Entertaining Beliefs in Economic Mobility
Eunji Kim†
Conditionally Accepted at the American Journal of Political Science
Abstract
Americanshavelong believed in upward mobility andthe narrativeofthe AmericanDream.
Even in the face of rising income inequality and substantial empirical evidence that economic
mobility has declined in recent decades, many Americans remain convinced of the
prospects for upward mobility. What explains this disconnect? I argue that their media
diets play an important role in explaining this puzzle. Specifically, contemporary Americans
are watching a record number of entertainment TV programs that emphasize “ragsto-riches”
narratives. I demonstrate that such shows have become a ubiquitous part of the
media landscape over the last two decades. Online and lab-in-the-field experiments as well
as national surveys show that exposure to these programs increases viewers’ beliefs in the
American Dream and promotes internal attributions of wealth. Media exemplars present in
what Americans leisurely consume everyday can powerfully distort economic perceptions
and have important implications for public preferences for redistribution.
*I am grateful to Larry Bartels, Taylor Carlson, Michael X. Delli Carpini, , Josh Clinton, Danny Donghyun Choi, Jamie Druckman,
Daniel Q. Gillion, Andy Guess, Jessica Feezell, Daniel J. Hopkins, Yue Hou, Cindy Kam, Yphtach Lelkes, Michelle Margolis, Marc Meredith,
Rasmus T. Pedersen, Spencer Piston, Markus Prior, Hye Young You, Danna Young, nine anonymous referees as well as participants
at the MPSA, APSA, GWU, Harvard, Hertie School of Governance, Stony Brook, Texas A&M, WUSTL, and Yale. In particular, I owe a
truckful of gratitude to Diana C. Mutz and Matt Levendusky who believed in this project from the beginning. Kathleen Hall Jamieson of
the Annenberg Public Policy Center generously shared the Nielsen ratings data. I also thank an excellent team of research assistants who
helped the implementation of the lab-in-the-field experiments. This research was funded by the University of Pennsylvania’s Institute
for the Study of Citizens and Politics (ISCAP) and the 2018 GAPSA-Provost Fellowship for Interdisciplinary Innovation. This paper
received APSA’s 2020 Paul Lazarsfeld Best Paper Award, Wilson Carey McWilliams Best Paper Award, ISPP’s 2020 Roberta Sigel Early
Career Scholar Paper Award, and ICA’s 2019 Top Student Paper Award in Political Communication.
†
Corresponding Author. Assistant Professor of Political Science, Vanderbilt University. eunji.kim@vanderbilt.edu. Verification
Materials: The data and materials required to verify the computational reproducibility of the results, procedures and analyses
in this article are available on the American Journal of Political Science Dataverse within the Harvard Dataverse Network, at:
https://doi.org/10.7910/DVN/P4AH5C
Electronic copy available at: https://ssrn.com/abstract=3838127
Introduction
The promise of upward economic mobility is fundamental to national identity in the United States. In
a land free of a feudal past, Americans were “apt to imagine that their whole destiny is in their hands”
(de Tocqueville 1835, p.206), believing that if they worked hard, their economic circumstances would
improve. This belief that hard work guarantees success is such a cornerstone of the American ethos
that it has become known as the American Dream (Hartz 1955; Lipset 1997; McCloskey and Zaller
1984).
In recent decades, however, Americans have seen a simultaneous increase in income inequality and
decrease in economic mobility (Chetty et al. 2017; Piketty 2014; Stiglitz 2012). Absolute intergenerational
mobility rates—the fraction of children who earn more than their parents—have fallen by more
than 40% (Chetty et al. 2017). In this age of intensifying class stratification, concerns about the fading
American Dream have certainly dominated public discourse. Politicians from Joe Biden to Donald
Trump have argued that the American Dream needs to be restored (Biden 2020; Trump 2020).
Nevertheless, many Americans continue to view the United States as the land of opportunity and believe
that people can achieve upward mobility through hard work. Recent polls, for instance, show that
around 70% of American adults hold such beliefs (Gallup Organization 2019; see also George Washington
University Battleground Poll 2018). Even in the midst of a pandemic, more than half of Americans
remain optimistic (YouGov 2020). Academic studies also show that Americans substantially overestimate
the extent to which people actually experience upward economic mobility (e.g., Davidai and
Gilovich 2018; Kraus and Tan 2015). Why do Americans’ beliefs in economic mobility persist despite
the raft of empirical evidence to the contrary? More importantly, why do some Americans retain this
belief in upward mobility more than others?
I argue that the contemporary media environment provides an important and overlooked part of
the answer. An excellent body of political communication scholarship makes it clear that only a small
subpopulation makes it their hobby to devote much time to news consumption. Most citizens instead
consume an astounding amount of entertainment media (Arceneaux and Johnson 2013; Flaxman, Goel
and Rao 2016; Prior 2007). In the past two decades, this overlooked part of the media landscape has
featured many entertainment programs that offer powerful exemplars of real-life Americans succeeding
because of their hard work and talent. Shows that illustrate an ordinary person on a trajectory
2
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of upward economic mobility—what I broadly term “rags-to-riches” programs1
—are among the most
popular on television. One such show, America’s Got Talent, often attracts a prime-time audience seven
times larger than that of Fox News (Elber 2018). Another show, American Idol, used to attract contestant
vote totals that exceeded those of a typical American presidential election (Schwarz 2015). Such
popularity matters because this segment of reality TV shares a meritocratic narrative. When millions
of Americans sit down every evening and watch these programs, they continue to see evidence that
economic mobility—the American Dream—is alive and well.
In this article, I investigate whether and to what extent these rags-to-riches TV programs affect
perceptions of economic mobility and attributions people make about wealth and poverty. Using comprehensive
Nielsen ratings data and original content analysis, I first demonstrate that these programs
have exploded in popularity in recent years and that they propagate a narrative emphasizing that hard
work produces economic success. Using several original experiments conducted both online and in a
lab-in-the-field setting, I assess the causal effect of these programs on beliefs in the American Dream.
I find strong evidence of such effects, especially among self-identified Republicans who already believe
in rugged individualism. Findings from an original national survey are also consistent with the experimental
evidence. I find that exposure to rags-to-riches programs increases perceptions of economic
mobility and promotes beliefs that economic success can be attributed to internal, rather than structural,
factors. These effects are substantively important: regularly watching six or more rags-to-riches
TV shows like Shark Tank is as powerful as having immigrant parents in shaping beliefs in upward
mobility. In contrast, neither local economic context nor personal economic insecurity explains much
of the variation in beliefs in upward mobility.
I conclude by discussing the implications of the post-broadcast media environment for the study of
public opinion. Despite the astounding amount of entertainment media consumption, it is still mostly
viewed as a force that simply dilutes news media effects (Arceneaux and Johnson 2013). But when
so-called non-political media consistently offers positive and vivid exemplars of upward mobility to
citizens who mostly opt out of consuming counternarratives from the news, it can powerfully distort
mass economic perceptions. Further, this evidence offers a new explanation to the scholarly debate
about why rising inequality has failed to spur public demand for redistribution (Bonica et al. 2013; Nor-
1
Rags-to-riches stories do not exclusively refer to situations in which a person rises from poverty to wealth. I use this term—a common
archetype in literature and popular culture—to broadly refer to various trajectories of upward economic mobility and to refer to any
situation in which a person rises from obscurity to fame and celebrity.
3
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ton and Ariely 2011; Kenworthy and McCall 2008). By affecting beliefs in economic mobility—which
are well-known to legitimize free-market capitalism (Piketty 1995)—the rags-to-riches narratives that
prevail in the contemporary media environment exert a conservative influence over American politics
in this new Gilded Age.
Media Exemplars and Perceptions of Economic Mobility
Where do beliefs in upward economic mobility come from? Canonical writers from Alexis de Tocqueville
(1835) to Werner Sombart (1906) have proposed that widespread belief in economic mobility
is a reason why Americans lack class consciousness and tolerate wealth disparities, but we rarely attempt
to explain variations in these sentiments. Literature has pointed to path-dependent historical
factors, such as the Protestant work ethic or waves of frontier settlement (Kluegel and Smith 1986;
McCloskey and Zaller 1984; Verba and Orren 1985), but these cannot explain why many Americans
continue to believe in the prospect of upward mobility, despite the vastly changed economic reality,
nor why some believe in it more than others (Wolak and Peterson 2020).
Understanding perceptions of upward economic mobility2
requires dissecting the economic information
that people regularly consume and the types of exemplars it provides. Building on longstanding
public opinion scholarship that considers mass media to be the primary driver of sociotropic
economic perceptions (Mutz 1998; Soroka 2014), I consider how individual-level variations in perceptions
of economic mobility are a function of exposure to mass media and the exemplars they offer. To
keep my hypotheses parsimonious, I follow the conventional conceptualization in which the news and
entertainment media are the two main building blocks of the mass media system. I consider the extent
to which these two types of media are relevant to understanding beliefs in the American Dream, paying
particular attention to the types of accessible exemplars each provides.
In sync with the news media’s well-known tendency to over-report negative economic information
(Soroka 2006) and the worsening economic realities of the new Gilded Age, it is no surprise that the
news media typically offer information about downward economic mobility. The news media have
devoted considerable attention to rising income inequality, with a consistent focus on highlighting the
2
I focus on sociotropic perceptions because citizens’ economic perceptions about collectives—as opposed to egotropic perceptions—play
a central role in shaping political attitudes (Feldman 1984; Kinder and Kiewiet 1981)
4
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diminishing prospects of upward mobility for the American working and middle classes (Diermeier
et al. 2017; Eshbaugh-Soha and McGauvran 2018; McCall 2013). Indeed, as seen in Figure 1, sentiments
in news coverage about economic mobility in America have been predominantly negative over the last
two decades. In theory, these patterns should have heightened citizens’ concerns about the prospects
for upward mobility, yet we still observe sustained beliefs in economic mobility.
Figure 1: The Sentiment Analysis of News Coverage on Economic Mobility (2000-2019)
−400
0
400
2000 2005 2010 2015 2020
Year
SentimentScore
Note: The sentiment score is calculated using the Bing Lexicon that categorizes words in a binary fashion into positive and negative
categories. Values below zero indicate negative sentiment. The corpus consists of a total of 9,341 New York Times articles that contain
the phrases related to economic mobility (i.e. upward mobility, land of opportunity, self-made success). See Appendix C for details.
In the meantime, entertainment media—whose purpose is to “entertain” people—tends to offer
uplifting exemplars of people who achieve upward economic mobility, ones that are more vivid and
accessible than real-world examples (Busselle and Shrum 2003). This idea indeed has a long scholarly
lineage. For instance, Harold Lasswell’s (1936) seminal book Politics: Who Gets What, When,
How asserts that Hollywood films hammer messages of upward mobility into citizens’ brains. Explaining
the paradox of why most low-income African Americans believe they can achieve the American
Dream, Jennifer Hochschild (1996) claims that “(television) shows with black male leads” are devoted
to “portraying the attractions and ignoring the dark side of the American dream” (p. 136). Similar
speculations can be found across myriad qualitative cultural and sociological studies that explore the
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links among American popular culture, belief in the American Dream, and the absence of class conflict
in America (Murray and Ouellette 2004; Pines 1993).
Although entertainment media is a much-overlooked source of economic information, decades
of work on cultivation theory suggests that entertainment media exert at least as much influence as
the news media on politically relevant attitudes. Many of our attitudes about political issues—ranging
from crime to social welfare—are shaped by exposure to entertainment television (e.g, Holbrook and
Hill 2005; Morgan and Shanahan 2010). Further, through their narrative presentations of information,
viewers experience the phenomenon of “transportation,” a cognitive and emotional experience
in which viewers immerse themselves in a story (Green, Brock and Kaufman 2004). Such narrative
persuasion in entertainment media is much more powerful than rhetorical persuasion via political
messages, as people are less likely to develop a counterargument or critically scrutinize such a message
(Jones and Paris 2018).3
Indeed, a growing body of natural and field experimental evidence finds that
entertainment media powerfully alter the dynamics of electoral processes (Durante, Pinotti and Tesei
2019; Xiong Forthcoming) and change the important social outcomes ranging from school enrollment
rates to eating habits and White supremacist activities (Jensen and Oster 2009; Ang 2020; Paluck et al.
2015).4
Taken together, these theories tell us that both news and entertainment media have power to shape
perceptions of economic mobility, with each type pushing them in opposite directions. The net impact
of media exposure, therefore, depends on the overall composition of media consumption. I contend
that the effect of the narrative of upward mobility from entertainment media is powerful, given that
most Americans choose to avoid news and spend an enormous amount of time watching entertainment
media instead. This imbalanced exposure to entertainment media may explain individual variations in
upwardly distorted perceptions of economic mobility. To test this, I develop empirically falsifiable hypotheses
that specify which type of entertainment media matters for perceptions of upward economic
mobility. Rather than leaving entertainment media unarticulated as a concept, I propose that three
components—the presence of everyday American, visible financial gains, and narrative emphasis on
meritocracy—comprise the rags-to-riches narrative that dominates parts of the entertainment media.
3
Several survey experimental studies have also demonstrated that non-political media influence real-world political attitudes (Mulligan
and Habel 2011; Mutz and Nir 2010.)
4
The “entertainment-education” initiatives that weave educational messages into short entertainment programs have been widely used
in public health interventions (Singhal et al. 2003) and found to be more effective, for instance, at reducing inter-group prejudice than
traditional methods (Murrar and Brauer 2018; Paluck 2009).
6
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Rags-to-riches programs, a subset of reality television, have three distinctive components that I hypothesize
shape viewers’ beliefs about upward economic mobility. First, they feature everyday American
citizens, not hired actors or celebrities. Successful entertainment content requires relatable characters
and believable storylines, elements that even children can list (Moyer-Gusé 2008). Featuring
ordinary Americans dramatizes the representation of reality and offers a convenient point of identification
for the viewer. Watching a working-class janitor or waitress become a celebrity overnight or
earn most of a year’s income in one month suggests that these things can happen to anyone, not just
to those from wealthy families or who have a post-secondary education. These glorified everymen can
serve as a social reference group and provide viewers with more relatable vicarious experiences (Reiss
and Wiltz 2004).
Second, these rags-to-riches shows generate and dramatize economic benefits such as a milliondollar
prize, a lucrative contract, a coveted job, or a brand-new house. Entertainment media writ large
are dominated by positive and upbeat stories, but these rags-to-riches shows in particular emphasize
the visible economic benefits obtained by those who take part. The economic component is important
because a general level of optimism toward life is conceptually different from holding an optimistic
view of the US as the land of economic opportunity.
