Adolescents' theories about economic inequality: why are some people poor while others are rich?

Developmental Psychology 2014, Vol. 50, No. 11, 2512–2525

© 2014 American Psychological Association 0012-1649/14/$12.00 http://dx.doi.org/10.1037/a0037934

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Adolescents’ Theories About Economic Inequality: Why Are Some People Poor While Others Are Rich? Constance A. Flanagan

Taehan Kim

University of Wisconsin-Madison

The Charles F. Kettering Foundation, Dayton, Ohio

Alisa Pykett

Andrea Finlay


VA Palo Alto Health Care System, Palo Alto, California, and Stanford University School of Medicine

Erin E. Gallay

Mark Pancer


Wilfrid Laurier University

Open-ended responses of an ethnically and socioeconomically diverse sample of 593 12- to 19-year-olds (M ⫽ 16 years old, SD ⫽ 1.59) were analyzed to explain why some people in the United States are poor and others are rich. Adolescents had more knowledge and a more complex understanding of wealth than of poverty and older adolescents had more knowledge and a more complex understanding of both. Controlling for age and demographics, adolescents had a deeper understanding of inequality if they were female, from better educated families, discussed current events in their families, and attended schools with classmates who discussed current events in their families. Higher parental education and attending schools with classmates who discussed current events with their families increased the likelihood of structural attributions for poverty. Keywords: economic inequality, attributions, adolescents’ lay theories, societal cognition

porary safety net for the poor (Hacker, 2006; Hacker & Pierson, 2011; Lehman & Danziger, 2004; Piketty, 2014). According to the 2010 Census, poverty rates reached 15.1%, the largest number since the Census started tracking poverty in 1959, and one that rose faster in 3 years than during any other 3-year period since the 1980s. That report got scant attention in the media, even less than the few weeks devoted to poverty in the wake of Hurricane Katrina. Media attention to the wealthy far outweighs that given to the poor (Kendall, 2005), and even sympathetic stories about poverty typically employ a case study rather than in-depth format (Iyengar, 1991; Sotirovic, 2003), with structural factors that may contribute to inequality downplayed (Bennett, 1996). Perhaps, then, it is not surprising that American adults are poorly informed about the degree of income inequality in the United States (Norton & Ariely, 2011). But what about adolescents? How much do they know and how do they explain why some people are rich while others are poor? And what factors underlie their understanding? These questions are the focus of the current study. First, we looked at factors related to the quantity and complexity of adolescents’ explanations for poverty and wealth. Second, we examined their attributions for poverty and wealth (to individual, societal, or uncontrollable causes) and the factors associated with these attributions. We begin with a summary of research on adults’ attributions for poverty and inequality followed by a summary of relevant work on children’s and adolescents’ understanding.

Adolescents’ ideas about economic inequality have received scant attention in developmental research despite the gap between the haves and have-nots that has grown over the past several decades (Noah, 2012; Saez, 2010). Structural economic changes aided and abetted by changes in tax and entitlement policies have resulted in increased wealth for those at the top, stagnant wages for the middle-class, and a shredded and tem-

This article was published Online First September 15, 2014. Constance A. Flanagan, Department of Civil Society and Community Studies, School of Human Ecology, University of Wisconsin-Madison; Taehan Kim, The Charles F. Kettering Foundation, Dayton, Ohio; Alisa Pykett, Department of Civil Society and Community Studies, School of Human Ecology, University of Wisconsin-Madison; Andrea Finlay, Center for Innovation to Implementation, Substance Use Disorder Quality Enhancement Research Initiative, VA Palo Alto Health Care System, Palo Alto, California, and Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine; Erin E. Gallay, School of Human Ecology, University of Wisconsin-Madison; Mark Pancer, Department of Psychology, Wilfrid Laurier University. Data collection for this study was supported by a grant from the William T. Grant Foundation to Constance A. Flanagan. We thank the students and schools for participating in the study. Correspondence concerning this article should be addressed to Constance A. Flanagan, Department of Civil Society and Community Studies, 4153 Nancy Nicholas Hall, School of Human Ecology, University of Wisconsin-Madison, Madison, WI 53706-1507. E-mail: caflanagan@ wisc.edu 2512

ADOLESCENTS’ THEORIES ABOUT INEQUALITY


American Adults’ Theories About Inequality An adolescent’s theory about inequality is socially mediated, i.e., informed by lay theories or widespread beliefs that are available to people as likely “causes” (Hewstone, 1989). Although people typically explain economic inequalities by referring either to individual, structural, or uncontrollable factors (Bullock, 1995; Furnham, 1982, 1988; Iyengar, 1989), Americans strongly endorse individual factors (Feagin, 1975). Compared to residents of other nations, they are more accepting of income and pay disparities (Kluegel & Smith, 1986; Osberg & Smeeding, 2006), with large majorities contending that anyone can escape poverty through dint of hard work (Austen, 2002). At the same time, there are differences between groups, with men and Whites contending that individuals deserve their station and women, ethnic minorities, and members of low-income groups more cognizant of both the structural and individual factors that contribute, in particular, to poverty (see Bullock, 2006, for review). People with higher levels of education also are more likely to recognize the structural factors underlying inequality (Hunt, 2004). Despite their awareness of structural barriers, members of lowincome groups remain deeply committed to hard work as the means for social mobility and the mechanism whereby they will attain the American dream (Bullock & Limbert, 2003; Bullock & Waugh, 2005; Kluegel & Smith, 1986). Furthermore, consistent with system justification theory, even the most economically disadvantaged Americans are highly committed to meritocratic ideologies, explaining inequality based on the merit or lack of merit of an individual’s effort and performance (Jost & Hunyady, 2005; Jost, Pelham, Sheldon, & Sullivan, 2003).

Children and Adolescents’ Understanding of Inequality Less is known about adolescents’ understanding of inequality. However, age-related differences in economic understanding, including inequality, are consistent with those noted in social cognitive research, i.e., increasing abilities between childhood and late adolescence to deal with abstract concepts, to reason about social issues, and to understand those issues from different perspectives (Smetana & Villalobos, 2009). Late adolescents have a better understanding than do children or early adolescents of such things as who sets prices at stores, the negative effects of doing away with taxes, or the individual and systemic factors contributing to unemployment and homelessness (Bowen, 2002; Cram & Ng, 2007; Flanagan & Tucker, 1999). Late adolescents are more accurate than early adolescents in their assessments of their family’s social class position (Goodman et al., 2001). When explaining how people become wealthy, older adolescents are more likely than early adolescents or children to mention systemic factors beyond individual control in addition to individual factors such as hard work (Furby, 1979; Halik & Webley, 2011; Harrah & Friedman, 1990) and to note such things as lack of jobs and training as factors contributing to poverty (Leahy, 1981). Structural factors contributing to poverty may be a challenge for early adolescents to understand: even after instruction emphasizing such factors, their attributions became more fatalistic rather than structural (Mistry, Brown, Chow, & Collins, 2012).

