 0.27 0.31 0.33 0.34 0.37 0.35 0.32 0.38 0.33 0.36 0.30 0.34 0.33 0.40 0.38 -0.01 -0.00 -0.04 0.05 0.02 0.03 164 11 12 Table 18.1 (cont’d) 13 14 15 16 17 18 19 20 21 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 181. * p <0.05 1.00 0.73 1.00 0.68 0.71 1.00 0.68 0.67 0.68 1.00 0.80 0.71 0.70 0.66 1.00 0.75 0.72 0.71 0.68 0.77 1.00 0.71 0.75 0.66 0.70 0.81 0.74 1.00 0.67 0.67 0.65 0.75 0.75 0.73 0.78 1.00 0.60 0.56 0.48 0.57 0.57 0.57 0.59 0.55 1.00 0.59 0.61 0.52 0.55 0.51 0.60 0.58 0.55 0.73 1.00 0.58 0.54 0.53 0.58 0.51 0.54 0.48 0.51 0.74 0.74 1.00 0.60 0.60 0.59 0.56 0.56 0.60 0.59 0.57 0.76 0.78 0.80 0.60 0.55 0.56 0.52 0.53 0.57 0.50 0.52 0.65 0.74 0.73 0.60 0.57 0.56 0.58 0.58 0.60 0.53 0.54 0.73 0.70 0.73 0.56 0.56 0.53 0.56 0.49 0.56 0.53 0.54 0.72 0.77 0.69 0.58 0.61 0.59 0.58 0.51 0.60 0.54 0.53 0.70 0.74 0.74 0.66 0.58 0.59 0.59 0.57 0.64 0.57 0.58 0.70 0.67 0.68 0.67 0.62 0.64 0.59 0.63 0.64 0.63 0.63 0.71 0.68 0.69 0.69 0.63 0.60 0.61 0.63 0.71 0.61 0.61 0.69 0.72 0.69 0.64 0.63 0.62 0.63 0.65 0.66 0.62 0.62 0.70 0.71 0.69 0.30 0.22 0.21 0.15 0.27 0.26 0.23 0.25 0.12 0.14 0.17 0.23 0.22 0.23 0.22 0.21 0.19 0.20 0.20 0.11 0.10 0.07 0.10 0.03 0.09 0.02 0.16 0.04 0.06 0.10 0.04 0.06 0.09 165 Table 18.1 (cont’d) 24 23 25 22 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 181. * p <0.05 1.00 0.72 1.00 0.72 0.72 1.00 0.73 0.75 0.76 1.00 0.80 0.76 0.76 0.79 1.00 0.72 0.69 0.76 0.73 0.76 1.00 0.72 0.67 0.72 0.71 0.74 0.77 1.00 0.76 0.71 0.73 0.74 0.76 0.80 0.78 1.00 0.74 0.72 0.76 0.72 0.76 0.78 0.75 0.79 0.23 0.20 0.16 0.26 0.23 0.26 0.28 0.23 0.09 0.07 0.07 0.08 0.17 0.20 0.18 0.16 0.05 0.08 0.07 0.10 0.08 0.04 0.09 0.02 166 Table 18.1 (cont’d) 30 31 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 181. * p <0.05 1.00 0.23 1.00 0.17 0.48 1.00 0.06 0.32 0.21 1.00 167 Table 18.2: Correlation Matrix for Friends Respondents with Age 35 or Above 2 4 3 1 1.00 M1 1 1.00 0.53 M2 2 0.47 1.00 0.58 M3 3 0.23 0.12 1.00 0.15 N1 4 0.37 0.33 0.27 0.48 N2 5 0.22 0.28 0.26 0.29 N3 6 -0.05 0.01 0.09 0.28 N4 7 0.31 0.25 0.39 0.37 N5 8 0.28 0.19 0.46 0.21 N6 9 0.29 0.24 0.41 0.39 N7 10 0.31 0.45 0.26 0.45 T1 11 0.33 0.44 0.16 0.39 T2 12 0.38 0.40 0.24 0.53 T3 13 0.39 0.36 0.24 0.45 T4 14 0.33 0.49 0.24 0.58 T5 15 0.45 0.48 0.17 0.51 T6 16 0.37 0.49 0.22 0.51 T7 17 0.42 0.45 0.21 0.47 T8 18 0.36 0.46 0.25 0.43 B1 19 0.30 0.42 0.25 0.38 B2 20 0.33 0.47 0.26 0.45 B3 21 0.30 0.45 0.27 0.37 B4 22 0.36 0.39 0.26 0.42 F1 23 0.34 0.40 0.24 0.43 F2 24 0.36 0.47 0.25 0.35 F3 25 0.34 0.37 0.23 0.31 F4 26 0.37 0.48 0.27 0.51 W1 27 0.31 0.44 0.25 0.46 W2 28 0.34 0.46 0.28 0.44 W3 29 0.37 0.49 0.27 0.43 W4 30 0.07 0.17 -0.04 31 0.14 SocDisBla 0.01 0.09 -0.04 32 SocialDisFem 0.08 0.01 0.15 0.10 0.09 SocDisUpp 33 Note. N = 146. * p <0.05 5 6 7 8 9 10 1.00 1.00 0.15 0.22 0.35 0.26 0.39 0.29 0.45 0.31 0.34 0.21 0.28 0.16 0.25 0.18 0.22 0.16 0.29 0.21 0.25 0.23 0.26 0.23 0.29 0.19 0.28 0.23 0.26 0.23 0.24 0.26 0.28 0.18 0.28 0.18 0.23 0.13 0.17 0.14 0.18 0.17 0.28 0.22 0.27 0.26 0.27 0.24 0.26 -0.13 0.16 1.00 0.31 0.02 0.37 0.22 0.29 0.37 0.35 0.31 0.23 0.34 0.31 0.31 0.27 0.32 0.29 0.31 0.29 0.41 0.38 0.30 0.42 0.42 0.43 0.36 0.34 -0.02 -0.06 0.02 0.22 0.04 1.00 0.55 1.00 0.55 0.61 0.46 0.38 0.29 0.31 0.42 0.39 0.38 0.35 0.37 0.33 0.38 0.33 0.43 0.34 0.38 0.31 0.28 0.25 0.29 0.22 0.35 0.27 0.27 0.26 0.33 0.34 0.34 0.32 0.27 0.27 0.24 0.28 0.32 0.28 0.32 0.36 0.34 0.32 0.29 0.30 0.05 -0.03 -0.04 0.05 0.12 0.27 0.12 0.11 1.00 0.39 0.28 0.37 0.31 0.37 0.35 0.35 0.30 0.28 0.28 0.33 0.32 0.39 0.40 0.27 0.22 0.32 0.35 0.35 0.31 -0.00 -0.05 0.16 168 11 12 Table 18.2 (cont’d) 13 14 15 16 17 18 19 20 21 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 146. * p <0.05 1.00 0.80 1.00 0.78 0.75 1.00 0.72 0.65 0.73 1.00 0.77 0.77 0.77 0.67 1.00 0.74 0.74 0.77 0.78 0.81 1.00 0.83 0.75 0.77 0.70 0.86 0.79 1.00 0.74 0.74 0.71 0.79 0.77 0.89 0.79 1.00 0.72 0.62 