Third, rags-to-riches shows tend to emphasize that economic outcomes are determined by hard
work and merit by portraying their beneficiaries as deserving. The notion of meritocracy is deeply
embedded in the American Dream, and these programs tend to highlight people’s humble backgrounds
and economic hardships in order to lionize their later success. Contestants routinely speak of how
they were not born with privileges and how they never gave up on their dreams, even while holding a
minimum-wage job, facing soaring medical bills, or receiving rejection after rejection from investors.5
Indeed, a frequent folk hypothesis is that these programs “reignited Horatio Alger’s imagination in the
modern world” (Cromewell 2015) and promoted “the national myth of meritocracy” (Anzuoni 2016).
Defining these three components of the rags-to-riches narrative is methodologically important for
this systematic study of their effects on perceptions of economic mobility. Many previous studies have
examined the effects of a single TV program or a few similarly themed episodes (e.g., Butler, Koopman
5
Several examples are: “I think I am living proof of the American dream. My parents emigrated here with $100 in their pocket from
Guyana, and look at me now. I just got a deal from Mark Cuban on Shark Tank.” (Krystal Persaud, Shark Tank); “I can’t be cleaning
pools forever. [...] I’ve literally been climbing a mountain to get my voice heard, and today is the day to reach the top.” (Blaise Raccuglia,
The Voice). See more quotes in Appendix D.
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and Zimbardo 1995; Lenart and McGraw 1989). But their net impact has been unclear because different
programs, or different episodes of the same program, typically contain various, sometimes competing,
types of messages and plot lines. This problem has long plagued research on the effect of non-political
media. In the next section, I establish the premise of this study by using detailed Nielsen ratings data,
a comprehensive online entertainment media database, and original content analyses to demonstrate
that rags-to-riches programs have become a ubiquitous part of the American media landscape over the
last two decades.
The Rise of “Rags-to-Riches” Entertainment Programs
Ranging from American Idol to Shark Tank, TV programs that feature real-life, everyday Americans—
widely referred to as reality TV shows—have been a ratings juggernaut that has dominated the American
media market during the past two decades (DeVolld 2016; Livingstone 2017). These observations
can be empirically confirmed. Using 102,523 TV programs—including those on popular streaming
services such as Netflix—released between 1960 and 2017 (N=102,523) as recorded in IMDb,6
I find a
clear surge in the number of reality/games shows starting in early 2000. By around 2008, one in five
newly released TV programs was a reality show (See Appendix B, Figure 1). The cheaper production
costs of reality shows featuring ordinary Americans also contributed to the increasing supply, leading
many critics to declare that we are living in the golden age of reality TV (Rosa 2019; Yahr, Moore
and Chow 2015).7
In the meantime, the relative share of news programs has remained stable. While
the absolute amount of news programming has increased in recent decades, the relative share of such
programming in the overall media supply has not increased (Van Aelst et al. 2017). This decreasing
share of news programming means that it is now easier to consume media while avoiding political news
altogether (Prior 2007).
Granted, not all reality TV shows broadcast narratives of upward mobility. Those that feature stories
about the undeserving rich would not have the same implications for real-world phenomena as the
ones that feature ordinary hard-working Americans (Condon and Wichowsky 2020). But, with the
6
This database, one of the most comprehensive media databases, contains information about programs’ release years, their genres, and
many other characteristics.
7
Indeed, there were 750 reality programs were aired on prime-time cable in 2015 (VanDerWerff 2016) alone, and most Americans are
watching reality TV show even when they think that there’s too much of it (Shevenock 2018). The pandemic also led to the increase in
reality TV viewership across networks and channels (Aurther 2020; Jones 2020).
8
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exception of Desperate Housewives in the 2004-2006 and 2007-2008 TV seasons, all the reality shows
that were among the 10 most watched programs from 2000 to 2017 had a competitive format that
featured a narrative of the American Dream (See Appendix B, Table 1). American Idol, for instance,
was the most watched program for eight consecutive seasons, from 2003 to 2011. None of the 10 most
watched TV shows over the last two decades was a news program; in stark contrast, 60 Minutes (CBS)
was a top-10 show from 1977 to 2000.8
To better establish that the rags-to-riches narrative is widespread, I conducted a content analysis focusing
on the three components I argue are essential to cultivating beliefs in upward mobility: whether
the TV program featured (1) ordinary Americans (2) working hard to (3) achieve considerable economic
benefits. First, I coded whether a program featured everyday Americans—such as small business
owners, home-based cooks, amateur singers, food-truck owners, and so forth—or celebrities and
expert professionals. Second, I coded the degree of economic benefits contestants received from winning.
Recognitions and prizes with clear implications for contestants’ career and business prospects
(e.g., a recording deal, a business contract, or a million-dollar cash prize) were coded as significant
benefits. Booby prizes, bragging rights or a paid date night were coded as trivial benefits. Finally, I
indicated the extent of hard work and effort that each show required in order to win. Programs that
were clearly merit-based and dramatize the process of working hard—ranging from Shark Tank (ABC)
to MasterChef (FOX)—were coded as “a lot of effort,” while dating shows or trivia quiz shows were
coded as “not much effort.”
I matched Nielsen ratings data from September 2015 to August 2017 with the Encyclopedia of Television
Shows 1925–2016 (Terrace 2012, 2017) and the TV Tango.com database to identify TV shows
that are classified as reality/game shows. Of the 8,701 entries of non-fictional entertainment shows
that aired between 2015 and 2017, Nielsen identified 3,362 as reality/game shows. I narrowed this list
to shows that had a competitive format, because the ideology of meritocracy and the self-made person
is closely tied to competition and amplified in the face of unequal outcomes (McNaMee and Miller Jr
2014). (See Appendix A, which summarizes the results of the content analysis for each element). About
71.3% of the competitive reality/game shows that aired between 2015 and 2017 had all three elements
of the rags-to-riches narrative, while only 1.8% had none of these elements.
Such programs not only offer a powerful lesson about hard work leading to success; they also broad-
8
See https://www.cbsnews.com/news/60-minutes-milestones/
9
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cast this message to a huge audience. Nielsen ratings data suggest that the most popular shows have
all three elements. Eight of the 10 top-rated programs that attracted more than four million regular
viewers featured a rags-to-riches narrative. To put their popularity in perspective, consider that Fox
News attracts three million prime-time viewers on average while seasonal average audiences for the
popular rags-to-riches reality shows America’s Got Talent and The Voice are usually over 10 million
(Concha 2019; Porter 2019; Throne 2019). Even in the midst of a pandemic that witnessed a surge in
news viewership, another new competitive reality TV program, Lego Masters (FOX), attracted a larger
audience than any of the cable TV news programs (Pucci 2020). The remaining question is: do the
contents of rags-to-riches TV affect public economic perceptions?
The Impact of Rags-to-Riches TV on Beliefs in Upward Mobility
Experimental Evidence
Figure 2: The mobile media laboratory
Having established the prevalence of rags-to-riches programming, I turn now to whether such programming
actually shapes citizens’ perceptions of economic mobility. To explore the causal effects of
rags-to-riches entertainment media, I conducted online and lab-in-the-field experiments, which took
place in October 2016 and in July-September 2018 respectively. I recruited 763 respondents online
through Amazon’s Mechanical Turk and 203 respondents offline in suburban New Jersey and Pennsylvania.
To obtain enough partisanship variation in the sample, Bucks, Lehigh, Northampton, and Salem
10
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counties were chosen based on their 2016 presidential election results.9
For the lab-in-the-field experiments,
I used a mobile media laboratory as shown in Figure 2. The vehicle—a big box truck—had
two separate rooms, each equipped with a TV screen and a chair. I drove to non-political events that
attract local residents of various ages, such as farmers’ markets, flea markets, and summer festivals. A
team of field assistants and I recruited participants on site. They were told that they would be watching
entertainment media and asked to share their thoughts in exchange for $10 in cash compensation (See
Appendix I).10
Although the setting and time of the data collection varied, all respondents were asked a similar set
of questions about their general attitudes about the American Dream.11
Respondents indicated the extent
to which they agreed with each of four statements: (1) “Anyone who works hard has a fair chance
to succeed and live a comfortable life.;” (2) “It is possible to start out poor in this country, work hard
and become well-off;” (3) “United States is no longer the land of opportunity;” and (4) “Most people
who want to get ahead can make it if they’re willing to work hard.” Respondents indicated the extent
to which they agreed with each statement. I averaged these four questions into one index—Beliefs in
Economic Mobility (Cronbach α= 0.75)—that ranged from 0 to 1, with higher values indicating more
optimistic views about the prospect of economic mobility. To increase the efficiency of the experimental
design by further accounting for pre-existing tendencies to believe in upward economic mobility,
this survey included partisan identification, a system justification scale, and an optimism scale. These
characteristics were expected to enhance the likelihood of believing in upward economic mobility after
being exposed to experimental stimuli.
Treatments
Given that the purpose of this experiment was to test the effects of media content that was typical
of a broad genre, rather than the effects of any one show, I constructed four treatments using different
rags-to-riches TV shows: Shark Tank, America’s Got Talent, American Ninja Warrior, and Toy Box.
These four shows were chosen after I conducted a pilot test using 14 different TV shows that featured
ordinary Americans achieving economic gains. (See Appendix J).
The Shark Tank treatment featured two young entrepreneurs who were pitching their start-up busi-
9
47.8%, 45.9%, 50.0%, and 55.6% of the total county votes, respectively, were cast for Donald Trump.
10
Because of the nature of lab-in-the-field experiments that recruit respondents on site—with some expressing reluctance while others
participating out of curiosity—the survey was intentionally designed to be short.
11
IRB Protocol 828418.
11
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ness product to a panel of judges who were business investors. They explained how they developed the
idea of caffeinated, chewable coffee pouches in their dorm room, and how they put effort into boosting
sales by contacting professional athletes. At the end of the treatment video, they got a successful
business deal. The America’s Got Talent treatment was about a young female singer-songwriter who
was deaf. After telling the story of her arduous journey as a singer without full hearing, she broke into
a song that she had written. At the end of her performance, the entire audience cheered and one of the
judges hit a golden buzzer, which sent the contestant into the next round’s live show. The American
Ninja Warrior treatment featured a young married male contestant competing for a one-million-dollar
award. In a brief biographical sketch, he was featured with his newborn baby and told how he would
be able to pay for a high-quality education for his son if he won. The treatment video ended with him
finishing an obstacle course in record-breaking time. The Toy Box treatment showed an elderly female
toymaker pitching a multilingual doll she invented to representatives of major toy-making companies.
She explained how she spent years developing this toy and faced many financial challenges in the
process. The video ended with her doll being endorsed and chosen by the judges.
Although these shows had different formats and contestants, the treatments—all edited to last less
than five minutes—highlighted very similar storylines of upward economic mobility. To ensure that the
treatment effects were driven by an upward economic mobility message rather than the particularities
of reality TV shows, I included a control media treatment that lacked a narrative of economic mobility.
The control treatment contained scenes from Cesar 911, a reality TV show that featured a young woman
seeking advice about her dog’s aggressive behavior. The dog behavior authority evaluated her pet, and
equipped the dog owner with knowledge and tools to address the aggression. The control treatment
ended with a well-behaved dog and a satisfied owner. The control treatment was chosen primarily
because the quality of life of the ordinary American featured on the show improved without any visible
financial gains. Manipulation checks successfully demonstrated that the experimental treatments did
convey the components I hypothesized were necessary for a belief in upward economic mobility.12
Results
My experiment shows that exposure to rags-to-riches entertainment media increases people’s beliefs
in upward economic mobility. As shown in Table 1, in the full-sample models with covariates
(Columns 1 and 5), watching a rags-to-riches program, even just for five minutes, makes people ap-
12
See Appendix K for full manipulation check results.
12
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proximately 5.5 to 6.8 percentage points more likely to believe in the prospect of upward economic
mobility. To put this into context, in the control condition for the lab-in-the-field sample, the partisan
gap in belief in the American Dream is 10.87 percentage points. In other words, the treatment effect is
substantial: more than half the size of the gap between Democrats and Republicans. A general level of
optimism and the system justification scale were all positively correlated with a post-treatment belief
in economic mobility. But the main treatment effects remained similar even after controlling for those
covariates.
Table 1: The effect of rags-to-riches TV on belief in economic mobility
DV = Beliefs in Economic Mobility
MTurk Sample Lab-in-the-field Sample
All Rep Dem Interaction Model All Rep Dem Interaction Model
(1) (2) (3) (4) (5) (6) (7) (8)
Rags-to-Riches TV Treatment 0.055∗∗∗ 0.150∗∗∗ 0.011 0.010 0.068∗∗ 0.085+ 0.061 0.066+
(0.011) (0.020) (0.017) (0.016) (0.025) (0.047) (0.037) (0.035)
Republican 0.036∗ 0.047
(0.015) (0.038)
Democrat −0.015 −0.057+
(0.012) (0.034)
Optimism Index 0.025∗∗∗ 0.032∗∗ 0.020∗ 0.024∗∗∗ 0.048∗∗ 0.019 0.064∗ 0.049∗
(0.006) (0.012) (0.009) (0.007) (0.018) (0.030) (0.028) (0.021)
System Justification Scale 0.090∗∗∗ 0.071∗∗∗ 0.092∗∗∗ 0.086∗∗∗ 0.101∗∗∗ 0.085∗∗ 0.142∗∗∗ 0.121∗∗∗
(0.007) (0.013) (0.010) (0.008) (0.018) (0.031) (0.028) (0.022)
Rep (vs Dem) −0.017 0.075
(0.020) (0.046)
Rags-to-Riches TV x Rep (vs Dem) 0.140∗∗∗ 0.035
(0.028) (0.063)
Constant 0.187∗∗∗ 0.211∗∗∗ 0.203∗∗∗ 0.208∗∗∗ 0.193∗ 0.403∗ −0.037 0.082
(0.024) (0.051) (0.034) (0.028) (0.084) (0.152) (0.127) (0.099)
Observations 763 161 348 509 203 50 109 159
R2 0.326 0.443 0.250 0.364 0.311 0.274 0.333 0.348
Note: Cell entries are OLS regression coefficients with associated standard errors in parentheses. The dependent variable is coded to range from 0 to 1, with 1 indicating stronger beliefs in
economic mobility. Columns 5-8 included survey date/location fixed effects. + p< 0.1, * p<0.05; ** p<0.01; *** p<0.001
I also find heterogeneous treatment effects by Party ID. The effects of rags-to-riches TV are statistically
significant among Republicans, albeit weakly in the lab-in-the-field sample (Columns 2 and
6), but not among Democrats (Columns 3 and 7). To formally test this difference, Columns 4 and 8
show the results of the interaction model. Note that the small size of the lab-in-the-field sample prevents
the precise estimation of interaction term. Given that the “pull yourself up by your bootstraps”
dictum is closely associated with Republican ideology, this suggests that the treatment video resonates
more strongly among those who already believe in the importance of economic individualism. As
additional evidence for this mechanism, I find that the treatment effects are larger among those who
tend to defend and rationalize existing social systems (Appendix K)13
—a pattern consistent with existing
evidence that Democrats tend to score consistently lower on system justification than Republicans
13
Similarly, Stavrositu (2014) finds that watching competition-based TV cultivates system-justifying beliefs and life satisfaction.