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Both children and adolescents believe that a rich person is more competent than a poor person but middle- and high-schoolers are better at articulating the individual factors that distinguish the rich from the poor (Sigelman, 2012). Although older adolescents are capable of understanding structural factors underlying inequality, they also believe that the poor are less intelligent, academically competent, and likely to succeed (Leahy, 1981; Skafte, 1989)— beliefs that are actually more pronounced among African American than European American students (Woods, Kurtz-Costes, & Rowley, 2005). Adolescents also are aware of the stigma associated with poverty and of the negative implications for the selfesteem and friendships of the poor (Skafte, 1989). Compared to their younger peers, older adolescents do not give equal weight to effort as a factor explaining poverty and wealth. Rather, they credit the rich for working hard but do not automatically blame the poor for failing to do so (Leahy, 1983; Skafte, 1989). In summary, between childhood and late adolescence, there are increases in one’s knowledge about the economy, capacities to deal with abstractions such as structural factors underlying inequality, and awareness of the psychological implications and social stigma associated with being poor. Besides age, social class differences in children’s and adolescents’ understanding of inequality have been the focus of several studies, although the measures and age groups have differed (Chafel, 1997). The bulk of the evidence, in our view, suggests that adolescents from higher socioeconomic status (SE)S families are more aware of the multiple factors that might contribute to inequality. Positive associations have been found between an adolescent’s family’s socioeconomic status and his or her awareness of barriers to equal opportunity (Eisenberg-Berg & Mussen, 1976; Simmons & Rosenberg, 1971), understanding of the scale of inequality and the range of factors contributing to it (Dickinson, 1990; Emler & Dickinson, 1985), and knowledge of the structural factors underlying unemployment and homelessness (Flanagan & Tucker, 1999). Compared to their working-class peers, adolescents from upper middle-class families are less likely to believe in the promise of equal opportunity in the abstract but more likely to believe that they and their family enjoy the benefits of the economic system (Goodman et al., 2000). Some studies have shown that adolescents from middle-class backgrounds are marginally more likely than their peers from working-class backgrounds to endorse individual causes for inequality (Emler & Dickinson, 1985) and to blame the poor for wasting their money (Leahy, 1983). However, others find that children in low-income families are more likely than their middleclass peers to hold individuals who are poor accountable—for being unwilling to work hard or for managing their money poorly (Crosby & Mistry, 2004). Consistent with the research on adults, adolescents from ethnic minority and low-income backgrounds are even more likely than their ethnic majority or privileged peers to believe that the poor can change their circumstances through their own determination and hard work (Dalbert, 2001; Leahy, 1983). Holding individuals accountable for their economic status is consistent with system justification theory, which argues that defending the status quo is the default for most people and that structural critiques that challenge widespread beliefs are more cognitively and emotionally demanding (Jost, Federico, & Napier, 2009). In summary, the rather limited body of research on adolescents’ theories about inequality suggests that older adolescents as well as

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those from higher SES backgrounds may be more likely than their younger and less privileged peers to consider structural as well as individual factors as causes for inequality.


Discussions of Current Events and Politics Adolescents’ understanding of inequality is one example of their sociocentric understanding, i.e., their knowledge about society and how it works. Several studies have identified adolescents’ participation in family discussions of current events and politics as an especially important correlate of their civic knowledge, understanding of social issues, and their capacities to see those issues from different perspectives (Andolina, Jenkins, Zukin, & Keeter, 2003; Flanagan, Gallay, Gill, Gallay, & Nti, 2005; Niemi & Junn, 1998). Analyses of national data reveal that adolescents are most savvy about political issues in homes where parents both know a lot about current events and discuss them with their children (McIntosh, Hart, & Youniss, 2007). Discussions of current events also can focus children’s attention on government accountability. For example, after Hurricane Katrina family discussions increased the likelihood that African American children would hold the government, rather than families, accountable for providing aid (Brown, Mistry, & Bigler, 2007). Discussions and reflections on social issues at school also can change students’ group stereotypes and attributions for public problems. For example, explicit conversations about racial discrimination reduced the racial biases of White elementary school children, whereas no reductions were found for peers who did not participate in such conversations (Hughes, Bigler, & Levy, 2007). Other work has documented change in adolescents’ and college students’ attributions for poverty before and after their participation in a service learning course. Specifically, pre-post tests showed that, after engaging in direct service with people in need and in class reflections on their experience, students were less likely to attribute poverty to individual and more likely to emphasize structural causes (Metz, 2003; Seider, Rabinowicz, & Gillmor, 2011). That said, opportunities for learning about, discussing, debating, and engaging in public problem solving vary with students from more privileged families having more opportunities (Kahne & Middaugh, 2009).

Schools and Families as Mesosystems Insofar as learning at school occurs in settings with fellow students, students’ learning, attitudes, and behaviors are affected by the norms and behaviors of their classmates (Shinn & Yoshikawa, 2008). For example, research in Germany showed that an individual student’s tolerance toward foreigners was positively related to the average attitude toward foreigners expressed by his or her classmates (Gniewosz & Noack, 2008). Similarly, research in the United States found that Latino ninth graders’ civic knowledge, commitment to voting, and support of immigrant rights was positively related to their classmates’ reports that students in their class experienced an open climate for discussing different views (Torney-Purta, Barber, & Wilkenfeld, 2007). Finally, according to longitudinal work, if a high percentage of fellow students in an adolescent’s high school consider voting a civic duty, that young person is far more likely to vote when he or she is eligible to vote. Such “collective civic duty” norms have a stronger impact on

voting than does an individual adolescent’s own belief that voting is a civic duty (Campbell, 2006). Since families and schools act as mesosystems (Bronfenbrenner, 1979), might an adolescent’s theory about inequality be affected by the family practices of his or her classmates? Specifically, might family discussions of current events have reach beyond individual adolescents, affecting knowledge and perspectives shared at school? If so, an adolescent who attends class with students whose families discuss current events and politics should benefit from the stockpile of knowledge of his or her classmates.