0.64 0.59 0.62 0.61 0.63 0.61 1.00 0.72 0.60 0.62 0.58 0.65 0.63 0.64 0.66 0.86 1.00 0.75 0.64 0.65 0.63 0.66 0.66 0.70 0.66 0.89 0.87 1.00 0.74 0.63 0.61 0.62 0.64 0.64 0.67 0.65 0.91 0.86 0.87 0.63 0.58 0.55 0.57 0.57 0.59 0.58 0.57 0.78 0.73 0.79 0.68 0.59 0.62 0.60 0.61 0.60 0.63 0.58 0.80 0.76 0.82 0.63 0.59 0.54 0.58 0.58 0.63 0.61 0.62 0.76 0.75 0.78 0.63 0.61 0.53 0.55 0.54 0.55 0.58 0.59 0.75 0.71 0.76 0.66 0.60 0.63 0.64 0.67 0.66 0.68 0.64 0.79 0.73 0.81 0.73 0.65 0.66 0.62 0.69 0.67 0.66 0.63 0.79 0.72 0.79 0.73 0.62 0.66 0.67 0.67 0.66 0.70 0.66 0.78 0.76 0.81 0.74 0.63 0.67 0.68 0.70 0.68 0.72 0.66 0.81 0.77 0.83 0.30 0.19 0.18 0.28 0.24 0.28 0.26 0.25 0.18 0.19 0.20 0.26 0.27 0.24 0.28 0.28 0.26 0.35 0.28 0.08 0.07 0.14 0.31 0.17 0.16 0.16 0.29 0.20 0.36 0.22 0.20 0.29 0.26 169 Table 18.2 (cont’d) 24 25 23 22 26 27 28 29 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 146. * p <0.05 1.00 0.78 1.00 0.81 0.89 1.00 0.77 0.81 0.84 1.00 0.78 0.80 0.82 0.82 1.00 0.79 0.79 0.77 0.71 0.74 1.00 0.78 0.76 0.77 0.74 0.72 0.88 1.00 0.81 0.77 0.79 0.78 0.75 0.89 0.88 1.00 0.81 0.74 0.78 0.78 0.73 0.87 0.86 0.88 0.22 0.14 0.16 0.22 0.19 0.17 0.18 0.19 0.09 0.08 0.09 0.16 0.11 0.13 0.15 0.13 0.23 0.25 0.26 0.19 0.20 0.21 0.15 0.21 170 Table 18.2 (cont’d) 30 31 32 33 M1 M2 M3 N1 N2 N3 N4 N5 N6 N7 T1 T2 T3 T4 T5 T6 T7 T8 B1 B2 B3 B4 F1 F2 F3 F4 W1 W2 W3 W4 SocDisBla 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 SocialDisFem SocDisUpp 33 Note. N = 146. * p <0.05 1.00 0.19 1.00 0.14 0.42 1.00 0.17 0.25 0.33 1.00 171 APPENDIX B: MERITOCRACY, MEDIA EXPOSURE, RII ITEMS (FRIENDS) Q2 Think about how people in our society get ahead or advance professionally or personally themselves. Read each statement and rate whether you agree or disagree with each statement about the society in general. Neither Strongly Agree or Strongly Statements Disagree Disagree Disagree Agree Agree People who work hard enough will definitely get ahead in life. o o o o o People who have a good education will certainly be able to advance in their career. Ambition indicates success in life. Those who come from wealthy families are guaranteed to get ahead in our o o o o o o o o o o society. o o o o o For people with well-educated parents, I expect they shall be successful in our society. Having political connections is sufficient to advance a person's o o o o o o o o o o 172 Neither Strongly Agree or Strongly Statements Disagree Disagree Disagree Agree Agree standing in the social hierarchy in our society. Knowing the right people will definitely help a person to get ahead in life. People will advance in our society as long as they cheat. Being born as a man will automatically advance standings in the social hierarchy in our society. People who are born white will easily get ahead in our society. Being born as a heterosexual will automatically advance standings in the o o o o o o o o o o o o o o o o o o o o social hierarchy in our society. o o o o o 173 Q4.2 Now think about how you currently watch Friends and answer the following questions. For each question, please check the appropriate circle. Questions Never Sometimes the time the time Always About half Most of How often do you watch Friends when you first wake up in the morning? o o How often do you watch Friends in the afternoon? o o How often do you watch Friends early at night? o o How often do you watch Friends late at night, before going to bed? o o How often do you watch Friends during the day on Saturday? o o How often do you watch Friends on Saturday nights? o o How often do you watch Friends during the day on Sunday? o o How often do you watch Friends on Sunday nights? o o 174 o o o o o o o o o o o o o o o o o o o o o o o o Q5.1 Screenwriters and Producers usually define the term BACKSTORY as the story that happens before the beginning of the main story that is seen on screen. Backstory gives us more