13
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(Jost, Banaji and Nosek 2004).14
It is worth noting that I conducted a conservative test: while my participants only watched a single
five-minute clip of rags-to-riches entertainment media, Nielsen ratings data confirm that many Americans
choose to watch these programs for more than an hour every evening. The experimental findings
here provide causal evidence on how media exemplars of upward mobility in entertainment media
shape beliefs in the American Dream. When survey participants are forced to consume pessimistic,
news-like economic information on declining economic mobility, they become more supportive of redistribution
(Alesina, Stantcheva and Teso 2018)—a pattern not found across different observational
data (Ashok, Kuziemko and Washington 2016; Kenworthy and McCall 2008). The effects of rags-toriches
media found here can shed light on this discrepancy. Indeed, in supplementary lab-in-the-field
experiments, I find that the meritocratic narrative in rags-to-riches TV programs promotes the idea
that rich people have more because of their hard work, dampens public support for redistribution, and
increases their tolerance of income inequality (See Appendix L).
Granted, there is no reason to believe that those who participated in the lab-in-the-field experiments
as well as MTurk respondents were truly representative of the general adult population in
America. Households in Quakertown, PA, for instance, have a slightly lower median annual income
($54,068) than the national average ($60,336), and it is a racially homogeneous suburban town where
86.5% of residents are White. Compared to the national representative sample, MTurk subjects are
notably younger and much less likely to own a house (Berinsky, Huber and Lenz 2012). To investigate
whether the effects of rags-to-riches TV are observable among the general population, I next turn to
national surveys.
Observational Evidence
I designed a national survey that Survey Sampling International (SSI) administered to 3,004 US residents
in August 2018.15
I present full details of the survey in Appendix E and summarize key elements
here. My goals in this step were to demonstrate that the effects of rags-to-riches entertainment media
are observable among the general population and that these effects can be distinguished from those of
14
Because of the logistical challenges of lab-in-the-field experiments and time constraints, I did not collect demographic variables.
15
SSI, now known as Dynata, used targeted recruitment to ensure that the survey sample closely matched US Census benchmarks for
education, income, age, gender, geography, and race/ethnicity.
14
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exposure to any reality TV program regardless of its narrative. This step also contextualizes the media
effects by testing the extent to which people’s real-world economic context and personal economic
experiences shape perceptions of economic mobility.
Key variables
The key outcomes of interest are (1) beliefs in economic mobility and (2) attributions of economic
success. I used instruments similar to those in the previous experiments to create an index—Beliefs
in Economic Mobility (Cronbach α = 0.86)—that ranged from 0 to 1, with higher values indicating
more optimistic views about the prospect of economic mobility. The survey also included a battery of
questions about why some people get further ahead than others. Respondents were given a list of eight
explanations, half of which were internal factors (ambition, self-determination, hard work, and talent)
and half of which were external factors (family wealth, well-educated parents, technological changes
and automation, and politicians’ failure to implement good policies). I averaged these four questions
into two indices—Internal Attribution and External Attribution—(Cronbach α = 0.71, 0.63) that ranged
from 0 to 1, with higher values indicating beliefs that economic success is a result of those factors.
I measured media consumption of rags-to-riches programming at the show level (see Dilliplane,
Goldman and Mutz 2013 for measurement validation). Respondents were shown a list of 30 TV
programs, which included 12 rags-to-riches reality programs, eight reality/game shows that featured
celebrities or ordinary Americans who were not competing for economic benefits, and 10 sports programs.
They were asked to mark all programs that they have regularly watched. The 12 rags-to-riches
programs were selected based on three criteria. First, they all illustrated the three components I argue
are essential to affecting beliefs in upward mobility: they featured (1) ordinary Americans (2) working
hard to (3) achieve considerable economic benefits. Second, the size of their two-year average audience,
according to Nielsen ratings data, was larger than one million. Third, these shows all aired in
2018.
For ease of interpretation, the key independent variable, rags-to-riches media consumption, is constructed
as a categorical variable, with the cutoff group line based on quintile values (see Appendix F
for the analysis with media consumption as a continuous variable). The baseline category is those who
watch zero rags-to-riches programs. Occasional viewers are coded as those who watch one or two ragsto-riches
programs. Frequent viewers are coded as those who watch three to five programs. Those who
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watch six or more are coded as heavy viewers.
The other programs were included to address alternative hypotheses and spurious relationships.
I included 10 popular sports programs because past studies have argued that sports exemplify meritocracy,
and that sports fandom is linked to internal attributions for economic success (Thorson and
Serazio 2018). The eight non-meritocratic reality/game programs on the list featured celebrities, or
spotlighted ordinary people who were not necessarily hard working and were not perceived to have
gained economic benefits. These were included to address the possibility that people who like to watch
reality programs, regardless of their content and overarching narrative, have unobservable differences
that make them more likely than non-viewers to believe in the prospect of upward economic mobility.
The survey design also included many alternatives to rags-to-riches media consumption that, according
to existing theories and studies, can affect sociotropic perceptions of economic mobility. Consistent
with the high Nielsen ratings of the programs included in the survey, 72% of survey respondents
watched one or more rags-to-riches TV programs. There was no partisan difference in the number of
rags-to-riches programs people regularly consumed (p=0.735).
Results
I examine how Americans’ rags-to-riches media consumption relates to their beliefs in upward mobility
and the extent to which people think that internal, rather than structural, factors are attributed
to economic success. Columns (1), (3), and (5) of Table 2 present a parsimonious model with no covariates;
Columns (2), (4), and (6) include other individual-level covariates and county-level economic
contexts that may contribute to sociotropic perceptions of economic mobility.
The controls include the total count of sports programs and other entertainment shows that respondents
regularly watch, in addition to the following covariates: age, gender, race, income, employment
status, party ID, Protestant, religious attendance, marital status, political interest, and state fixed effects.
To account for personal economic experiences that are frequently linked with the American
Dream, the model also includes respondents’ perceptions about their own intergenerational mobility
experiences, whether either of their parents was an immigrant, and personal economic insecurity. A
general level of optimism about life was also included. To take geographic context into consideration,
the model included county-level absolute intergenerational mobility rates and the Gini index of income
inequality.
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Table 2: The correlation between rags-to-riches TV and belief in upward mobility as well as attributions of
economic success
Belief in Economic Mobility Internal Attribution External Attribution
(1) (2) (3) (4) (5) (6)
Occasional Viewer (1-2 Programs) 0.019 0.013 0.006 0.013 −0.004 −0.007
(0.012) (0.011) (0.010) (0.010) (0.009) (0.009)
Frequent Viewer (3-5 Programs) 0.047∗∗∗ 0.032∗∗ 0.008 0.017+ 0.009 0.005
(0.012) (0.011) (0.010) (0.010) (0.009) (0.010)
Heavy Viewer (6+ Programs) 0.076∗∗∗ 0.040∗ 0.052∗∗∗ 0.052∗∗∗ 0.039∗∗∗ 0.014
(0.013) (0.016) (0.011) (0.014) (0.011) (0.013)
Controls Included:
Other media consumption N Y N Y N Y
Demographics N Y N Y N Y
Personal economic context N Y N Y N Y
County-level economic context N Y N Y N Y
State fixed effect N Y N Y N Y
Observations 3,004 2,998 3,004 2,998 3,004 2,998
R2 0.013 0.239 0.008 0.143 0.006 0.110
Note: Cell entries are OLS regression coefficients with associated standard errors in parentheses. + p< 0.1, * p<0.05; ** p<0.01; *** p<0.001
The top three rows in Columns 1 and 2 show the difference in the probability of believing in upward
mobility for occasional, frequent, and heavy viewers compared to those who do not watch any ragsto-riches
TV programs. The gap between non-viewers and occasional viewers was only 1.3 percentage
points, and was not statistically significant. The gaps between non-viewers and frequent viewers and
between non-viewers and heavy viewers, however, were both statistically significant. Those who regularly
watch more than six rags-to-riches programs, for instance, were 4 percentage points more likely
to believe in the American Dream. Heavy viewers were also more likely than non-viewers to attribute
economic success to internal factors. The relationship between exposure to rags-to-riches programs
and external attribution was less robust; as Column 6 shows, rags-to-riches media exposure had no
explanatory power when I added an array of control variables. In addition, I find that the effects of
rags-to-riches TV programs are stronger among those who are less interested in politics (Appendix F).
To better contextualize the explanatory power of rags-to-riches entertainment media against other
factors, Figure 3 shows the predicted change in beliefs in upward mobility from a one-SD change in key
variables from the regression model reported in Table 1 Column (2). Partisanship clearly matters: being
a self-identified Republican is the biggest predictor of beliefs in economic mobility (See also Alesina,
Stantcheva and Teso 2018; Manza and Brooks 2021). Respondents who perceive their life as better than
that of their parents and those who have immigrant parents were more likely to believe in the American
Dream. This is consistent with existing theories on how upwardly mobile individuals learn from their
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Figure 3: The predicted change in beliefs in upward mobility
Note: The figure shows predicted change in beliefs in upward mobility from a one-SD change in each of key variables from the model
reported in Table 1 Column 2. The full model is reported in Appendix F.
own experiences and update their economic beliefs about redistributive politics (Piketty 1995). The
generational divide in beliefs in the American Dream is worth noting as well. Older people—who
watch much more television than young adults—are more optimistic. This may reflect the fact that
one’s chances of upward mobility are likely to be greater over a much longer time frame (Chambers,
Swan and Heesacker 2015). It may also be a result of the economic disruption that millennials have
experienced during their early years in the labour market. Those who went through a recession when
young believe that success in life depends on luck more than on hard work (Giuliano and Spilimbergo
2014).
These all suggest that both macro-structural forces and personal experiences shape American economic
beliefs. Yet it is noteworthy that rags-to-riches entertainment media consumption does play an
important role. Indeed, regularly watching six or more TV programs like America’s Got Talent is as
powerful as having immigrant parents in shaping beliefs in economic mobility. Its relative predictive
power is in stark contrast with the null effects of many other covariates—such as race and income—
that have been reported as important in the previous literature (Hochschild 1996). Neither countylevel
intergenerational mobility rates nor local income inequality had much explanatory power. The
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pioneering study by Raj Chetty and his colleagues quantified the extent to which children born in the
Deep South have starkly lower chances of achieving upward mobility than those from the coastal cities
(Chetty et al. 2014). Yet such geographic variation in economic reality seems not to matter much in
shaping beliefs in the American Dream. The main findings here are replicated with two nationally
representative surveys.16
Taken as a whole, these observational findings confirm that rags-to-riches
entertainment media is correlated with beliefs in the prospect of upward economic mobility and that
economic success is attributed to internal factors.
Discussion and Conclusion
What sustains beliefs in the prospect of upward economic mobility in America? Social science literature
points to an extensive list of historical factors unique to the United States—such as the existence of
the frontier or the Protestant work ethic—and concludes that belief in the American Dream is “just
deeply embedded in American mythology...and myths last because they are dreams fulfilled in our
imaginations” (Hanson and White 2011, p.7; see also Hochschild 1996; McCloskey and Zaller 1984).
I argue that perceptions of economic mobility must be understood alongside the media discourse
and environment, just like any other sociotropic economic perceptions. Unlike much of political science
scholarship, which assumes that the news media are the primary source of politically relevant information,
I highlight that the media content that Americans watch the most—entertainment media—
offers powerful exemplars of upward mobility and serves as an important source of information that
affects people’s beliefs in the American Dream. Although the findings here are cross-sectional evidence,
trends over the last three decades suggest that people who watch a lot of television have become
more optimistic about the American Dream (Appendix L).
The duration of entertainment media effects—the possibility that these media effects fade away
after a short time—should be explored in future studies. In the meantime, the methodological advantages
of focusing on shared rags-to-riches narratives are clear, because these messages remain the
same across different episodes and programs. If anything, the sheer availability and popularity of these
programs alleviate concerns about external validity. Even if the public’s taste for shows that feature
16
Though they have a far less detailed information on entertainment media consumption, they do allow me to replicate the finding with
nationally representative data.
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ordinary Americans dissipates, the challenges of producing high-cost scripted shows in a fragmented
media market have led to expectations that the vast majority of cable TV shows will continue featuring
everyday Americans (Ralph Bunche Center 2015). For the same financial reasons, streaming services
such as Netflix, Amazon, and HBO now produce their own reality programs that have a similar ragsto-riches
narrative (e.g., Making the Cut and Next in Fashion).
My results underscore the overdue need to expand the scope of political communication and public
opinion research beyond news. The mass media has long been known to influence citizens’ sociotropic
perceptions, but mainstream social science research usually equates mass media with news media.
Despite dramatic changes in the media environment, the scholarly focus on news has remained intact.
The most prominent works of political communication in recent years confirm a focus on traditionally
defined “political” aspects. Scholars have richly documented the political consequences of dwindling
news audiences (Prior 2007), partisan media (Arceneaux and Johnson 2013; Levendusky 2013), soft
news (Baum 2011), social media (Settle 2018), and fake news (Guess, Nyhan and Reifler 2020), among
other considerations.
Though behavioral evidence suggests that most Americans tune out the news (Flaxman, Goel and
Rao 2016; Guess 2020), very little attention has been paid to the political content that is present in what
they are watching instead. Entertainment media are still deemed worthy of studying only when they
affect ostensibly political variables (Delli Carpini 2014). As long as economic perceptions are central
to the study of politics, however, this category of non-political programs that affect such perceptions
can no longer be dismissed. Furthermore, studying entertainment media consumption may provide
answers to many questions about distortions and biases in public opinion. Widespread American misperceptions
about the criminal justice system, for example, could be better understood if we account
for the fact that America’s most popular network TV shows have consistently been police procedurals
such as NCIS (Byers and Johnson 2009).