Hypotheses We tested the following hypotheses: In light of the disproportionate attention that the media give to wealth over poverty and of the esteem in which the wealthy are held as models to emulate, we expect that adolescents will have more knowledge and a more complex understanding of wealth than of poverty (H1). Based on age-related increases in adolescents’ understanding of society, the economy, and of factors underlying social stratification and inequality, we expect that, compared to early adolescents, older adolescents will have more knowledge and a more complex understanding of wealth and of poverty (H2). Based on the advantages to learning about society that accrue to those in more privileged families, we expect that those adolescents whose parents have higher levels of education will have more knowledge and a more complex understanding of poverty and wealth and will discuss current events more often in their families (H3). Insofar as discussions of current events are positively associated with adolescents’ knowledge and understanding of public issues, we expect that this family practice (albeit, more often found in better educated families) will be associated with more knowledge of and greater complexity in adolescents’ understanding of inequality (H4). Since schools and families operate as mesosystems, we expect that an adolescent’s understanding of inequality will benefit from the habits of family discussions of his or her classmates. That is, we expect that an adolescent whose classmates’ families discuss current events and politics will have more knowledge and a greater appreciation of the complexity underlying issues of economic inequality (H5). We are also interested in the content of adolescents’ explanations, in particular the degree to which they attribute poverty or wealth to individual, societal, or uncontrollable factors. Based on system justification theory, we contend that individual attributions for poverty and wealth are those that maintain (justify) the status quo. Holding individuals accountable for their economic status is the default for most Americans who hew to the widespread belief that individuals deserve their fates. Contesting such widely held beliefs (and arguing that there may also be structural or societal causes for inequality) requires more cognitive sophistication and exposure to different sources of information. An adolescent’s age (H6) and his or her parents’ level of education (H7) should be positively associated with the likelihood that he or she will mention societal or multiple dimensions (societal, individual, uncontrollable) when explaining poverty or wealth. In addition, since family discussions of current events and politics expose adolescents to a wider range of perspectives on social issues, we expect that such family discussions in an adolescent’s family (H8) and such family discussions among an adolescent’s classmates (H9)


will be associated with the likelihood that he or she will attribute poverty and wealth to societal or to a mixture of (societal, individual, uncontrollable) factors.

Method


Sample Data were collected in a Midwestern state from school districts selected because they represented high-, middle-, and low-SES communities. Participants were made aware that their answers were collected anonymously and that there were no right or wrong answers. Five-hundred ninety-three seventh- through 12th-grade students (M ⫽ 16.12 years old, SD ⫽ 1.56; 57% female) from 13 schools were surveyed in social studies classes by trained research assistants. Based on students’ reports of their racial/ethnic background, the sample was 53.7% European American, 19.8% African American, 11.5% Arab American, 5.8% Asian American, 5.8% Native American, and 3.4% Hispanic American. The social class composition of the sample, based on adolescents’ reports of their parents’ education, indicated that 33% of parents had a high-school diploma or less (6.7% had not finished high school), 16.4% had some training after high school, 19.7% had a college degree, and 30.9% had professional or postbaccalaureate degrees.

Measures of Adolescents’ Understanding of Poverty and Wealth Students’ ideas about poverty and wealth were tapped with two open-ended questions since open-ended items are considered a superior method for obtaining explanatory judgments than are rating scales (Hewstone, 1989). Adolescents were prompted with the statement, “Imagine that someone from another country were visiting the United States and they asked you to explain some things to them,” followed by (a) “Suppose they asked you to explain why some people in the United State are poor, what would you say?” and (b) “Suppose they asked you to explain why some people in the United States are rich, what would you say?” Quantity. Adolescents could provide more than one explanation for the causes of poverty and wealth. Up to four answers for poverty and four for wealth per participant were coded for content, and answers were labeled sequentially, from first through fourth responses. Attribution for poverty and wealth. Answers to poverty and wealth questions were assigned to discrete categories and then grouped into four superordinate categories (see Table 1). The first three superordinate categories (references to individual, societal, or uncontrollable factors) are those typically used to code attributions in research on inequality (Bullock, 1995; Furnham, 1982, 1988; Iyengar, 1989). Intercoder reliability based on Cohen’s kappa was .86 for poverty and .91 for wealth. Overall, in looking at adolescents’ first responses, a greater percentage of their attributions for poverty were to societal factors (43.5% to societal vs. 32.9% to individual) and, for wealth, to individual factors (35.2% to societal and 49% to individual). In looking at discrete attributions within wealth and poverty, the most commonly cited reasons for being poor were lack of job opportunities (18.2% of all first responses for poverty), lack of motivation (14.1%), and little effort in education (9%). The major discrete

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reasons cited to explain why some people are rich were: working hard (31.3%), birth/background (11.4%), having a good job (10%), and luck (8.6%). As presented in Table 1, the “other” category included definitions but no attribution (“Rich people have money, poor people don’t have much money”). Besides such definitional responses, the most common responses in the “other” category were general references to education (e.g., rich people have “a lot of education”; poor people do “not have enough education”) and, for poverty, general references to not having a job. However, it was unclear whether the individual (e.g., worked hard in school) or society (e.g., there are not enough jobs) was held accountable and therefore additional assignment to superordinate categories was not made. The “other” category was included in analyses of the total number or quantity of responses and in the integrative complexity analyses described below. However, these responses were excluded from analyses that compared the three main categories. In addition to the assignment of each answer to one of the four (individual, societal, uncontrollable, other) categories, we classified students’ answering patterns into the following: whether the pattern invoked ONLY individual, societal, uncontrollable, or other factors and thus reflected a unidimensional understanding, or whether the pattern was multidimensional, invoking different categories. Integrative complexity. The level of complexity of an adolescent’s understanding of poverty and wealth was measured using integrative complexity (IC) coding techniques. Integrative complexity looks at the structure rather than the content of a response and is defined with respect to two cognitive structural variables: differentiation and integration (Suedfeld, Tetlock, & Streufert, 1992). Differentiation refers to the perception of different dimensions and/or the taking of different perspectives when considering an issue. Integration reflects a higher level of complexity that builds on differentiation and connects or integrates the different perspectives. In order to score open-ended responses for integrative complexity, a coder goes through training on the technique and trains until he or she reaches a level of intercoder agreement with others who have trained and use the IC technique. For this study, an individual trained to use the IC coding system with an intercoder reliability score of .91 coded all responses for complexity. As an additional check on reliability, a random sample of responses was coded by a second coder trained in integrative coding techniques. An intercoder agreement of 88% was obtained between these two trained IC coders. The integrative complexity coding technique is commonly used in studies of political or social dilemmas (Suedfeld & Leighton, 2002). It has also been used in longitudinal studies of university matriculants as a predictor of their capacities for adjusting to the stressors of university life (Pancer, Hunsberger, Pratt, & Alisat, 2000). To our knowledge, IC coding has not been done with an adolescent sample. IC scoring uses a 1–7 scale. Scores of 1 on the scale indicate the lowest level of complexity, and typically reflect a one-dimensional, value-laden perspective on an issue. Representative statements scored “1” in our study: for poverty (They have no jobs); for wealth (They worked hard). Scores of 2 show the beginnings of differentiation, typically favoring a one-dimensional perspective but acknowledging the possible presence of other perspectives. Representative statements scored “2” in our study:

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Table 1 Attribution Categories of Poverty and Wealth Responses and Sample Representative Statements Category

Motivation

Intelligence/Education


Personal problems Negative reference to individual

Training/Education Birth/Background Job opportunities Policies Societal characteristics