context about the situations, relationships, or circumstances in the story and how a character becomes the person we meet at the beginning of the main story. Please indicate how often have you done the following regarding the BACKSTORY of EVENT(S) in Friends AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a situation in a story better, imagine a backstory associated with the situation o o o o o o o To understand the conflict in a story better, imagine a backstory associated with that conflict o o o o o o o To understand some of the significant events in a story better, imagine a backstory associated with those events o o o o o o o 175 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand the protagonist in a story better, imagine a backstory associated with that character o o o o o o o Q5.2 Please indicate how often have you done the following regarding the BACKSTORY of BLACK CHARACTER(S) in Friends AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a black character(s) better, do you ever imagine a backstory associated with that character(s). o o o o o o o To understand certain challenging circumstances faced by a black character(s), do you ever imagine a backstory associated with the o o o o o o o 176 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always formation of those circumstances? To understand the crucial relationships of a black character(s) with other story characters, do you ever imagine a backstory associated with the formation of those relationships? o o o o o o o To understand the motivations/choices made by a black character(s) better, do you ever imagine a backstory associated with those motivations of the character(s)? o o o o o o o Q5.3 Please indicate how often have you done the following regarding the BACKSTORY of FEMALE CHARACTER(S) in Friends AFTER watching/reading it and thinking about it later: 177 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a female character(s) better, do you ever imagine a backstory associated with that character(s). o o o o o o o To understand certain challenging circumstances faced by a female character(s), do you ever imagine a backstory associated with the formation of those circumstances? o o o o o o o To understand the crucial relationships of a female character(s) with other story characters, do you ever imagine a backstory associated with the formation of those relationships? o o o o o o o 178 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand the motivations/choices made by a female character(s) better, do you ever imagine a backstory associated with those motivations of the character(s)? o o o o o o o Q5.4 Please indicate how often have you done the following regarding the BACKSTORY of WEALTHY CHARACTER(S) in Friends AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a wealthy character(s) better, do you ever imagine a backstory associated with that character(s). o o o To understand certain challenging circumstances o o o o o o o o o o o 179 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always faced by a wealthy character(s), do you ever imagine a backstory associated with the formation of those circumstances? To understand the crucial relationships of a wealthy character(s) with other story characters, do you ever imagine a backstory associated with the formation of those relationships? o o o o o o o To understand the motivations/choices made by a wealthy character(s) better, do you ever imagine a backstory associated with those motivations of the character(s)? o o o o o o o 180 Q3.3 Now think about how you currently watch television and answer the following questions. For each question, please check the appropriate circle. Questions Never Rarely Sometimes Often the Time Always Always Most of Almost How often do you watch television when you first wake up in the morning? o o o o o How often do you watch television in the afternoon? o o o o o