My findings also shed light on the continuing debate about why the United States has largely failed to
address the rising level of economic inequality. One critical part of the answer is institutional. Government
policies that could have addressed the wealth disparity did not materialize because of legislative
polarization, institutional features that bias policy outcomes toward the status quo, and a campaign
finance system that allows unequal access, to name a few (for a summary, see Bonica et al. 2013). Yet it
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is the public opinion part of the answer that has intrigued many. Scholars have been perplexed to find
that citizens are generally moving away from more egalitarian policy preferences as the income gap
widens (Ashok, Kuziemko and Washington 2016; Kenworthy and McCall 2008), a pattern that defies
the predictions of the workhorse political economy model (Meltzer and Richard 1983).
To solve this puzzle, existing empirical research points out the misperceived level of inequality
(Hauser and Norton 2017; Chambers, Swan and Heesacker 2015), system justification motivations
(Trump 2018), lay perceptions of government costs and benefits (Porter 2020), and trust in government
(Alesina, Stantcheva and Teso 2018), among many others. But across all these studies, scholars
consistently refer to one dominant explanation as a “time-honored tradition” (McCall 2013, p. 56):
the distinctiveness of the liberal individualism rooted in American political culture (see also Feldman
1984; Lipset 1997). The paradox is that though many agree that beliefs in upward mobility are central
to understanding how Americans react to economic inequality, there has been no serious attempt to
amass empirical evidence to determine which aspect of American culture affects such economic beliefs
or the extent of that influence.
My findings here make it clear that rags-to-riches entertainment media are an important cultural
force that promotes and perpetuates beliefs in upward mobility. The “puzzling” patterns in public attitudes
toward redistribution are less so if we take into account the fact that Americans are reportedly
watching four hours of television every day (Koblin 2016) and are receiving distorted information about
upward mobility. Belief in economic mobility can powerfully legitimize wealth disparity (Kluegel and
Smith 1986; Shariff, Wiwad and Aknin 2016), and scholars of class and inequality should recognize
that non-political mass media cultivate foundational aspects of American politics, such as beliefs in
economic freedom and individualism. If American exceptionalism includes persistent adherence to
egalitarianism, self-determination, and laissez-faire economics, it is important to remember that the
United States consumes more TV than any other developed economy (OECD 2013).
In the Gilded Age of the late 19th century, Americans read Horatio Alger’s rags-to-riches dime
novels. Today, their counterparts in the new Gilded Age are browsing through hundreds of channels
saturated with rags-to-riches entertainment programs, and elected the former host of The Apprentice
as the head of state. In this era of choice, entertainment media is what captivates hearts and minds. Its
political consequences are anything but trivial.
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Online Appendix for
“Entertaining Beliefs in Economic Mobility”
List of Supplementary Materials
A. Content Analysis
B. Media Data Descriptions
C. New York Times Coverage Sentiment Analysis
D. Quotes from Rags-to-Riches Reality TV Programs
E. Observational Survey Methods and Details
F. Full Regression Results
G. Replication Using 2016 ANES and ISCAP Survey
H. Heterogeneous Effects by Party ID in Survey Data
I. Lab-in-the-Field Experiments Logistics
J. Pilot Experiment
K. Experiment Questionnaire, Manipulation Checks, and Heterogeneous Effects
L. Supplementary Experimental Evidence
M. Trends in the American Dream Between 1990 to 2018
Electronic copy available at: https://ssrn.com/abstract=3838127
A. Content Analysis
I matched Nielsen ratings data from September 2015 to August 2017 with the Encyclopedia of Television Shows 1925–2016
(Terrace 2012, 2017) and the TV Tango.com database to identify TV shows that are classified as reality and game shows. Of
the 8,701 entries of non-fictional entertainment shows that aired between 2015 and 2017, Nielsen identified 3,362 as reality
and game shows. I narrowed this list to shows that have a competitive format, because the ideology of meritocracy and the
self-made person is closely tied to competition and amplified in the face of unequal outcomes (McNaMee and Miller Jr 2014).
Coding Instructions
Here are coding instructions for the content analysis of competitive reality and game shows from 2015-2017 to quantify the
prevalence of the shows that feature 1) ordinary Americans 2) gaining economic benefits 3) through hard work and efforts.
Category 1: ORDINARY PEOPLE?
Most of the plot summaries of TV programs mention the characteristics of contestants/participants when they are not ordinary
Americans. (i.e. celebrities, professional athletes etc). References to just “contestants,” “participants,” “performers” usually
mean ordinary people. Even when they feature celebrities, if people who participate/get money are ordinary citizens, then the
program should be coded as 1 or 2 depending on their characteristics.
• 0 – No (i.e. celebrity/ celebrity families)
• 1 – Professionals (celebrity-chefs competing in cooking competitions, expert survivalists competing in survival shows,
professional ballroom dancers)
• 2 – Everyday American (i.e. contestants, grandmothers, homeowners, aspiring models/singers, American families)
Category 2: ECONOMIC BENEFITS?
Economic benefits can mean cash prizes ($100,000), lucrative contracts (a contract for the new album, or a new job), general
life improvements in terms of something of monetary value (i.e. a new house, renovated dining room/hotel facilities), or
professional recognition (i.e. Great American Baking Show does not have any material “prize” for the winner; s/he just gets
the honor of being the best baker in the country). Some of the examples that do not feature economic benefits are mostly
competitive dating shows. The Bachelor/Bachelorette series, for instance, should be coded as 0.
• 0 – None (i.e. dating shows) / Economic benefits for others / Insignificant amount of economic benefits.
– Prizes go to charity (most of the time, when celebrities compete in reality/game show, they donate prize money.
There are cases when they pair up with a contestant, in which a contestant gets to keep his/her own money. In that
case, the TV show should be coded from the perspective of an ordinary contestant)
– Booby prizes or bragging rights (i.e. some trivia game shows give out random items as a “prize”; a winner of a
cooking competition show gets a meal cooked by the loser as a prize)
– Survivor shows that have no cash prize and focus on “personal inner growth” part of achievement
• 1 – Modest amount of economic benefits.
– Trophies and recognitions without cash prize, but can increase their earning potentials i.e. being the best “bike”
builder or the best baker can lead to more sales later, Great American Bake-Off
– Modest cash prizes (i.e. when there is no reference to specific amount of money—mostly, pop quiz shows give
out a modest amount of cash)
– Cash prizes that have no clear implications for contestants’ job/career/business prospects
– A luxury vacation or free trip
• 2– Significant amount of economic benefits.
– Prizes/recognitions that have clear implications for contestants’ job/career/business prospects (i.e. recoding deal,
coveted job, a contestant’s own TV show, a contract, business investment)
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– Cash prizes more than one million dollar, regardless of its implications for business prospects
Category 3: HARD WORK/EFFORT?
• 0 – It requires not much effort.
– Dating shows (people put a similar level of energy into dating in their real lives)
– Trivia/guessing games on the street, pop quiz shows where contestants were recruited on site
• 1 – It requires some effort. (i.e. Quiz shows that require some knowledge.)
• 2 – It requires hard work/a lot of effort.
– Most of the merit-based competition/game shows will be in this category; i.e. The Voice, American Idol, Jeopardy
– Most of the survival competition shows or shows that require extraordinary physical strength such as American
Ninja Warrior
– The process of preparing for the competition is shown / dramatized.
Figure A1. Content analysis results of reality/game programs aired 2015-2017. Note: 275 competitive reality/game TV
shows were coded for three attributes: type of people (contestants), the degree of economic benefit, and the amount of hard
work and effort as opposed to luck required to win. Each attribute has three categories. The panels show the distribution of
programs classified into each category. See Appendix A for details.
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Table A1. Full Coding Results for a Random Subset of Competitive Reality/Game Shows
Cohen’s Kappa (unweighted) for the first category (Ordinary people): 0.936
Cohen’s Kappa (unweighted) for the second category (Economic benefit): 0.91
Cohen’s Kappa (unweighted) for the third category (hard work): 0.835
Originator Program Name Type Ordinary Benefit Hard Work
r Coder 1 Coder 2 Coder 1 Coder 2 Coder 1 Coder 2
ABC $100,000 PYRAMID, THE QG 1 1 1 1 1 1
ABC 500 QUESTIONS QG 1 1 1 1 1 1
DISCOVERY CHANNEL ALASKAN BUSH PEOPLE DO 1 1 0 0 2 2
CBS AMAZING RACE PV 1 1 1 1 3 3
NBC AMERICA’S GOT TALENT PV 1 1 1 1 2 2
FOX AMERICAN GRIT PV 1 1 1 1 3 3
FOX AMERICAN IDOL GV 1 1 1 1 2 2
NBC AMERICAN NINJA WARRIOR PV 1 1 1 1 3 3
NBC APPRENTICE PV 1 1 1 1 2 2
ABC BACHELOR IN PARADISE PV 1 1 0 0 0 0
ABC BACHELOR, THE PV 1 1 0 0 0 0
ABC BACHELOR:AFTER FINAL ROSE PV 1 1 0 0 0 0
ABC BACHELORETTE, THE PV 1 1 0 0 0 0
ABC BACHELORETTE:AFTER ROSE PV 1 1 0 0 0 0
ABC BACHELORETTE:MEN TELL ALL PV 1 1 0 0 0 0
UNI BANDA 2, LA SUN GV 1 1 1 1 2 2
UNI BANDA, LA SUN GV 1 1 1 1 2 2
ABC BATTLEBOTS PV 1 1 1 1 2 2
ABC BATTLEBOTS: GEARS AWAKEN PV 1 1 1 1 2 2
FOX BEAT SHAZAM QG 1 1 1 1 1 1
ABC BEYOND THE TANK PV 1 1 1 1 2 1
CBS BIG BROTHER GV 1 1 1 1 1 1
NBC BIGGEST LOSER PV 1 1 1 1 2 3
ABC BOY BAND PV 1 1 1 1 2 2
TEL C. CERRADO (Case Closed) GV 1 1 0 0 0 0
NBC CAUGHT ON CAMERA GV 1 1 0 0 0 0
ABC CELEBRITY FAMILY FEUD QG 0 0 1 1 1 1
20TH TELEVISION CELEBRTY NAME GAME QG 1 1 1 1 1 1
TLC COUNTING ON DO 1 1 0 0 0 0
FOX COUPLED PV 1 1 0 0 0 0
UNI DALE REPLAY QG 1 1 1 1 1 1
ABC DANCING WITH THE STARS PV 0 0 1 1 2 2
DISCOVERY CHANNEL DC: DUNGEON COVE (Deadliest Catch) DO 1 1 1 0 3 3
CW DOG WHISPERER 3 DO 1 1 0 0 0 0
CW DOG WHISPERER 4 DO 1 1 0 0 0 0
ANIMAL PLANET DR. DEE DO 1 1 0 0 2 2
DISCOVERY CHANNEL DUAL SURVIVAL DO 1 1 0 0 3 3
FOX F WORD, THE PV 1 1 1 1 2 2
20TH TELEVISION FAMILY FEUD (AT) QG 1 1 1 1 1 1
NBC FIRST DATES PV 1 1 0 0 0 0
DISCOVERY CHANNEL GOLD RUSH: DIRT AFTERSHOW DO 1 1 1 0 2 3
DISCOVERY CHANNEL GOLD RUSH: THE DIRT DO 1 1 1 0 2 3
ABC GONG SHOW, THE QG 1 1 1 1 2 2
ABC GREAT AMERICAN BAKING SHOW PV 1 1 1 1 2 2
DISNEY CHANNEL GREAT CHRISTMAS LIGHT FIG GV 1 1 1 1 2 1
ABC GREAT HOLIDAY BAKING SHOW PV 1 1 1 1 2 2
ABC GREAT XMAS LIGHT FIGHT-3 PV 1 1 1 1 2 2
FOX HELL’S KITCHEN PV 1 1 1 1 2 3
NBC HOLLYWOOD GAME NIGHT QG 1 1 1 1 1 1
FOX HOME FREE PV 1 1 1 1 2 2
FOX HOTEL HELL PV 1 1 1 1 2 2
CBS HUNTED GV 1 1 1 1 2 3
CBS I GET THAT A LOT GV 0 0 0 1 1 1
CBS TV DISTRIBUTION JEOPARDY QG 1 1 1 1 2 2
TLC JILL & JESSA: COUNTING ON DO 1 1 0 0 0 0
CW JUST FOR LAUGHS GV 1 1 0 0 0 0
FOX KICKING & SCREAMING GV 1 1 1 1 3 3
CBS LET’S MAKE A DEAL 1 AP 1 1 1 1 1 1
CBS LET’S MAKE A DEAL 2 AP 1 1 1 1 1 1
NBC LITTLE BIG SHOTS PV 1 1 0 0 2 2
FOX LOVE CONNECTION GV 1 1 0 0 0 0
BRAVO MARIAHS WORLD DO 0 0 0 0 0 0
FOX MASTERCHEF PV 1 1 1 1 2 2
FOX MASTERCHEF CELEB SHOWDOWN PV 0 0 1 1 2 2
FOX MASTERCHEF JR-NY DAY 9P PV 1 1 1 1 2 2
ABC MATCH GAME QG 1 1 1 1 1 1
DISCOVERY CHANNEL MEN, WOMEN, WILD SPC DO 1 1 0 0 3 3
DISNEY ABC DOMEST TV MILLIONAIRE (AT) QG 1 1 1 1 1 1
ANIMAL PLANET MY CAT FROM HELL SNEAK PE DO 1 1 0 0 0 1
ABC MY DIET BETTER THAN YOURS PV 1 1 1 1 2 3
FOX MY KITCHEN RULES PV 0 0 0 0 2 2
DISCOVERY CHANNEL NAKED AND AFRAID: BARES DO 1 1 0 0 3 3
NBC NYE GAME NIGHT-ANDY COHEN QG 1 0 1 1 1 1
UNI PARODIANDO 3 SUN GV 1 1 1 1 2 2
UNI PEQUENOS GIGANTES USA MON GV 1 1 1 1 2 2
CBS PRICE IS RIGHT 1 AP 1 1 1 1 1 1
CBS PRICE IS RIGHT 2 AP 1 1 1 1 1 1
UNI REINA DE LA CANCION THU GV 1 1 1 1 2 2
TLC RETURN TO AMISH: COUNTDOW DO 1 1 0 0 1 0
SONY PICTURES TV RIGHT THIS MINUTE GV 1 1 0 0 0 0
DISCOVERY CHANNEL ROCKIN ROADSTERS DO 0 0 0 0 2 2
NBC RUNNING WILD: B. GRYLLS PV 0 0 0 0 3 3
DISCOVERY CHANNEL SACRED STEEL DO 1 1 0 0 2 2
ABC SHARK TANK PV 1 1 1 1 2 2
FOX SO YOU THINK CN DANCE GV 1 1 1 1 2 2
NBC SPARTAN:TEAM CHALLENGE PV 1 1 1 1 3 3
ABC STEVE HARVEY’S FUNDERDOME QG 1 1 1 1 2 2
NBC STRONG PV 1 1 1 1 2 3
FOX SUPERHUMAN GV 1 1 1 1 2 2
CBS SURVIVOR GV 1 1 1 1 3 3
CBS SURVIVOR REUNION PV 1 1 1 1 3 3
CBS SURVIVOR-SPECIAL PV 1 1 1 1 3 3
ABC TO TELL THE TRUTH PV 1 1 1 1 0 1
ABC TOY BOX, THE PV 1 1 1 1 2 2
CBS UNDERCOVER BOSS GV 1 1 1 1 1 1
UNI VA POR TI 2 GV 1 1 1 1 2 2
NBC VOICE PV 1 1 1 1 2 2
TEL VOZ KIDS 4 SUN PV 1 1 1 1 2 2
NBC WALL QG 1 1 1 1 1 1
CBS TV DISTRIBUTION WHEEL OF FORTUNE QG 1 1 1 1 1 1
NBC WORLD OF DANCE PV 1 1 1 1 2 2
FOX YOU THE JURY GV 1 1 0 0 1 1
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B. Media Data Descriptions
Internet Movie Database (IMDB)
The Internet Movie Database has information about year of programs’ release as well as their genre among many others. I
downloaded 102,523 TV programs registered in IMDb.com, which were released between 1960 and 2017. Using a release
year comes with a caveat that a long-running TV show that has different seasons will be only recorded once in this data.