Luck Illness Formerly successful

Lack of a job General reference—Education Have no money (have lots of money) Feeling sorry for others Have no place to live

Statement Individual People are poor because they are lazy and don’t want to work hard. They do not have the ambition. People are rich because they stayed in school, pursued a career and probably succeed in their goals. They work harder than others so they are richer. I would say they [the rich] were smart and went on to college. Some [poor people] did not pay attention in school and then they failed. Some are poor because they got into drugs and alcohol and some who ran away from home. They might be poor because they waste their money on junk. They [the rich] could be dishonest and getting this money out of unlawful places. Societal People are poor because not everyone receives the same skills or training and encouragement when they are young. Some people were born into poverty and it is hard to get out. Some people are rich because they inherited money or a big business. They could be poor because the plant they work for closed down. Mostly there is no work. I would say that a lot of them [poor] got laid off and could not afford their homes anymore. Some of them [who are poor] were on welfare but got cut off. Some [of the poor] are discriminated against. Uncontrollable Some people are rich because they won the lottery. Some are poor because they just had a run of bad luck. People might be poor because someone they know got very sick and they had to pay for the medicine. Some [who are poor] were thrown out of their houses because of a divorce. Other Cause they [the poor] don’t have a job. They [the poor] don’t have the education. They [the rich] are educated. Because they [the poor] have no money. They [the rich] have a lot of money. I’d say they [the poor] should get lots of help. No home

for poverty (It was their choice, and they should have worked harder); for wealth (They tried harder and took their chances). Scores of 3 show clear differentiation, in that the statement being coded shows an ability to see that different perspectives may be taken on an issue, or that the issue has different dimensions or aspects that must be taken into consideration. Representative statements scored “3” in our study: for poverty (Poor people may have a hard time with finances or might just not be paid well); for wealth (They got an education and worked very hard or they inherited money or a business). Scores of 4 to 7 indicate, in addition to differentiation, the ability to integrate the different perspectives or dimensions related to the issue. The range of IC scores for participants in this study was 1 to 3 on each question, in keeping with their younger age compared to other studies.

Predictor Variables Parental education was measured using the highest level that a student’s parent(s) had completed based on a 6-point scale (1 ⫽ less than high school degree, 2 ⫽ high school degree, 3 ⫽ college education, 4 ⫽ bachelor’s degree, 5 ⫽ graduate school or master’s degree, 6 ⫽ more than master’s degree). When students

provided data for both parents, we used the highest education attainment as the indicator of parental education (M ⫽ 3.62, SD ⫽ 1.6). A student’s self-identified race/ethnicity and gender also were used as predictors, although we did not test specific hypotheses concerning the relationships of these variables with the outcomes. Family discussions of current events and politics (hereafter, family discussion) was measured by students’ responses to four statements (␣ ⫽ .76): “In my house we have many discussions about current events and politics”; “My parents discuss what’s happening in the world with me”; “I tell my parents my opinions about events in the news”; “Sometimes I argue with my parents about current events.” For all statements, responses were given on a Likert-type (1 ⫽ strongly disagree to 5 ⫽ strongly agree) scale. A family discussion factor was formed from the mean of these items with higher scores indicating more discussions (M ⫽ 3.12, SD ⫽ 0.9). In addition to this measure for individual families we created an aggregate mean of the level of family discussions of current events reported by participating students in each school (hereafter, classmates’ family discussions). The 13 participating schools were


divided into two groups based on the mean of these aggregate scores (3.06) with six schools falling below the mean and seven above the mean.1


Analytic Strategy Hypotheses 1–5 concerned the amount and complexity of adolescents’ understanding of poverty and wealth. To test the first hypothesis (that students would have more knowledge and a more complex understanding of wealth than poverty), paired-samples t tests were conducted, first on the mean number of answers to wealth vs. poverty and second on the IC scores for wealth versus poverty. Multiple regressions were used to test Hypotheses 2–5, i.e., that age and opportunities for learning (measured by parental education and family discussions of current events in individual families and aggregated across classmates’ families) would be positively associated with the amount and complexity of students’ understanding of inequality. First, we examined the relationship between the outcome variables (the total number of answers and IC scores for each question) and adolescents’ age, sex, race/ ethnicity, and level of their parents’ education (Model 1). Second, we estimated the full models with personal and classmates’ family discussions of current events added to the first model (Model 2). Hypotheses 6 –9 concerned the attributions (first response and pattern of responses) that adolescents used to explain poverty and wealth. Multinomial logistic regression analysis was used to test the relationship between predictor variables and adolescents’ attributions. First, we considered first responses only because they should capture what psychologists refer to as the “availability heuristic,” i.e., a reference to the relevant information that comes to mind or is retrieved from memory quickly and easily (Tversky & Kahneman, 1973). Second, we considered all of the attributions an adolescent gave for poverty or wealth and grouped them into four patterns: references only to individual, societal, or uncontrollable factors (unidimensional patterns) or to different factors (multidimensional patterns). We focused on the difference in the odds of using an individual, societal, or multidimensional answering pattern.2 Again, two models were estimated, the first with adolescent’s age, sex, race/ethnicity, and level of parents’ education (Model 1) and the second a full model with the addition of personal and classmates’ family discussions of current events (Model 2). All statistical analyses were carried out using the IBM SPSS software package (Version 20).

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ethnic groups, Arab Americans have lower levels of parental education but are more likely to engage in family discussions and to have classmates who engage in family discussions of current events. In contrast, compared to other racial/ethnic groups, not only do African Americans have lower levels of parental education, they also are less likely to attend schools with classmates who discuss current events at home.

Paired-Samples t Tests Results from paired-samples t tests confirmed our first hypothesis: Students had more knowledge and a more complex understanding of wealth than of poverty. They gave more answers to explain wealth than to explain poverty (M ⫽ 1.71, SD ⫽ 0.84 for wealth; M ⫽ 1.61, SD ⫽ 0.91 for poverty), t(592) ⫽ 2.521, p ⬍ .05, and had higher average IC scores for wealth than for poverty (M ⫽ 1.96, SD ⫽ 0.95 for wealth; M ⫽ 1.70, SD ⫽ 0.89 for poverty; p ⬍ .001).