How often do you watch television early at night? o o o o o o o o o o o How often do you watch television late at night, before going to bed? o o o o o o o How often do you watch television during the day on Saturday? o o o o o How often do you watch television on Saturday nights? o o o o o o o o o 181 Questions Never Rarely Sometimes Often the Time Always Always Most of Almost How often do you watch television during the day on Sunday? o o o o o How often do you watch television on Sunday nights? o o o o o o o o o 182 APPENDIX C: MERITOCRACY, MEDIA EXPOSURE, RII ITEMS (MCU) Q2 Think about how people in our society get ahead or advance professionally or personally themselves. Read each statement and rate whether you agree or disagree with each statement about the society in general. Neither Strongly Agree or Strongly Statements Disagree Disagree Disagree Agree Agree People who work hard enough will definitely get ahead in life. o o o o o People who have a good education will certainly be able to advance in their career. Ambition indicates success in life. Those who come from wealthy families are guaranteed to get ahead in our o o o o o o o o o o society. o o o o o For people with well-educated parents, I expect they shall be successful in our society. Having political connections is sufficient to advance a person's o o o o o o o o o o 183 Neither Strongly Agree or Strongly Statements Disagree Disagree Disagree Agree Agree standing in the social hierarchy in our society. Knowing the right people will definitely help a person to get ahead in life. People will advance in our society as long as they cheat. Being born as a man will automatically advance standings in the social hierarchy in our society. People who are born white will easily get ahead in our society. Being born as a heterosexual will automatically advance standings in the o o o o o o o o o o o o o o o o o o o o social hierarchy in our society. o o o o o Q4.2 Now think about how you currently watch MCU and answer the following questions. For each question, please check the appropriate circle. 184 Questions Never Sometimes the time the time Always About half Most of How often do you watch MCU when you first wake up in the morning? o o How often do you watch MCU in the afternoon? o o How often do you watch MCU early at night? o o How often do you watch MCU late at night, before going to bed? o o How often do you watch MCU during the day on Saturday? o o How often do you watch MCU on Saturday nights? o o How often do you watch MCU during the day on Sunday? o o How often do you watch MCU on Sunday nights? o o o o o o o o o o o o o o o o o o o o o o o o o o Q5.1 Screenwriters and Producers usually define the term BACKSTORY as the story that happens before the beginning of the main story that is seen on screen. Backstory gives us more context about the situations, relationships, or circumstances in the story and how a character becomes the person we meet at the beginning of the main story. 185 Please indicate how often have you done the following regarding the BACKSTORY of EVENT(S) in MCU AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a situation in a story better, imagine a backstory associated with the situation o o o o o o o To understand the conflict in a story better, imagine a backstory associated with that conflict o o o o o o o To understand some of the significant events in a story better, imagine a backstory associated with those events o o o o o o o To understand the protagonist in a story better, imagine a backstory associated with that character o o o o o o o 186 Q5.2 Please indicate how often have you done the following regarding the BACKSTORY of BLACK CHARACTER(S) in MCU AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a black character(s) better, do you ever imagine a backstory associated with that character(s). o o o o o o o To understand certain challenging