IMDb typically records up to three relevant genres for each TV program, and I focused on Realty-TV/Game and News genre.
I calculated the average proportion of each genre per year.
Figure B1. The relative share of news shows and reality/game shows over time (1960-2017). I assessed 102,523 TV
programs released between 1960 and 2017 using the Internet Movie Database (IMDb.com), which typically lists up to three
relevant genres for each TV program. I calculated the average proportion of each genre per year and plotted the relative share.
Comprehensive Nielsen Ratings Data 2015-2017
The Nielsen ratings data use a nationally representative sample of households to capture information about which TV
programs people watch. Because the electronic meters automatically track what channel the televisions are tuned to, the
Nielsen data are immune to the flaws of self-reported measures of media exposure and social desirability biases. Most
importantly, the Nielsen data address the problem that national election surveys do not contain extensive questions about
entertainment media consumption, hence serving as the most comprehensive data on American TV exposure to entertainment
media. Nielsen ratings data come with their own genre categorizations, and unfortunately, they do not have a specific genre
called “reality or game shows.”’ I focused on 8 non-fictional genres in Nielsen data. This is not to argue that that fictional
entertainment media does not matter for perceptions of economic mobility. However, in attempt to find a systematic way
of studying shared rags-to-riches narratives across different TV programs, I focus on reality and game shows for their
explicit focus on touting and celebrating ordinary individuals’ economic successes. I particularly focus on 8 non-fictional
entertainment categories—AP (Audience Participation), DO (Documentary, General), GV (General Variety), IA (Instructions,
Advice), PV (Participation Variety), QG (Quiz-Give Away), QP (Quiz-Panel), and U (Unclassified)—that typically include
reality TV shows and game shows that predominantly feature ordinary Americans. Note that the number of entries does not
mean the number of programs, as one program can have multiple entries. For instance, a popular reality TV show, Dancing
with the Star, has one entry that records its average weekly program ratings, in addition to ratings for special series such as
the final or semi-final episode. I manually matched Nielsen’s 8,701 entries with the corresponding entries in Encyclopedia of
Television Shows 1925–2016 and TV Tango.com database to identify the shows that are considered reality and game shows.
TV Tango.com is an online database of entertainment media that has information about the genre of each TV program.
It provides the most comprehensive compilation of TV information, and offers search results across ten different websites
including IMDb.com, TV.com, TVguide.com, Amazon.com, iTunes, and Wikipedia.
5
Electronic copy available at: https://ssrn.com/abstract=3838127
Table B1. Top 10 Most Popular TV Program 2000-2017
Rank Program Rating Rank Program Rating Rank Program Rating
2000-2001 2001-2002 2002-2003
1 Survivor (CBS) 17.4 1 Friends (NBC) 15 1 CSI: Crime Scene Investigation (CBS) 16.3
2 ER (NBC) 15 2 CSI: Crime Scene Investigation (CBS) 14.5 2 Friends (NBC) 13.9
3 Who Wants to Be a Millionaire — Wednesday (ABC) 13.7 3 ER (NBC) 14.2 3 Joe Millionaire (FOX) 13.3
4 Who Wants to Be a Millionaire — Tuesday (ABC) 13 4 Everybody Loves Raymond (CBS) 12.8 4 ER (NBC) 13.1
5 Friends (NBC) 12.6 5 Law Order (NBC) 12.6 5 American Idol — Tuesday (FOX) 12.6
5 Monday Night Football (ABC) 12.6 6 Survivor (CBS) 11.8 6 American Idol — Wednesday (FOX) 12.5
5 Everybody Loves Raymond (CBS) 12.6 7 Monday Night Football (ABC) 11.5 7 Survivor (Thailand Amazon) (CBS) 11.9
8 Who Wants to Be a Millionaire — Sunday (ABC) 12.4 8 The West Wing (NBC) 11.4 7 Everybody Loves Raymond (CBS) 11.9
9 Law Order (NBC) 12.3 9 Will Grace (NBC) 11 9 Law Order (NBC) 11.7
10 The Practice (ABC) 11.7 9 Leap of Faith (NBC) 11 10 Monday Night Football (ABC) 11.4
Rank Program Rating Rank Program Rating Rank Program Rating
2003-2004 2004-2005 2005-2006
1 CSI: Crime Scene Investigation (CBS) 15.9 1 CSI: Crime Scene Investigation (CBS) 16.5 1 American Idol — Tuesday (FOX) 17.6
2 American Idol — Tuesday (FOX) 14.9 2 American Idol — Tuesday (FOX) 15.7 2 American Idol — Wednesday (FOX) 17.2
3 American Idol — Wednesday (FOX) 14.1 3 American Idol — Wednesday (FOX) 15.3 3 CSI: Crime Scene Investigation (CBS) 15.6
4 Friends (NBC) 13.6 4 Desperate Housewives (ABC) 14.5 4 Desperate Housewives (ABC) 13.8
5 The Apprentice (NBC) 13 5 CSI: Miami (CBS) 12.4 5 Grey’s Anatomy (ABC) 12.5
6 ER (NBC) 12.9 6 Without a Trace (CBS) 12.3 6 Without a Trace (CBS) 12.3
7 Survivor (CBS) 12.3 7 Survivor (CBS) 12 7 Dancing with the Stars (ABC) 12
8 CSI: Miami (CBS) 11.9 8 Grey’s Anatomy (ABC) 11.6 8 CSI: Miami (CBS) 11.8
9 Monday Night Football (ABC) 11.2 9 Everybody Loves Raymond (CBS) 11.2 9 Monday Night Football (ABC) 10.6
9 Everybody Loves Raymond (CBS) 11.2 10 Monday Night Football (ABC) 10.8 9 House (FOX) 10.6
Rank Program Rating Rank Program Rating Rank Program Rating
2006-2007 2007-2008 2008-2009
1 American Idol — Wednesday (FOX) 17.3 1 American Idol — Tuesday (FOX) 16.1 1 American Idol — Wednesday (FOX) 15.1
2 American Idol — Tuesday (FOX) 16.8 2 American Idol — Wednesday (FOX) 15.9 2 American Idol — Tuesday (FOX) 14.6
3 Dancing with the Stars — Monday (ABC) 12.7 3 Dancing with the Stars — Monday (ABC) 14 3 Dancing with the Stars — Monday (ABC) 12.9
3 Dancing with the Stars — Tuesday (ABC) 12.7 4 Dancing with the Stars — Wednesday (ABC) 12.6 4 CSI: Crime Scene Investigation (CBS) 11.5
3 Dancing with the Stars — Wednesday (ABC) 12.7 5 Dancing with the Stars — Tuesday (ABC) 12.3 5 NCIS (CBS) 10.9
6 CSI: Crime Scene Investigation (CBS) 12.2 6 Desperate Housewives (ABC) 11.6 6 The Mentalist (CBS) 10.8
7 Grey’s Anatomy (ABC) 12.1 7 CSI: Crime Scene Investigation (CBS) 10.6 7 Dancing with the Stars — Tuesday (ABC) 10.7
8 House (FOX) 11.1 8 House (FOX) 10.5 8 Sunday Night Football (NBC) 10
9 Desperate Housewives (ABC) 10.8 9 Grey’s Anatomy (ABC) 10.4 9 Desperate Housewives (ABC) 9.9
10 CSI: Miami (CBS) 10.7 10 Sunday Night Football (NBC) 9.7 10 Grey’s Anatomy (ABC) 9.6
Rank Program Rating Rank Program Rating Rank Program Rating
2009-2010 2010-2011 2011-2012
1 American Idol — Tuesday (FOX) 13.7 1 American Idol — Wednesday (FOX) 14.5 1 Sunday Night Football (NBC) 12.4
2 American Idol — Wednesday (FOX) 13.3 2 Dancing with the Stars (ABC) 13.8 2 NCIS (CBS) 12.3
3 Dancing with the Stars (ABC) 12.6 3 American Idol — Thursday (FOX) 13.4 3 Dancing with the Stars (ABC) 12
4 NCIS (CBS) 11.5 4 Sunday Night Football (NBC) 12.7 4 American Idol — Wednesday (FOX) 11.8
5 Sunday Night Football (NBC) 11.3 5 NCIS (CBS) 11.8 5 American Idol — Thursday (FOX) 11
6 The Mentalist (CBS) 10.6 5 Dancing with the Stars — Results (ABC) 11.8 6 Dancing with the Stars — Results (ABC) 10.6
7 Dancing with the Stars — Results (ABC) 9.9 7 NCIS: Los Angeles (CBS) 10.1 7 NCIS: Los Angeles (CBS) 10.2
8 NCIS: Los Angeles (CBS) 9.8 8 The Mentalist (CBS) 9.6 8 The Big Bang Theory (CBS) 9.7
8 Undercover Boss (CBS) 9.8 9 Body of Proof (ABC) 9 9 The Mentalist (CBS) 9.3
10 CSI: Crime Scene Investigation (CBS) 9.7 10 Criminal Minds (CBS) 8.7 10 The Voice (NBC) 9.2
Rank Program Rating Rank Program Rating Rank Program Rating
2012-2013 2013-2014 2014-2015
1 NCIS (CBS) 13.5 1 Sunday Night Football (NBC) 12.6 1 Sunday Night Football (NBC) 12.3
2 Sunday Night Football (NBC) 12.4 1 NCIS (CBS) 12.6 2 The Big Bang Theory (CBS) 11.6
3 The Big Bang Theory (CBS) 11.6 3 The Big Bang Theory (CBS) 12.3 2 NCIS (CBS) 11.6
4 NCIS: Los Angeles (CBS) 11 4 NCIS: Los Angeles (CBS) 10.3 4 NCIS: New Orleans (CBS) 11.3
5 Person of Interest (CBS) 10 5 Dancing with the Stars (ABC) 10 5 Empire (FOX) 10.9
6 Dancing with the Stars (ABC) 9.9 6 The Blacklist (NBC) 9.5 6 Thursday Night Football (CBS) 10.6
7 American Idol — Wednesday (FOX) 9.2 7 Person of Interest (CBS) 9 7 Dancing with the Stars (ABC) 9.7
7 Dancing with the Stars Results (ABC) 9.2 8 The Voice (NBC) 8.9 8 Criminal Minds (CBS) 9
9 American Idol — Thursday (FOX) 8.9 9 Blue Bloods (CBS) 8.8 8 Madam Secretary (CBS) 9
10 Two and a Half Men (CBS) 8.7 10 The Voice — Tuesday (NBC) 8.6 8 Scandal (ABC) 9
Rank Program Rating Rank Program Rating
2015-2016 2016-2017
1 NCIS (CBS) 12.8 1 The Big Bang Theory (CBS) 11.5
2 Sunday Night Football (NBC) 12.6 2 NCIS (CBS) 11.4
3 The Big Bang Theory (CBS) 12.5 3 Sunday Night Football (NBC) 11.1
4 Thursday Night Football (CBS) 10.6 4 Thursday Night Football (CBS/NBC) 9.6
5 Empire (FOX) 10.2 4 Bull (CBS) 9.6
6 NCIS: New Orleans (CBS) 9.4 6 This Is Us (NBC) 9.4
7 Dancing with the Stars (ABC) 8.8 7 Blue Bloods (CBS) 8.9
8 Blue Bloods (CBS) 8.4 8 NCIS: New Orleans (CBS) 8.5
9 The Voice: Monday (NBC) 8.2 9 Dancing with the Stars (ABC) 8.1
9 The X-Files (FOX) 8.2 10 NCIS: Los Angeles (CBS) 7.8
6
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C. New York Times Coverage Sentiment Analysis
Using the New York Times API, I downloaded all the articles from 2000 to 2019 that contains the following phrases:
economic mobility; intergenerational mobility; social mobility; upward mobility; income mobility; socioeconomic mobility;
class mobility; income ladder; economic ladder; social ladder; rags to riches; land of opportunity; American Dream; meritocracy;
rugged individualism; self-made man; self-made woman; self-made success; Horatio Alger
To make sure that the articles about the United States, the articles do not contain the word “United States”, “U.S.” or “America”
were excluded.
D. Quotes from Rags-to-Riches Reality TV Programs
“Thinking about our journey, I get emotional every time, when you’re a mom that wants to show your kids that anything is
possible. I mean I was a struggling mom to them and overnight my whole life changed. We are so thankful for our *Shark
Tank* experience, and I think that Mom and I are proof that a grandma and a stay-at-home mom can become an overnight
success. It truly is the American dream.” –– Gloria Hoffman, Shark Tank, Season 7
“I’ve been singing in the subway for roughly 37 years. That’s the good thing...The low point is on a Monday or a Tuesday,
you don’t make that much. But people get paid on Thursdays and Fridays, and then make up for it...You know success is
what you make it, but there’s no better stage, there’s no better place to be than right here.” –– Mike Young, America’s Got
Talent, Season 12
“I used to own 100% of nothing, and I’m living the American dream. I mean, I’m a Muslim first-generation American who is
now pitching a vegan pork rind on *Shark Tank*. Like, if that’s not the American dream, I don’t know what is, you know?”