Multiple Regressions

Results

Table 3 displays the results of regression models for the quantity and complexity of adolescents’ knowledge of poverty and of wealth (Hypotheses 2–5). Results confirmed our second hypothesis: age was positively related to the quantity of adolescents’ knowledge of poverty (␤ ⫽ .063, p ⬍ .05 in Model 1; ␤ ⫽ .071, p ⬍ .01 in Model 2) and of wealth (␤ ⫽ .082, p ⬍ .001; ␤ ⫽ .090, p ⬍ .001 in Model 2). Age was also positively associated with IC scores for poverty (␤ ⫽ .085, p ⬍ .01 in Model 1; ␤ ⫽ .090, p ⬍ .001 in Model 2) and for wealth (␤ ⫽ .086, p ⬍ .01 in Model 1; ␤ ⫽ .092, p ⬍ .01 in Model 2). In summary, compared to younger adolescents, older adolescents provided a greater number of explanations for wealth and for poverty and their explanations demonstrated a higher level of complexity, even when controls for family discussions and classmates’ family discussions of politics and current events were entered in the models. We found limited support for our third hypothesis. Parental education was positively related to the quantity of adolescents’ knowledge about wealth in Model 1 (␤ ⫽ .046, p ⬍ .05). However, when personal and classmates’ family discussions were introduced (Model 2), the positive relationship was no longer significant. This suggests that family discussions of current events may mediate the effects of parental education on adolescents’ knowledge of the ways that people become wealthy. Contrary to our hypothesis, parental education was unrelated to the quantity or complexity of

Table 2 presents the zero-order correlation matrix as well as means and standard deviations for all variables. Here we highlight relationships that are not tested in the regression models. First, as would be expected, the total number of answers given by an adolescent to explain poverty or wealth is correlated with the level of integrative complexity for that item. Second, the level of parental education for an individual adolescent is positively correlated not only with discussions of current events in his or her own family but also with similar discussions in his or her classmates’ families. Finally, two ethnic differences are noteworthy for what they reveal about sources for learning: Compared to other racial/

1 Although data in this study have a nested structure (i.e., students within schools), we do not use hierarchical linear modeling (HLM) due to the small number of schools (13) in the study and recommendations for the number of groups (e.g., 20 or more) for using HLM (Snijders & Bosker, 2012). 2 There were too few cases invoking only uncontrollable factors both for the poverty and wealth items and thus we did not include the results from the comparison of the uncontrollable pattern with the other response patterns. For first responses, 84 responses for poverty (14.17%) and 41 responses for wealth (6.91%) were excluded. For analyses of response patterns, some of these cases were included if they referenced a different category as their second or additional response. Respondents who did not give at least one reference to an individual, societal, or uncontrollable factor were excluded from the analyses of response patters (91 cases for poverty and 48 cases for wealth).

Descriptive Statistics

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Table 2 Zero-Order Correlations, Means, and Standard Deviations


Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. M SD

1

2

3

4

Total number of answers (poverty) 1.00 Total number of answers (wealth) .419ⴱⴱ 1.00 IC (poverty) .660ⴱⴱ .370ⴱⴱ 1.00 IC (wealth) .320ⴱⴱ .727ⴱⴱ .393ⴱⴱ 1.00 Sex (female) .077 .041 .036 .068 Age .103ⴱ .128ⴱⴱ .115ⴱⴱ .117ⴱⴱ African American ⫺.085ⴱ ⫺.069 ⫺.013 ⫺.068 Arab American .027 ⫺.017 ⫺.048 ⫺.008 Other race/ethnicity ⫺.067 ⫺.058 ⫺.017 ⫺.039 Parental education .022 .087ⴱ .028 .071 Family discussion of current events .077 .118ⴱⴱ .088ⴱ .123ⴱⴱ Classmates’ family discussions .146ⴱⴱ .153ⴱⴱ .043 .107ⴱ 1.61 1.71 1.68 1.93 0.91 0.84 0.88 0.96

5

6

7

1.00 ⫺.071 .059 ⫺.009 ⫺.021 ⫺.108ⴱ ⫺.007 ⫺.022 0.57 0.50

1.00 ⫺.013 .167ⴱⴱ ⫺.102ⴱ ⫺.166ⴱⴱ ⫺.035 ⫺.149ⴱⴱ 16.12 1.56

8

9

10

11

12

1.00 ⫺.179ⴱⴱ 1.00 ⫺.209ⴱⴱ ⫺.151ⴱⴱ 1.00 ⫺.179ⴱⴱ ⫺.221ⴱⴱ .086ⴱ 1.00 ⫺.064 .114ⴱⴱ ⫺.090ⴱ .127ⴱⴱ 1.00 ⫺.283ⴱⴱ .258ⴱⴱ ⫺.009 .415ⴱⴱ .282ⴱⴱ 1.00 0.20 0.11 0.15 3.62 3.12 0.53 0.40 0.32 0.36 1.60 0.90 0.50

Note. IC ⫽ integrative complexity. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

explanations for poverty and only marginally associated with the complexity scores for wealth. We found limited support for our fourth hypothesis: If an adolescent discussed current events and politics in his or her family, he or she gave a greater number of reasons (␤ ⫽ .083, p ⬍ .05) and had a more complex understanding (␤ ⫽ .119, p ⬍ .05) of wealth. However, such family discussions were not related to adolescents’ explanations for poverty and were only marginally related to their IC scores for poverty.

We found partial support for our fifth hypothesis: Adolescents gave a greater number of responses to explain poverty and wealth if they attended schools with classmates who engaged in family discussions of current events (␤ ⫽ .318, p ⬍ .01 for poverty; ␤ ⫽ .234, p ⬍ .01 for wealth). However, adolescents’ IC scores were not associated with attending schools with classmates who engaged in such family discussions. Finally, although we had not hypothesized racial/ethnic or gender differences, the multiple regressions revealed some differ-

Table 3 Multiple Regressions for Quantity and Complexity of Answers for Poverty and Wealth Quantity (poverty) Variable Sex (female) Age African American Arab American Othera Parental education Family discussionb Classmates’ family discussionsc

Model 1

Model 2

ⴱ

ⴱ

.189 (.078) .063ⴱ (.026) ⫺.226ⴱ (.106) ⫺.041 (.129) ⫺.195† (.111) .019 (.025)

.173 (.078) .071ⴱⴱ (.026) ⫺.170 (.107) ⫺.224 (.137) ⫺.171 (.111) ⫺.029 (.029) .046 (.045) .318ⴱⴱ (.096)

Complexity (poverty) Model 1 Sex (female) Age African American Arab American Othera Parental education Family discussionb Classmates’ family discussionsc

.080 (.080) .085ⴱⴱ (.026) ⫺.020 (.108) ⫺.174 (.132) ⫺.035 (.116) .025 (.026)

Model 2 .078 (.080) .090ⴱⴱⴱ (.027) .016 (.110) ⫺.255† (.141) ⫺.003 (.116) .005 (.030) .086† (.046) .104 (.099)

Quantity (wealth) Model 1

Model 2

.112 (.072) .082ⴱⴱⴱ (.024) ⫺.241ⴱ (.098) ⫺.101 (.120) ⫺.166 (.103) .046ⴱ (.024)

.106 (.072) .090ⴱⴱⴱ (.024) ⫺.194† (.099) ⫺.245† (.127) ⫺.133 (.103) .010 (.027) .083ⴱ (.041) .234ⴱⴱ (.089)

Complexity (wealth) Model 1 ⴱ

.187 (.085) .086ⴱⴱ (.028) ⫺.221† (.116) ⫺.058 (.140) ⫺.121 (.119) .050† (.027)