circumstances faced by a black character(s), do you ever imagine a backstory associated with the formation of those circumstances? o o o o o o o To understand the crucial relationships of a black character(s) with other story characters, do you ever imagine a backstory o o o o o o o 187 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always associated with the formation of those relationships? To understand the motivations/choices made by a black character(s) better, do you ever imagine a backstory associated with those motivations of the character(s)? o o o o o o o Q5.3 Please indicate how often have you done the following regarding the BACKSTORY of FEMALE CHARACTER(S) in MCU AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a female character(s) better, do you ever imagine a backstory associated with that character(s). o o o o o o o 188 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand certain challenging circumstances faced by a female character(s), do you ever imagine a backstory associated with the formation of those circumstances? o o o o o o o To understand the crucial relationships of a female character(s) with other story characters, do you ever imagine a backstory associated with the formation of those relationships? o o o o o o o To understand the motivations/choices made by a female character(s) better, do you ever imagine a backstory associated with o o o o o o o 189 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always those motivations of the character(s)? Q5.4 Please indicate how often have you done the following regarding the BACKSTORY of WEALTHY CHARACTER(S) in MCU AFTER watching/reading it and thinking about it later: Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand a wealthy character(s) better, do you ever imagine a backstory associated with that character(s). o o o o o o o To understand certain challenging circumstances faced by a wealthy character(s), do you ever imagine a backstory associated with the formation of those circumstances? o o o o o o o 190 Hardly Almost Activity Never Ever Occasionally Sometimes Usually always Always To understand the crucial relationships of a wealthy character(s) with other story characters, do you ever imagine a backstory associated with the formation of those relationships? o o o o o o o To understand the motivations/choices made by a wealthy character(s) better, do you ever imagine a backstory associated with those motivations of the character(s)? o o o o o o o Q6.1 How much attention do you pay to the following topics or events in the media recently? Not at A A Moderate A A Great Topics or Events all Little Amount lot Deal The Black Lives Matter Movement o o o o o 191 Not at A A Moderate A A Great Topics or Events all Little Amount lot Deal The Me Too Movement o o o o o Political Leaders (e.g., Donald Trump, Joe Biden, etc.) o o o o o Business Leaders (e.g., Elon Musk, Bill Gates, etc.) Entertainment Celebrities Our current economic condition o o o o o o o o o o o o o o o Q3.3 Now think about how you currently watch television and answer the following questions. For each question, please check the appropriate circle. Questions Never Rarely Sometimes Often the Time Always Always Most of Almost How often do you watch television when you first wake up in the morning? o o o o o How often do you watch television in the afternoon? o o o o o o o o o 192 Questions Never Rarely Sometimes Often the Time Always Always Most of Almost How often do you watch television early at night? o o o o o o o How often do you watch television late at night, before going to bed? o o o o o o o How often do you watch television during the day on Saturday? o o o o o How often do you watch television on Saturday nights? o o o o o How often do you watch television during the day on Sunday? o o o o o How often do you watch television on Sunday nights? o o o o o o o o o o o o o 193