–– Samy Kobrosly, Shark Tank, Season 11
“I think I am living proof of the American dream. My parents emigrated here with $100 in their pocket from Guyana, and
look at me now. I just got a deal from Mark Cuban on Shark Tank.” –– Krystal Persaud, Shark Tank, Season 11
“I am a very extreme contortionist dancer [...] I was actually homeless for two years before I got my apartment just dancing
on the streets juts doing I had to it, but I dance, all 100%, 100%, I’ve never done anything like this, just to be right here.
Dreams came true... I hope every kids that’s watching us who wants to dance, who’s ever been told that they can’t do it, they
got that just prove to them that you can do it.” –– Alonzo Jones (Turf), America’s Got Talent, Season 7
“I have some of the most amazing people in the culinary world all taste my dish and say that it was fantastic and that they
were impressed that I did my best with what limitations I have and I’m so touched that they all complimented me on my food
and they believed in me so I feel like ecstatic you can overcome anything you want to overcome and get what you want to get
and I’m gonna be the next MasterChef.” –– Christine Ha, MasterChef, Season 3
“I was diagnosed with lymphoma, blood cancer. I had blood transplants, blood transfusions, platelet transfusions, and
chemotherapy. I lost my voice; I lost my hearing in one ear. During that time all I had really was my faith and my music. For
me to go to being half dead to being on The Voice, I’ve never felt more alive than that. I’ll be signing Don’t Stop Believing
by Journey. When I was in intensive care, I played this song over and over again. This song is the epitome of my life. Keep
believing in yourself, keep believing in great things, and things will happen.” –– Rayshun LaMarr, The Voice, Season 14
“During the week I’m a pool technician; I service anywhere from 12 to 15 pools per day. I’ll get my machine ready, vacuum
the pool, check the chemicals. But I know there’s more for my life. As a kid I loved to sing, especially in my grandparents’
church. I started playing guitar and I knew that music was really starting to become a part of my life. I attended a leadership
college because I knew that taking leadership courses was going to translate into bigger things for my life. So, I started my
first ministry called Cliffside 360. It started with just me and my guitar and it has grown in two years to a hundred people
faithfully coming, young and old from across the city, to worship God. And what better spot than on top of a mountain?
Cliffside has done so much in my life but I’m ready to see what’s next. As much as I enjoy my day-to-day job, I can’t be
cleaning pools forever. I know my goal is to be a Christian artist and being on this platform is pushing me in that direction.
I’ve never had an opportunity like this in my life. I’ve literally been climbing a mountain to get my voice heard, and today is
the day to reach the top.” — Blaise Raccuglia, The Voice, Season 14
7
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E. Observational Survey Methods and Details
To assess the impact of exposure to entertainment media on perceptions of economic mobility, I designed the Media & Culture
Survey, which Survey Sampling International (SSI) administered to 3,004 US residents in August 2018. SSI used targeted
recruitment to ensure that the survey sample closely matched US Census benchmarks for education, income, age, gender,
geography, and race/ethnicity.
Survey Questionnaire
Q. Please tell us bit about yourself!
[OPTIMISM SCALE]
Q. To what extent do you agree/disagree with each of the following statements? [5 point MATRIX]
1) In uncertain times, I usually expect the best. 2) If something can go wrong for me it will. 3) I am always optimistic about
my future. 4) I hardly ever expect things to go my way. 5) I rarely count on good things happening to me. 6) Overall, I expect
more good things to happen to me than bad.
[PARTY ID]
Q. Generally speaking, do you usually think of yourself as a Republican, a Democrat, an Independent, or something else?
If PARTY ID = 1 (Republican)
Would you call yourself a... 1. Strong Republican 2. Not very strong Republican
If PARTY ID = 2 (Democrat)
Would you call yourself a... 1. Strong Democrat 2. Not very strong Democrat
IF PARTY ID = 3, 4, 5 or refused (Independent, Another party, or No preference) Do you think of yourself as closer
to the... 1. Republican Party; 2. Democratic Party; 3. Neither
[IDEOLOGY] Where would you place yourself on this scale, or haven’t you thought much about this?
Extremely Liberal, Liberal, Slightly Liberal, Moderate, middle of the road, Slightly conservative, Conservative, Extremely
Conservative, Haven’t thought much about this
[RELIGION1] Do you go to religious services [every week, almost every week, once or twice a month, a few times a year, a
few times a year, or never]?
[RELIGION2] What is your present religion, if any?
1) Protestant 2) Roman Catholic 3) Mormon 4) Eastern or Greek Orthodox 5) Jewish 6) Muslim 7) Buddhist 8) Hindu 9)
Atheist 10) Agnostic 11) Nothing in particular 12) Something else
[HAVE IMMIGRANT PARENTS] Were both of your parents born in the United States? (Yes/No)
[INTERGENERATIONAL MOBILITY EXPERIENCES]
Q. Compared to your parents when they were the age you are now, do you think your own standard of living now is much
better, somewhat better, about the same, somewhat worse, or much worse than theirs was?
[POLITICAL INTEREST] Some people seem to follow what’s going on in government and public affairs most of the time,
whether there’s an election going on or not. Others aren’t that interested. Would you say you follow what’s going on in
government and public affairs most of the time, some of the time, only now and then, or hardly at all?
[PERSONAL ECONOMIC INSECURITY]
Q. Next is a list of things that some people worry about and others do not. Please indicate how worried you are about each of
the following statements (Very worried; Somewhat worried; Not too worried; Not at all)
• That you won’t be able to afford the health care services you and your family need?
• About not having enough money for retirement?
• About not being able to afford the cost of education for yourself or a family member
8
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[EXPOSURE TO ENTERTAINMENT MEDIA] (Program-Level Measures)
Q. We would like to know which TV shows you enjoy. Below is the list of programs that many Americans watch. Please
check all the program(s) you have regularly watched.
1) America’s Got Talent (NBC) 2) Voice (NBC) 3) American Idol (FOX) 4) Survivor (CBS) 5) American Ninja Warrior
(NBC) 6) Shark Tank (ABC) 7) Amazing Race (CBS) 8) MasterChef / MasterChef Junior (FOX) 9) BattleBots (ABC) 10)
Hell’s Kitchen (FOX) 11) So You Think You Can Dance (FOX) 12) World of Dance (NBC) 13) Love Hip Hop: Hollywood
(VH1) 14) The Bachelor (ABC) 15) The Bachelorette (ABC) 16) Love Connection (FOX) 17) Celebrity Family Feud (ABC)
18) Keeping Up With the Kardashians (E!) 19) The Real Housewives (Bravo) 20) Jersey Shore: Family Vacation (MTV) 21)
Fox NFL Sunday (FOX) 22) The NFL on CBS (CBS) 23) Sunday Night Football (NBC) 24) College Football Today (CBS)
25) MLB on Fox (FOX) 26) NASCAR on Fox (FOX) 27) NBA Saturday Primetime (ABC) 28) UFC Fight Night (FOX) 29)
CBS Sports Spectacular (CBS) 30) College Basketball on CBS (CBS)
[PERCEPTIONS OF ECONOMIC MOBILITY]
Q. Please tell us the extent to which you agree or disagree with the following statements. [5 point MATRIX]
1) Anyone who works hard has a fair chance to succeed and live a comfortable life. 2) It is possible to start out poor in this
country, work hard and become well-off. 3) The United States is no longer the land of opportunity. 4) Most people who want
to get ahead can make it if they’re willing to work hard.
[ATTRIBUTIONS OF SUCCESS]
Q. Why do you think that some people get ahead farther than others? Please indicate the degree to which you agree or disagree
with each of these explanations. Because...
1) Some people work harder than others; 2) Some people are more talented than others; 3) Some people are more ambitious
and determined than others; 4) Some have a good education; 6) Technological changes and automation benefited some more
than others; 7) Politicians have failed to implement good policies that advance equality of opportunity; 8) Some people have
well-educated parents; 8) Some come from a wealthy family.
*Information on education, marital status, employment status, race, income, and region was given by SSI.
Table E1. Program-Level Entertainment Media Consumption Patterns
% Regular Viewer % Regular Viewer
America’s Got Talent (NBC) 39.6 Amazing Race (CBS) 16.7
The NFL on CBS (CBS) 34.8 College Basketball on CBS (CBS) 16.1
Sunday Night Football (NBC) 34.0 NBA Saturday Primetime (ABC) 15.1
Fox NFL Sunday (FOX) 32.9 Keeping Up with Kardashians (E!) 14.8
Shark Tank (ABC) 30.8 NASCAR on Fox (FOX) 14.4
Hell’s Kitchen (FOX) 26.7 Bachelor (ABC) 14.2
Voice (NBC) 26.4 Bachelorette (ABC) 13.5
American Idol (ABC) 25.9 Jersey Shore (MTV) 13.1
American Ninja Warrior (NBC) 25.2 The Real Housewives (BRAVO) 12.5
MasterChef (FOX) 24.8 UFC Fight Night (FOX) 11.5
Celebrity Family Feud (ABC) 22.9 World of Dance (NBC) 11.4
Survivor (CBS) 21.3 Love & Hip Hop: Hollywood (VH1) 11.1
MLB on Fox (FOX) 21.0 CBS Sports Spectacular (CBS) 10.7
College Football Today (CBS) 17.9 BattleBots (ABC) 8.9
So You Think You Can Dance (FOX) 17.2 Love Connection (FOX) 7.6
Note: Programs in bold contain a rags-to-riches narrative.
Consistent with the high Nielsen ratings of the programs included in the survey, 85% of respondents indicated that they
regularly tuned into at least one of the 30 programs. The most-watched program is America’s Got Talent, which attracted
roughly 40% of survey respondents. Football games are widely popular as well, but it is worth pointing out that each of the
different rags-to-riches programs attracts a good share of the audience. Other types of reality programs (e.g., dating shows,
programs that promote the luxury lifestyles of quasi-celebrities) are less popular. While heavy television consumers watch
a lot of entertainment programs in general—3% of survey respondents reported that they watch 20 or more programs, I find
that 72% of survey respondents watch one or more rags-to-riches TV programs. Importantly, there was no partisan difference
in the number of rags-to-riches programs people regularly consumed. Overall, the mean number of rags-to-riches programs
was 2.80 and 2.84 for Republicans and Democrats, respectively, which is not statistically significantly different (p=0.735).
In this era of hyper-polarization in which partisans have different preferences even on food, coffee, pet, and baby names, the
absence of partisan self-selection into rags-to-riches programs is important and methodologically convenient. Demand for
these shows largely stems from an innocuous demand for entertainment, and their political impacts are likely spillover effects.