Model 2 .171ⴱ (.085) .092ⴱⴱ (.028) ⫺.177 (.117) ⫺.195 (.150) ⫺.089 (.119) .017 (.031) .119ⴱ (.048) .167 (.105)

Note. Unstandardized beta values (and standard errors) are reported. European American is the reference group for race/ethnicity. a Other race/ethnicity group includes American Indian, Asian American, and Hispanic American. b Personal family discussions of current events and politics. c Shared (classmates) family discussions of current events and politics. † p ⬍ .1. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.



ences. As shown in Table 3, compared to European Americans, African American students gave fewer explanations for poverty or wealth (␤ ⫽ –.226, p ⬍ .05 for poverty; ␤ ⫽ –.241, p ⬍ .05 for wealth) and marginally less complex explanations for wealth (␤ ⫽ –.221, p ⬍ .1) in Model 1. However, these differences were not significant when family and classmates’ discussions of current events were added (Model 2). In addition, females had more knowledge about poverty than their male peers, based on the number of explanations that they offered (␤ ⫽ .189, p ⬍ .05 in Model 1; ␤ ⫽ .173, p ⬍ .05 in Model 2). Females also had higher IC scores for wealth than their male peers (␤ ⫽ .187, p ⬍ .05 in Model 1; ␤ ⫽ .171, p ⬍ .05 in Model 2). Next we turn to the results for the variables associated with the content of adolescents’ explanations, i.e., the likelihood of endorsing a societal factor in the first response and the likelihood of endorsing societal or mixed factors in the pattern of responses. First answer. With regard to the first or “most available” response, adolescents offered more societal than individual attributions for poverty (241 societal and 182 individual); in contrast, they offered more individual than societal attributions for wealth (201 societal and 280 individual). As shown in Table 4, adolescents whose parents had medium (some college or BA) or high (graduate or professional degree) levels of education tended to give more societal than individual attributions for poverty. In contrast, those in the least educated (high school or less) families were equally likely to hold individuals and society responsible and noted more uncontrollable factors contributing to poverty. For wealth, adolescents whose parents had the lowest or medium levels of education gave far more individual than societal attributions. In contrast those whose parents had the highest levels of education were equally likely to give societal or individual attributions for wealth.

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Partial support was also found for our seventh hypothesis, i.e., the higher an adolescent’s parents’ education, the more likely he or she was to give societal rather than individual causes for poverty (␤ ⫽ .242, OR ⫽ 1.274, p ⬍ .001 in Model 1; ␤ ⫽ .164, OR ⫽ 1.178, p ⬍ .05 in Model 2). Parental education also was positively associated with the odds of offering societal rather than uncontrollable causes for poverty, regardless of whether personal and classmates’ family discussion variables were added (␤ ⫽ –.359, OR ⫽ 0.698, p ⬍ .01 in Model 1; ␤ ⫽ –.319, OR ⫽ 0.727, p ⬍ .01 in Model 2). As expected, family discussions of current events increased the likelihood that an adolescent would offer a societal rather than an individual attribution as their first explanation for poverty (␤ ⫽ .257, OR ⫽ 1.293, p ⬍ .05). Female students were more likely than their male peers to state societal rather than individual attributions for poverty (␤ ⫽ .470, OR ⫽ 1.600, p ⬍ .05 in Model 1; ␤ ⫽ .434, OR ⫽ 1.543, p ⬍ .05 in Model 2) and to mention uncontrollable rather than individual causes (␤ ⫽ .732, OR ⫽ 2.079, p ⬍ .05 in Model 1). However, in the full model, this gender difference was only marginally significant (p ⬍ .1). There was only one effect of ethnicity: Compared to Euro American students, Arab American students were less likely to give societal rather than individual attributions as their first response for poverty (␤ ⫽ –.971, OR ⫽ 0.379, p ⬍ .05 in Model 2). First response for wealth. For wealth, there were fewer significant differences in the odds of giving one kind of attribution over another. In Model 1, higher parental education increased the likelihood that an adolescent would give a societal rather than individual attribution (␤ ⫽ .142, OR ⫽ 1.153, p ⬍ .05). However, this association disappeared when personal and classmates’ family discussion variables were added. Attending schools where one’s classmates engaged in family discussions of current events increased the odds that a student would give a societal rather than individual explanation (␤ ⫽ .508, OR ⫽ 1.662, p ⬍ .05). Females were less likely than their male peers to explain wealth by invoking uncontrollable rather than societal factors (␤ ⫽ –1.047, OR ⫽ 0.351 in Model 1; ␤ ⫽ –1.044, OR ⫽ 0.352 in Model 2, p ⬍ .01) or uncontrollable rather than individual causes (␤ ⫽ –.758, OR ⫽ 0.469 in Model 1; ␤ ⫽ –.770, OR ⫽ 0.463 in Model 2; p ⬍ .05 in both Models). In summary, for their first responses, adolescents gave more societal explanations for poverty and more individual explanations for wealth. For their first responses explaining poverty, older students and those whose families discussed current events were more likely to mention societal, as opposed to individual factors

Logistic Regressions First response for poverty. Table 5 presents the results from multinomial logistic regressions on adolescents’ first responses for poverty and wealth. Concerning poverty, as expected, older students were more likely to provide societal rather than individual causes as the first answer, whether personal and classmates’ family discussions of current events were added or not (␤ ⫽ .207, odds ratio [OR] ⫽ 1.230, p ⬍ .01 in Model 1; ␤ ⫽ .235, OR ⫽ 1.265, p ⬍ .01 in Model 2). However, age was unrelated to the likelihood of giving a societal rather than individual cause as the first answer for wealth (H6).

Table 4 The First Answer for Poverty and Wealth Questions by Parents’ Education Level Poverty Variable Individual Societal Uncontrollable Total

L

M

Wealth H

L

M

H

62 (43.66%) 64 (39.02%) 48 (31.58%) 98 (60.87%) 93 (51.67%) 77 (46.67%) 59 (41.55%) 82 (50%) 96 (63.16%) 52 (32.3%) 71 (39.44%) 70 (42.42%) 21 (14.79%) 18 (10.98%) 8 (5.26%) 11 (6.83%) 16 (8.89%) 18 (10.91%) 142 (100%) 164 (100%) 152 (100%) 161 (100%) 180 (100%) 165 (100%)

Note. L ⫽ High school degree or less; M ⫽ Some college or BA; H ⫽ Graduate or Professional School. The “Other” category is omitted. Numbers reflect cases for which there were data on parental education.

FLANAGAN ET AL.