9
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F. Full Regression Results
Table F1. The Impact of Watching Rags-to-Riches Programs
Beliefs in Economic Mobility Internal Attribution External Attribution
(1) (2) (3) (4) (5) (6)
Occasional Viewer (1-2 Programs) 0.019 0.013 0.006 0.013 −0.004 −0.007
(0.012) (0.011) (0.010) (0.010) (0.009) (0.009)
Frequent Viewer (3-5 Programs) 0.047∗∗∗
0.032∗∗
0.008 0.017+
0.009 0.005
(0.012) (0.011) (0.010) (0.010) (0.009) (0.010)
Heavy Viewer (6+ Programs) 0.076∗∗∗
0.040∗
0.052∗∗∗
0.052∗∗∗
0.039∗∗∗
0.014
(0.013) (0.016) (0.011) (0.014) (0.011) (0.013)
Other TV 0.001 −0.002 0.0003
(0.003) (0.003) (0.003)
Sports TV 0.007∗∗
0.006∗∗
0.006∗∗∗
(0.002) (0.002) (0.002)
Republican 0.117∗∗∗
0.026∗
−0.029∗∗
(0.013) (0.011) (0.011)
Democrat −0.003 −0.019+
0.027∗∗
(0.012) (0.010) (0.010)
Education −0.022∗∗∗
−0.003 0.010∗∗
(0.004) (0.003) (0.003)
Income −0.002 −0.001 −0.002
(0.003) (0.003) (0.002)
Married 0.016+
0.007 −0.003
(0.009) (0.008) (0.007)
Female 0.011 0.010 0.001
(0.009) (0.008) (0.008)
Age 0.001∗∗∗
0.002∗∗∗
0.001∗∗∗
(0.0003) (0.0002) (0.0002)
White 0.017+
0.022∗
−0.003
(0.010) (0.009) (0.008)
Unemployed −0.032∗
−0.011 0.011
(0.014) (0.012) (0.011)
Political Interest −0.007 0.013∗∗
0.020∗∗∗
(0.005) (0.004) (0.004)
Attend Church 0.005+
−0.001 −0.005∗
(0.003) (0.002) (0.002)
Protestant 0.010 0.018∗
−0.002
(0.010) (0.009) (0.008)
Optimism index 0.057∗∗∗
0.032∗∗∗
0.009∗
(0.005) (0.005) (0.004)
Economic insecurity 0.002 0.019∗∗∗
0.045∗∗∗
(0.005) (0.005) (0.005)
Perceived intergenerational mobility 0.036∗∗∗
0.015∗∗∗
−0.001
(0.004) (0.003) (0.003)
Have immigrant parents 0.045∗∗∗
0.022∗
−0.002
(0.011) (0.010) (0.010)
County-level absolute intergenerational mobility rates 0.001 −0.0001 0.001
(0.001) (0.001) (0.001)
County-level Gini index −0.016 −0.025 0.006
(0.046) (0.040) (0.039)
Constant 0.649∗∗∗
0.267∗∗
0.756∗∗∗
0.431∗∗∗
0.709∗∗∗
0.401∗∗∗
(0.008) (0.085) (0.007) (0.075) (0.006) (0.072)
Observations 3,004 2,998 3,004 2,998 3,004 2,998
R2
0.013 0.239 0.008 0.143 0.006 0.110
Note: OLS regression coefficients with standard errors in parentheses. State fixed effects are included. + p< 0.1, * p<0.05; ** p<0.01; *** p<0.001
10
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Table F2. The Impact of Watching Rags-to-Riches Program (Using a Continuous Measure)
Belief in Economic Mobility
Rags-to-Riches TV Consumption 0.006∗∗
(0.002)
Other TV −0.001
(0.003)
Sports TV 0.006∗∗
(0.002)
Republican 0.118∗∗∗
(0.012)
Democrat −0.003
(0.012)
Education −0.022∗∗∗
(0.004)
Income −0.002
(0.003)
Married 0.017+
(0.009)
Female 0.011
(0.009)
Age 0.001∗∗∗
(0.0003)
White 0.017+
(0.010)
Unemployed −0.032∗
(0.014)
Political Interest −0.006
(0.005)
Attend Church 0.005+
(0.003)
Protestant 0.010
(0.010)
Optimism Index 0.057∗∗∗
(0.005)
Economic insecurity 0.002
(0.005)
Perceived intergenerational mobility 0.036∗∗∗
(0.004)
Have immigrant parents 0.045∗∗∗
(0.011)
County-level absolute intergenerational mobility rates 0.001
(0.001)
County-level Gini index −0.014
(0.046)
Constant 0.275∗∗
(0.085)
Observations 2,998
R2
0.239
Note: OLS regression coefficients with standard errors in parentheses. State fixed
effects are included. + p< 0.1, * p<0.05; ** p<0.01; *** p<0.001
11
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Table F3. The Impact of Watching Rags-to-Riches Programs By Level of Political Interest
Beliefs in Economic Mobility Internal Attribution External Attribution
Low Interest High Interest Low Interest High Interest Low Interest High Interest
Occasional Viewer (1-2 Programs) 0.010 0.013 0.018 0.009 −0.006 −0.004
(0.014) (0.018) (0.012) (0.015) (0.012) (0.015)
Frequent Viewer (3-5 Programs) 0.024 0.037∗
0.028∗
0.003 0.020 −0.016
(0.015) (0.018) (0.013) (0.016) (0.013) (0.015)
Heavy Viewer (6+ Programs) 0.054∗∗
0.017 0.076∗∗∗
0.021 0.037∗
−0.010
(0.021) (0.025) (0.019) (0.021) (0.018) (0.021)
Other TV −0.002 0.003 −0.007+
0.005 −0.002 0.003
(0.004) (0.005) (0.004) (0.004) (0.004) (0.004)
Sports TV 0.008∗∗
0.004 0.010∗∗∗
0.002 0.008∗∗
0.004+
(0.003) (0.003) (0.003) (0.002) (0.002) (0.002)
Republican 0.099∗∗∗
0.126∗∗∗
0.023+
0.032 −0.018 −0.034+
(0.015) (0.023) (0.013) (0.019) (0.013) (0.019)
Democrat 0.008 −0.024 −0.003 −0.034+
0.027∗
0.040∗
(0.014) (0.022) (0.012) (0.018) (0.012) (0.018)
Education −0.028∗∗∗
−0.016∗∗
−0.007 −0.001 0.012∗∗
0.004
(0.005) (0.006) (0.005) (0.005) (0.005) (0.005)
Income 0.002 −0.008+
−0.001 −0.003 −0.003 −0.002
(0.004) (0.005) (0.003) (0.004) (0.003) (0.004)
Married 0.016 0.013 0.012 −0.002 −0.009 −0.002
(0.011) (0.014) (0.010) (0.012) (0.009) (0.012)
Female 0.025∗
−0.007 0.029∗∗
−0.014 0.001 0.001
(0.012) (0.015) (0.011) (0.012) (0.011) (0.012)
Age 0.002∗∗∗
0.0002 0.002∗∗∗
0.002∗∗∗
0.001∗∗∗
0.001∗
(0.0004) (0.0005) (0.0003) (0.0004) (0.0003) (0.0004)
White 0.011 0.029+
0.022+
0.016 −0.003 −0.016
(0.013) (0.016) (0.012) (0.013) (0.011) (0.013)
Unemployed −0.019 −0.058∗
−0.004 −0.039+
0.010 0.006
(0.016) (0.027) (0.014) (0.023) (0.013) (0.022)
Attend Church 0.002 0.005 −0.004 0.002 −0.008∗∗
0.0002
(0.004) (0.004) (0.003) (0.004) (0.003) (0.004)
Protestant 0.032∗
−0.010 0.041∗∗∗
−0.011 0.010 −0.017
(0.013) (0.015) (0.012) (0.013) (0.011) (0.012)
Optimism index 0.060∗∗∗
0.054∗∗∗
0.037∗∗∗
0.024∗∗∗
0.008 0.011+
(0.007) (0.008) (0.006) (0.007) (0.006) (0.007)
Economic insecurity 0.006 −0.008 0.029∗∗∗
0.003 0.043∗∗∗
0.046∗∗∗
(0.007) (0.008) (0.006) (0.007) (0.006) (0.007)
Perceived intergenerational mobility 0.028∗∗∗
0.044∗∗∗
0.014∗∗∗
0.010∗
−0.003 −0.004
(0.005) (0.006) (0.004) (0.005) (0.004) (0.005)
Have immigrant parents 0.031∗
0.074∗∗∗
0.024+
0.025 −0.002 0.0005
(0.014) (0.019) (0.013) (0.016) (0.012) (0.016)
County-level absolute intergenerational mobility rates 0.002 −0.00000 0.001 −0.001 0.002 0.0001
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
County-level Gini index 0.069 −0.142∗
0.015 −0.091 0.023 −0.037
(0.060) (0.072) (0.054) (0.061) (0.051) (0.060)
Constant 0.147 0.468∗∗∗
0.324∗∗
0.730∗∗∗
0.371∗∗∗
0.649∗∗∗
(0.109) (0.139) (0.099) (0.117) (0.094) (0.116)
Observations 1,774 1,224 1,774 1,224 1,774 1,224
R2
0.227 0.303 0.164 0.140 0.110 0.137
Note: OLS regression coefficients with standard errors in parentheses. State fixed effects are included. + p< 0.1, * p<0.05; ** p<0.01; *** p<0.001
12
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G. Replication Using 2016 ANES and ISCAP Survey
Additional data are the 2016 ANES and the ISCAP panel survey. The 2016 ANES uses both face-to-face interviews and
an online survey, and the ISCAP is a population-based panel survey conducted between 2007 and 2016, recruited via GfK’s
Knowledge Panel. The major drawback of these data is that they have a limited battery of questions on entertainment media
exposure and belief in economic mobility. The measures for key variables are far inferior to the ones used in the SSI survey
I designed. With these caveats, I still use these additional data to see whether similar results are found using different data
collected at different times. The dependent variable, Belief in Economic Mobility, is constructed as an index comprising two
related questions (Cronbach’s α= 0.63) in the ANES. The first item measured the perceived level of opportunity in America
to get ahead, and the second measured the extent to which economic mobility has gotten easier or harder compared to 20
years ago. Since the two questions use different scales, they are standardized and recoded to range from 0 to 1. Wave 11
of the ISCAP survey (collected in October 2016) included one question that taps into retrospective perceptions of economic
mobility, which was used as the dependent variable.
Both surveys contained only three questions about exposure to reality TV programs. The ANES asked about exposure to The
Voice, Dancing with the Stars, and Shark Tank, and the ISCAP asked about exposure to The Voice, Dancing with the Stars and
American Idol. For the ANES analysis, Exposure to Rags-to-Riches Programs is constructed as a measure that ranges from
0 (watches none of these programs) to 3 (watches all three of these programs). Of 4,271 pre-election respondents, 31.4%
indicated that they watched at least one of these three programs regularly. In the ISCAP survey, only three earlier waves
of the panel (collected between 2012 and 2014) measured media consumption. Of the 1,227 panelists who were surveyed
again in 2016, 36.6% indicated that they tuned in to one of the three programs in at least one wave. Note that because this
information is not collected in 2016 but was collected in earlier waves, Exposure to Rags-to-Riches Programs is coded to
range from 0 to 1 here - just to serve as a rough proxy for people’s entertainment media preference. For other predictors, I
include a set of demographic variables such as partisan identification, ideology, race, education, gender, income, age, religion,
employment status, and residency in metropolitan areas. I also include news media consumption (from a previous wave) and
other variables that tap into sociotropic economic perceptions. The ISCAP survey also includes a system justification scale
(Cronbach’s alpha = 0.67)—capturing people’s general tendency to justify the status quo and believe that society is fair—
which were also used as a covariate.
As before, belief in economic mobility is regressed on the count measure of exposure to rags-to-riches programs. Table ??
shows that the replication analyses largely support the hypothesis that more exposure to rags-to-riches programs is correlated
with more optimistic perceptions of economic mobility in the United States. Given that these supplementary data contain
unsatisfactory measures of key variables, it is noteworthy that the effects of exposure to rags-to-riches programs remain
robust after controlling for other demographic variables, national economic perceptions and even a system justification scale
that captures foundational psychological dispositions.
Table G1. The Effect of Exposure to Rags-to-Riches Programs on Belief in Economic Mobility
Data: 2016 ANES Data: 2016 ISCAP
(1) All (2) Rep Only (3) Dem Only (4) All (5) Rep Only (6) Dem Only
Exposure to Rags-to-Riches Programs 0.012∗
0.019∗∗
0.006 0.045∗∗
0.037 0.019
(0.005) (0.007) (0.007) (0.017) (0.033) (0.023)
Weights Y Y Y Y Y Y
Controls Y Y Y Y Y Y
R2
0.126 0.131 0.127 0.181 0.231 0.209
Observations 3,291 1,342 1,530 1,180 346 594
Cell entries are weighted OLS regression coefficients with standard errors in parentheses.†
p<0.1; ∗
p<0.05; ∗∗
p<0.01
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H. Heterogeneous Effects by Party ID in Survey Data
Across all three survey data, I find the main effects for the rags-to-riches television, which is reassuring. However, I find
inconsistent heterogeneous effects by party ID. Using a nationally representative survey from 2016 ANES, I find that the
effects are mainly driven by Republicans. Using another nationally representative survey that adopted a probability-based
sampling (conducted by GfK) in 2016, the coefficients for the Rags-to-Riches TV consumption were larger for Republicans,
but due to a reduced sample size (N=346), the standard errors were too large for it to be precisely estimated.
Table H1. 2016 ANES and ISCAP Results by Party ID
DV = Beliefs in Economic Mobility
Data: 2016 ANES Data: 2016 ISCAP
All Rep Dem Ind All Rep Dem Ind
(1) (2) (3) (4) (5) (6) (7) (8)
Rags-to-Riches TV Consumption 0.012∗
0.019∗∗
0.006 0.010 0.045∗∗
0.037 0.019 −0.101
(0.005) (0.007) (0.007) (0.015) (0.017) (0.033) (0.023) (0.120)
Weights Y Y Y Y Y Y Y Y
Controls Y Y Y Y Y Y Y Y
Observations 3,291 1,342 1,530 419 1,180 346 594 34
R2
0.126 0.131 0.127 0.162 0.181 0.231 0.209 0.613
Note: Cell entries are OLS regression coefficients with associated standard errors in parentheses. The dependent variable is coded to range from 0 to 1, with
1 indicating stronger beliefs in economic mobility. + p< 0.1, * p<0.05; ** p<0.01; *** p<0.001
Using an original survey I launched using SSI (now Dyanata) in 2018, I find that the effects were mostly driven by those
who are self-identified as independents. An array of factors might explain these inconsistent results because the survey date,
survey platform, and question wordings were all different. SSI data is not a national representative survey, and it has a higher
proportion of independents compared to both 2016 ANES and 2016 ISCAP survey.
Table H2. 2018 Media and Culture Survey Results by Party ID
DV = Beliefs in Economic Mobility
Data: 2018 SSI
All Rep Dem Ind
(1) (2) (3) (4)
Occasional viewer 0.013 −0.012 0.005 0.070∗
(0.011) (0.018) (0.016) (0.028)
Frequent viewer 0.032∗∗
0.013 0.018 0.091∗∗
(0.011) (0.018) (0.017) (0.032)
Heavy viewer 0.040∗
0.001 0.031 0.119∗∗
(0.016) (0.027) (0.023) (0.043)
Observations 2,998 1,019 1,489 490
R2
0.239 0.198 0.187 0.322
Note: Cell entries are OLS regression coefficients with associated standard errors
in parentheses. The dependent variable is coded to range from 0 to 1, with 1
indicating stronger beliefs in economic mobility. + p< 0.1, * p<0.05; ** p<0.01;
*** p<0.001
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I. Lab-in-the-Field Experiments Logistics
Since using an online survey experiment in this context cannot perfectly guarantee forced exposure, I included several
attention checks when collecting data online, which involved questions that respondents could not correctly answer if they
had not watched the treatment segments. A typical media lab on campus usually recruits undergraduate students. Though
these lab experiments are still valuable in teaching us about psychological mechanisms at work regardless of the sample
characteristics, recruiting non-student samples that are balanced in terms of partisan identification is a challenging task for
researchers in a liberal, metropolitan city. To address this issue, I conducted lab-in-the-field survey experiments in suburban
Pennsylvania and New Jersey between 2018 and 2019 using a mobile media laboratory, as shown below. As the random
assignment was at the individual level, only one respondent was assigned to each room. As the vehicle could accommodate
two respondents at a time, we prepared five folding chairs, headsets, and tablet PCs. We could accommodate a maximum of
seven respondents simultaneously—two inside, and five outside.
Figure I1. The mobile media laboratory
July 21, 2018 - Bethlehem Blueberry Festival, Burnside Plantation, 1461 Schoenersville Rd, Bethlehem, PA (Lehigh/Northampton
County)
July 29, 2018 & August 5, 2018 & March 24, 2019 & March 30, 2019 - Quakertown Farmers Market and Flea Market, 201
Station Rd, Quakertown, PA 18951 (Bucks County)
September 29, 2018 - Cowtown Farmer’s Market, 780 Harding Hwy, Pilesgrove, NJ 08098 (Salem County)
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J. Pilot Experiments
Pre-Test Pilot Survey Questionnaire
You have just watched a short video segment of a popular TV show, [Insert TV show name]. Please indicate the extent to
which you agree with the following statements. (1: Strongly Disagree - 5: Strongly Agree)
– The contestants on the show were ordinary Americans that I might meet in my everyday life.
– I can imagine someone I know being a contestant on the show.
– The winner on the show profited financially from being on it.
– If the winner on this show had financial difficulties, they probably don’t anymore.
– The winner worked very hard and made a lot of effort.
– People from all walks of life and all kinds of backgrounds could succeed on this show if they worked hard enough.
– This program is a good example of how hard work pays off.
– Watching this program made me feel like this is a land of opportunity.