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Table 5 Multinomial Logistic Regressions for the First Answer to Poverty and Wealth Questions Ia versus S Variable

Model 1

Sex (female) Age African American Arab American Otherb Parental education Family discussionc Classmates’ family discussionsd

.470ⴱ .207ⴱⴱ .096 ⫺.586 ⫺.061 .242ⴱⴱⴱ

Sex (female) Age African American Othere Parental education Family discussionc Classmates’ family discussionsd

.289 .015 ⫺.054 .041 .142ⴱ

Sa versus U

Model 2

Ia versus U

Model 1

Model 2

Model 1

Model 2

.262 ⫺.172 .529 .645 ⫺.587 ⫺.359ⴱⴱ

.242 ⫺.187 .512 .853 ⫺.637 ⫺.319ⴱ ⫺.349† ⫺.164

.732ⴱ .035 .625 .059 ⫺.648 ⫺.118

.676† .049 .673 ⫺.118 ⫺.616 ⫺.155 ⫺.092 .356

⫺1.047ⴱⴱ .039 .240 ⫺.697 .073

⫺1.044ⴱⴱ .055 .354 ⫺.661 .103 ⫺.216 .056

⫺.758ⴱ .054 .185 ⫺.656 .215†

⫺.770ⴱ .079 .406 ⫺.706 .187 ⫺.107 .564


Poverty .434ⴱ .235ⴱⴱ .161 ⫺.971ⴱ .020 .164ⴱ .257ⴱ .520† Wealth .273 .024 .052 ⫺.045 .084 .109 .508ⴱ

Note. I ⫽ Individual attribution; S ⫽ Societal attribution; U ⫽ Uncontrollable attribution. Unstandardized beta values are reported. European American is the reference group for race/ethnicity. a Reference attribution category. b Other race/ethnicity group includes American Indian, Asian American, and Hispanic American. c Personal family discussions of current events and politics. d Shared (classmates’) family discussions of current events and politics. e For wealth, Other race/ethnicity group includes Arab American, American Indian, Asian American, and Hispanic American because no Arab American provided the Uncontrollable attribution answer. † p ⬍ .1. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

Table 6 presents the answering patterns by parental education level. For poverty, regardless of their parents’ educational background, approximately 30% of the explanations reflected a mixture of categories. In addition, adolescents in the least educated families tended to endorse individual causes, whereas those in the middle- and highest-educated families tended to endorse societal causes. When explaining wealth, more than one-third of the adolescents used a mixture of categories (nearly 39% of the adolescents in the least educated families, 36% in the mideducated families and almost 50% of those in the most educated families). In addition, adolescents in the least educated families were more likely to invoke individual causes for wealth (almost 41%) when compared to their peers whose parents had the middle- (34%) or highest-levels of education (almost 24%).

and adolescents in better educated families were more likely to mention societal as opposed to individual or uncontrollable factors. Finally, females were more likely than males to mention a societal rather than individual factor and Arab Americans were less likely than Euro Americans to mention a societal rather than an individual factor. Concerning first responses for wealth, attending schools with classmates whose families discussed current events increased the odds of giving a societal rather than individual first response and females were more likely than males to give societal rather than individual or uncontrollable explanations. Answering patterns. In explaining why some people are rich, multidimensional patterns had the highest frequency followed by individual patterns. To explain why some people are poor, societal/ structural patterns were the most frequent followed by roughly equal percentages of multidimensional or individual patterns.

Table 6 Answering Patterns for Poverty and Wealth Questions by Parents’ Education Level Poverty Variable

L

M

Individual Societal Uncontrollable Mixed Total

55 (35.26%) 46 (29.49%) 11 (7.05%) 44 (28.21%) 156 (100%)

42 (24.56%) 65 (38.01%) 12 (7.02%) 52 (30.41%) 171(100%)

Wealth H

L

M

H

29 (18.13%) 68 (40.72%) 63 (34.05%) 40 (23.67%) 80 (50%) 30 (17.96%) 47 (25.41%) 40 (23.67%) 4 (2.5%) 4 (2.4%) 8 (4.32%) 5 (2.96%) 47 (29.38%) 65 (38.92%) 67 (36.22%) 84 (49.7%) 160 (100%) 167 (100%) 185 (100%) 169 (100%)

Note. L ⫽ High school degree or less; M ⫽ Some college or BA; H ⫽ Graduate school. Numbers reflect cases for which there were data on parental education.



The results from multinomial logistic regressions on students’ pattern of responses are presented in Table 7. When explaining poverty, older students were more likely to invoke societal than individual attributions, (␤ ⫽ .255, OR ⫽ 1.290, p ⬍ .01 in Model 1; ␤ ⫽ .294, OR ⫽ 1.342, p ⬍ .01 in Model 2) and to provide a multidimensional rather than an individual response pattern (␤ ⫽ .205, OR ⫽ 1.228, p ⬍ .05 in Model 1; ␤ ⫽ .254, OR ⫽ 1.289, p ⬍ .01 in Model 2). Having better educated parents increased the odds that a student would give societal rather than individual attribution patterns in both Model 1 and Model 2 (␤ ⫽ .353, OR ⫽ 1.423, p ⬍ .001 and ␤ ⫽ .287, OR ⫽ 1.332, p ⬍ .01, respectively). Higher levels of parental education also increased the likelihood of giving a multidimensional rather than individual attribution pattern for poverty (␤ ⫽ .223, OR ⫽ 1.250, p ⬍ .05 in Model 1), although the effect was no longer significant when discussions of current events were added in Model 2. Attending schools with classmates whose families were above the mean in discussions of current events increased the odds that a student would offer societal rather than individual patterns by 1.879 times over their peers who attended schools with classmates whose families were below the mean in discussing current events (␤ ⫽ .631, OR ⫽ 1.879, p ⬍ .05). However, an adolescent’s own family discussions were not associated with his or her response pattern when explaining poverty. Finally, females were more likely than their male peers to give societal over individual and multidimensional over individual response patterns to explain poverty.

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In summary, being older, female, having better educated parents and attending schools with classmates whose families discussed current events increased the odds that an adolescent would explain poverty with a societal rather than an individual pattern of attributions. Being older and female increased the likelihood of giving a multidimensional as opposed to an individual pattern of attributions for poverty. We found fewer predictors of the answering patterns for wealth. In Model 1, parental education was positively associated with the odds of giving societal (␤ ⫽ .186, OR ⫽ 1.204, p ⬍ .05 in Model 1), or multidimensional (␤ ⫽ .173, OR ⫽ 1.189, p ⬍ .05 in Model 1), rather than individual response patterns. However, there was no effect of parental education on answering patterns in Model 2.