The List of 14 Pilot Test TV Shows
Amazing Race; America’s Got Talent; American Grit; American Ninja Warrior ; Beat Shazam; Biggest Loser; Great
Christmas Light Fight; Home Free; Shark Tank; MasterChef ; The Voice; Toy Box; Wheel of Fortune; 100,000 Pyramid
To develop appropriate experimental stimuli, I previously conducted a pilot test using 14 different TV shows that featured
ordinary Americans achieving economic gains. All of the shows were edited to last less than 5 minutes (see the appendix for a
full description). A group of 20 undergraduate students evaluated each show on 9 different questions that tap into three major
conceptual dimensions: 1) whether the program featured ordinary Americans, 2) whether it showed them achieving clear
economic gain, and 3) whether the economic gain was the result of hard work and effort. Based on the pilot test results, the
four TV shows scoring the highest in all dimensions combined were selected as experimental stimuli (America’s Got Talent,
American Ninja Warrior, Shark Tank, and Toy Box) for the first round of survey experiment.
K. Experiment Questionnaire, Manipulation Checks, and Heterogeneous Effects
Questionnaire
[Mturk] This survey requires you to have audio on your computer to participate, as you will be watching a 5-minute video.
You will proceed to the actual survey once you answer the following question correctly. Click the play button and listen
carefully.
[Lab-in-the-field] The Institute for the Study of Citizens and Politics (ISCAP) a non-partisan research institute based in
Philadelphia, is conducting research about entertainment media and American culture. If you decide to participate, you will
be asked to watch a portion of one popular TV show and share your thoughts. Your participation in this study is completely
voluntary. This anonymous survey does not ask for any personally identifiable information. At the end of a 10 minute survey,
you will get paid $10 in cash. Your survey will start once you click the ”I agree” button below.
Q. Please choose the word you’ve just heard (Only included in Mturk survey)
1) Television 2) Fantasy 3) Entertainment 4) Drama 5) Soap Opera 6) Comedy
Please tell us a bit about yourself first!
Q. Generally speaking, do you usually think of yourself as a Republican, a Democrat, an Independent, or something else?
If PARTY ID = Republican, Q. Would you call yourself a...
-Strong Republican / Not very strong Republican
If PARTY ID = Democrat, Q. Would you call yourself a...
- Strong Democrat / Not very strong Democrat
If PARTY ID = Independent/Other/Don’t know, Q. Do you think of yourself as closer to the...
- Republican Party / Democratic Party
Q. To what extent do you agree/disagree with each of the following statements? (1: Strongly Disagree - 5: Strongly Agree)
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1) In uncertain times, I usually expect the best. 2) If something can go wrong for me it will. 3) I am always optimistic about
my future. 4) I hardly ever expect things to go my way. 5) I rarely count on good things happening to me. 6) Overall, I expect
more good things to happen to me than bad.
Q. To what extent do you agree/disagree with each of the following statements? (1: Strongly Disagree - 5: Strongly Agree)
1) In general, I find society to be fair. 2) American society needs to be radically restructured. 3) Most policies serve the
greater good. 4) Everyone has a fair shot at wealth and happiness. 5) Our society is getting worse every year. 6) Society is
set up so that people usually get what they deserve.
Treatment (Experimental Stimuli)
We are interested in knowing what types of TV shows people find most entertaining. Next, you will see a portion of one TV
show for about 4 minutes. You won’t be able to move on until the video ends. Then you will be asked to answer several
questions about the program.
- Treatment Group: Shark Tank/Toy Box/America’s Got Talent/American Ninja Warrior
- Control Group: Cesar 911
Post-Treatment Items
Q. How much did you like or dislike the program? (1: Liked it very much - 5: Disliked it very much)
Q. How entertaining was this show? (1: Very entertaining - 5: Not very entertaining )
Q. Indicate to what extent you feel this way right now. (1: Not at All - 5: Extremely)
joyful, proud, sad, afraid, mad, lively, scared, cheerful, happy, miserable
Q. Please tell us the extent to which you agree or disagree with the following statements. (1: Strongly Disagree - 5: Strongly
Agree)
1) Anyone who works hard has a fair chance to succeed and live a comfortable life. 2) It is possible to start out poor in this
country, work hard and become well-off. 3) United States is no longer the land of opportunity. 4) Most people who want to
get ahead can make it if they’re willing to work hard.
Manipulation Checks
Next we are going to ask some questions about your perceptions of the person in the TV program you just watched. Think
about [ Matt and Pat, the entrepreneurs, (if Shark Tank) Darla, the toy maker, (if Toy Box) Mandy Harvey, the singer (if
America’s Got Talent) Ian Dory, the contestant, (if American Ninja Warrior) Yolanda, the dog owner (If Cesar 911) ] as you
answer these questions.
Q. Please tell us the extent to which you agree or disagree with the following statements. (1: Strongly Disagree - 5: Strongly
agree)
1) The person on the show profited a lot financially from being on it. 2) The person featured in the program is likely to have a
higher income from now on. 3) The person featured in the program has a good work ethic. 4) This program shows that people
can succeed when they are willing to work hard.
Attention Checks
IF SHARK TANK
Q. what is the name of the Matt and Pat’s company ? 1. Jolt 2. Grinds 3. Uptime 4. Catalyst
Q. What was their previous job? 1. NBA players 2. Football players 3. Soccer players 4. Baseball players
IF TOY BOX
Q. How many phrases Niya can speak? 1. 10 phrases 2. 100 phrases 3. 200 phrases 4. 500 phrases
Q. What is the name of the storybook that comes with the doll? 1. We Are Friends 2. The Adventures of Niya 3. Touch the
Earth 4. Niya Loves Me
IF AMERICA’S GOT TALENT
Q. What is the title of the song that Mandy Harvey wrote? 1. At Last 2. Again 3. Smile 4. Try
Q. During Mandy’s performance, 1. Mandy did not wear shoes. 2. Mandy played piano. 3. Mandy’s mom was crying. 4.
Mandy was wearing a blue dress.
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IF AMERICAN NINJA WARRIOR
Q. What is the name of Ian’s son? 1. Pax 2. Michael 3. Matt 4. Dan
Q. Where does Ian keep his son’s photo? 1. In his wallet 2. In his pocket 3. In his socks 4. In his pants
IF CESAR 911
Q. What is the name of Yolanda’s dog ? 1. Phoebe 2. Emmy 3. Roxie . 4. Izzy
Q. What is the name of Yolanda’s second dog? 1. Dodger 2. Bailey 3. Charlie 4. Tucker
I employ several manipulation checks to ensure that my treatments have their intended effect on perceptions of economic
mobility. First, I need to verify that the treatment prime actually conveyed the components that I hypothesized to be necessary
to a belief in upward economic mobility. Respondents in the treatment condition were much more likely to say that the person
featured on the show profited a lot financially (t = -17.032, p < 0.001), is likely to have a higher income from now on (t=-
17.251, p < 0.001), has a good work ethic (t= -16.35, p < 0.001), and showed that people can succeed when they are willing
to work hard (t=-11.669, p < 0.001) than those in the control condition. Further, I also checked whether my manipulation
had unintended consequences. There was no statistically significant difference between the two conditions regarding whether
respondents liked the program (t=-0.631, p=0.528) or whether they thought the program was entertaining (t=-1.467, p=0.148).
The tables below demonstrate the heterogeneous treatment effects by system justification tendency among the full, combined
sample (with survey mode fixed effects included).
Table K1. Heterogeneous Treatment Effects by System Justification Tendency
Dependent variable:
Beliefs in Upward Mobility
Rags-to-Riches Media Treatment −0.029∗∗
(0.013)
System Justification Scale - High (vs Low) 0.032∗∗
(0.014)
Treatment x System Justification Scale - High 0.181∗∗∗
(0.020)
Optimism 0.042∗∗∗
(0.005)
Party ID −0.033∗∗∗
(0.007)
Constant 0.550∗∗∗
(0.037)
Date/Location Fixed Effects Yes
Survey Mode Fixed Effects Yes
N 966
Adjusted R2
0.393
Note: A median value of system justification scale is used (high vs low) * p<0.05; ** p<0.01; *** p<0.001
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L. Supplementary Experimental Evidence: The Effects of Merit-Based Rags-toRiches
TV on Attitudes Toward Inequality and Redistribution
Sociotropic perceptions about upward economic mobility are fundamentally linked to ideas about how people get ahead.
Although scholars across disciplines conceptualize economic mobility in different ways, studies of perceptions about economic
mobility typically tap people’s beliefs in meritocracy. Disentangling this meritocratic mechanism is particularly important
because merit and hard work affect how people think about whether the rich deserve what they earned or whether the poor
deserve to receive social welfare. .
To disentangle the effects of the meritocratic narrative in “rags-to-riches” TV programs on policy preferences, I conducted
additional lab-in-the-eld experiments at a farmer’s and ea market in Quakertown, Pennsylvania, in March and April 2019,
again using the mobile media laboratory.1
I constructed two treatments using different rags-to-riches TV shows. The
America’s Got Talent video was the same one I used in the previous experiment. The Shark Tank video clip featured a
White, middle-aged contestant, Aaron Krause, who pitched the idea for a smiley-faced cleaning sponge. After emphasizing
how hard he worked to get where he is now, he secured the investment he needed.
Because the goal of this experiment was to disentangle the effects of the presence of hard work and merit in getting ahead,
I included a control media treatment that awarded nancial benets to contestants who did not demonstrate any hard work or
talent. The control treatment contained scenes from Wall (NBC), a reality TV show that featured a middle-aged White couple
who won half a million dollars primarily due to luck. The premise of the show is that contestants, if they correctly answer
trivia questions, are allotted a selection of large balls that ping around on a four-story-tall pegboard and randomly fall into
slots marked with various U.S. dollar amounts up to one million dollars. To prevent even a slight possibility that respondents
would think that these contestants are “good people” who deserve such wealth, I edited the video so there was no mention of
the contestants’ occupation and background. Their correct answering of trivia questions was also edited out, as some people
might interpret that behavior as “talent.”
The first two outcomes measured what people think leads to some people being rich and others being poor. Respondents were
asked to choose between whether they think that some people are rich because they worked harder than others or because
they had more advantages than others (The Rich Work Hard). They were also asked to choose between whether they think
that some people are poor because of lack of effort on their own part or because of circumstances beyond their control (The
Poor Lack Effort). In addition, respondents were asked a series of questions about their attitudes toward income inequality.
They indicated the extent to which they agreed that the income gap between the rich and poor is a serious problem, income
inequality is a desirable feature of modern society because people make different contributions, and high-income earners
in our society generally deserve their pay. These three questions are coded to range from 0 to 1 (greater tolerance with
income inequality) and are averaged together into Inequality Tolerance (Cronbach’s α = .73). The last dependent variable
uses four questions to measure attitudes toward government-led redistribution. Respondents indicated the extent to which
they agreed that the government should increase tax rates on Americans earning more than $250,000 a year, reduce the
gap between the rich and the poor, reduce assistance to the unemployed, and expand federal rental assistance program to
high-poverty neighborhoods. These four questions are coded to range between 0 and 1, with higher numbers indicating
the most conservative response, and averaged together into Anti-Redistribution (Cronbach’s α = .68). To ensure that my
treatments would have their intended effects, I conducted manipulation checks and veried that the treatment priming did
convey the meritocratic components that I hypothesized to be important for people’s attitudes toward income inequality and
redistribution.
Results
My experiments show the extent to which merit-based rags-to-riches TV programs inuence people’s attitudes toward attribution
of economic success, income inequality, and redistribution, as displayed in Table L1. Columns 1 and 2 show the results on the
attitudes toward the rich and poor. When respondents were limited to two choices— whether they thought that some people
are rich because they worked hard or because they were lucky— exposure to merit-based rags-to-riches TV programs had
substantial effects: it increased the perception that the rich people are rich because of hard work and talent by around 17.5
percentage points.
To put this in context, the partisan gap in the control condition was 19 percentage points. In other words, the treatment effects
were the same size as the gap between Democrats and Republicans. On the other hand, the treatment effects on the perception
1Similar to the previous experiments, respondents received $10 compensation in cash for their participation. All respondents were asked a set of questions
about their general attitudes about the prospect of upward economic mobility, income inequality, and redistribution. Party ID was measured as a pre-treatment
covariate.
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Table L1. The impact of merit-based rags-to-riches TV on redistribution-related attitudes
The Rich Work Hard The Poor Lack Efforts Inequality Tolerance Anti-Redistribution
(1) (2) (3) (4)
Merit-based TV Treatment 0.175+
−0.090 0.098∗
0.079+
(vs. Luck-based treatment) (0.091) (0.092) (0.045) (0.044)
Observations 119 119 119 119
R2
0.115 0.066 0.097 0.087
Note: Pre-treatment covariates include Party ID and optimism index. + p¡ 0.1, * p¡0.05; ** p¡0.01; *** p¡0.001
that some people are poor due to lack of effort, not circumstances beyond their control, were not statistically signicant. This
hints a possibility that narrative emphasis on the merits of the economic winners does more to legitimate the deservingness of
the rich than to delegitimize the deservingness of the poor.
Consistent with my expectations, merit-based rags-to-riches TV programs have signicant treatment effects on people’s attitudes
toward income inequality and redistribution. People in the treatment condition were approximately 10 percentage points more
likely to tolerate income inequality and around 8 percentage points more likely to be opposed to redistribution. Granted, there
is no reason to believe that people who participated in the lab-in-the-field experiments were representative of the general
adult population in America. The experimental finding here is not conclusive, but it sheds useful light on the psychological
mechanism articulated in previous studies that links meritocracy with tolerance of income inequality and lower support for
redistribution (Mijs 2019, Piketty 1995).
M. Trends in the American Dream from 1990 to 2018
It is important to acknowledge that the main findings of the manuscript are cross-sectional evidence, while the ultimate
question of why beliefs in the American Dream have persisted can be better answered with long-running surveys. But
perhaps reflective of the discipline’s general reluctance of accepting “unusual forms of political discourse as important ones”
(Herbst 2006), widely-used national surveys have either not asked about non-news media consumption or only included a few
program-level measures of entertainment media consumption. With this glaring data limitation, the below figure demonstrates
the marginal effects of TV consumption on beliefs in the American Dream from 1990 to 2018. Though not conclusive, it
demonstrates that people who watch more than 3 hours of television per day have become more optimistic over time.
0.75
0.80
0.85
1990 1994 1998 2002 2006 2010 2014 2018
Year
peoplecangetaheadbyworkinghard
Overall TV Consumption Low High
Figure M1. Marginal effects of TV consumption on beliefs in the American Dream. Note: The figure uses the General Social
Survey from 1990 to 2018. High TV consumption (navy) refers to those who watch more than 3 hours of television per
day. The cut is based on mean. The marginal effects are calculated conditional on age, income, race, education, gender, and
interest in news. The outcome variable ranges from 0 to 1.
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