Discussion This study sheds light on the development of adolescents’ lay theories about inequality, a domain of sociocentric knowledge that has received relatively little scholarly attention. Adolescents had more knowledge about wealth than about poverty, which is consistent with results for the general public and likely reflects the disproportionate attention in mass media to the lives and concerns of the wealthy (Kendall, 2005). According to Hatano and Takahashi (2005), mass media is one of three pathways through which children and adolescents develop knowledge about society. That said, the content of adolescents’ attributions revealed differences in the way they conceived of ways that people might become rich or poor. Consistent with earlier studies of adolescents (Leahy,

Table 7 Multinomial Logistic Regressions for Answering Patterns for Poverty and Wealth Ia versus S Variable

Model 1

Sex (female) Age African American Arab American Otherb Parental education Family discussionc Classmates’ family discussionsd

.696ⴱⴱ .255ⴱⴱ ⫺.334 ⫺.290 .165 .353ⴱⴱⴱ

Sex (female) Age African American Othere Parental education Family discussionc Classmates’ family discussionsd

.236 .006 .028 .047 .186ⴱ

Model 2

Sa versus M

Ia versus M

Model 1

Model 2

Model 1

Model 2

⫺.069 ⫺.050 .192 .100 ⫺.118 ⫺.130†

⫺.064 ⫺.040 .234 .097 ⫺.094 ⫺.126 .057 ⫺.043

.626ⴱ .205ⴱ ⫺.142 ⫺.190 .047 .223ⴱ

.611ⴱ .254ⴱⴱ ⫺.018 ⫺.595 .174 .161† .196 .589†

⫺.068 .082 ⫺.475 ⫺.278 ⫺.013

⫺.031 .075 ⫺.531 ⫺.246 .008 .046 ⫺.154

.169 .087 ⫺.447 ⫺.231 .173ⴱ

.171 .099 ⫺.365 ⫺.313 .126 .189 .423

Poverty .675ⴱⴱ .294ⴱⴱ ⫺.251 ⫺.692 .268 .287ⴱⴱ .138 .631ⴱ Wealth .203 .024 .166 ⫺.068 .118 .143 .577†

Note. I ⫽ Individual answering pattern; S ⫽ Societal answering pattern; M ⫽ Multidimensional answering pattern. Unstandardized beta values are reported. Results related to the Other answering pattern are not reported. European American is the reference group for race/ethnicity. a Reference answering pattern category. b Other race/ethnicity group includes American Indian, Asian American, and Hispanic American. c Personal family discussions of current events and politics. d Shared (classmates) family discussions of current events and politics. e For wealth, Other race/ethnicity group includes Arab American, American Indian, Asian American, and Hispanic American because no Arab American provided the Uncontrollable attribution answer. † p ⬍ .1. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.


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FLANAGAN ET AL.

1983; Skafte, 1989), whereas they gave credit to the wealthy for working hard (31% of the explanations invoked effort or hard work, followed by 11.4% referring to one’s birth or family background), they were more measured in their explanations for why people might be poor, holding both society (the most common first response, 18.2%, referred to the lack of jobs) and individuals (14.1% referring to a lack of motivation) accountable. The results also confirmed age differences in understanding inequality found in other studies (Dotson & Hyatt, 2005; Emler & Dickinson, 2005). Older adolescents gave a greater number of explanations and, based on their Integrative Complexity scores, demonstrated a more complex appreciation of wealth and of poverty than did younger adolescents. The results are consistent with the age-related increases in capacities to classify groups noted in developmental intergroup theory (DIT; Bigler & Liben, 2007) and to classify one’s own social class position in the class hierarchy (Goodman et al., 2001). Older adolescents also were more likely to attribute poverty to societal or multidimensional rather than individual factors. The effects of age on adolescents’ theories about inequality held even when parental education and discussions of current events were controlled. The fact that older adolescents were more likely to mention different categories in their explanations for poverty supports Emler and Dickinson’s (2005) thesis that age-related changes in sociocentric understanding reflect additions to (rather than replacements of) the repertoire of ideas that adolescents have at their disposal. They also support sociologists’ observations that structural attributions for inequality tend to be layered on to (rather than replace) individualistic attributions (Bobo, 1991; Hochschild, 1995). As research on social cognition documents (Smetana & Villalobos, 2009), as adolescents develop, they have more knowledge about society and greater capacities to grapple with abstract concepts such as structural or systemic factors underlying inequality. The results also echo the age-related increase in awareness of systemic factors underlying inequality that has been found in other work (Furby, 1979; Harrah & Friedman, 1990). However, our results challenge contentions that, because the relationship between individual merit and social status becomes more salient with age, older adolescents also would be more likely to legitimize inequality (Leahy, 1983). In fact, their use of societal/systemic attributions to explain poverty and their higher IC scores suggest that older adolescents are more cognitively prepared than their younger peers to mount structural critiques challenging widespread beliefs that the poor are responsible for their station (Jost et al., 2009). Our study also reveals differences in opportunities to learn about society that accrue to adolescents from different social classes, opportunities that may underlie the social class differences in economic understanding identified in earlier studies (Emler & Dickinson, 2005; Enright, Enright, Manheim, & Harris, 1980; Goodman et al., 2000). Specifically, adolescents were more likely to engage in discussions of current events and politics if their parents had higher levels of education. Furthermore, adolescents in better-educated families attended schools where their classmates’ parents were well educated and those classmates were more likely to participate in family discussions of current events and politics. Insofar as families and schools operate as a mesosystem (Bronfenbrenner, 1979), we found a spillover effect: Attending schools

with classmates who discussed current events in their families increased an adolescent’s knowledge about poverty and wealth. It also increased the likelihood that he or she would list structural rather than individual factors underlying poverty. The “classmates” effect was in addition to the increased likelihood of structural attributions for poverty given by adolescents in better educated families. Adolescents in better educated families also were more likely to mention societal or multidimensional (rather than individual) factors to explain wealth, but these differences were mediated by attending school with classmates who discussed current events with their families. The increasing awareness of structural factors underlying poverty that accrues from exposure to current events discussions converges with results found for curricular interventions that educate students about the structural factors underlying poverty (Seider et al., 2011). The social class differences in adolescents’ exposure to discussions of current events and politics echo other work documenting social class disparities in opportunities for civic learning and understanding (Hart & Atkins, 2002; Kahne & Middaugh, 2009). Gender differences in adolescents’ attributions for inequality found in this study are consistent with those found in research with adults: compared to males, females appreciate the multiple factors, including structural ones, underlying inequality (Bullock, 2006; Mestre, Samper, Frias, & Tur, 2009). Females’ awareness of the extenuating circumstances faced by the poor is consistent with women’s tendencies to use care-oriented prosocial reasoning as the bases for their moral judgments (see meta-analysis by Jaffee & Hyde, 2000) and also fits with gender socialization studies showing that parents are more likely to emphasize values of caring, helping, and attending to others’ needs when raising daughters than when raising sons (Eisenberg & Morris, 2004). Two ethnic differences also emerged in our results. First, compared to European Americans, African Americans gave fewer explanations for inequality, and these effects were mediated by the fact that African Americans were less likely to attend schools where classmates discussed current events at home. Concerning the content of attributions, Arab Americans were more likely than European Americans to give individual rather than societal attributions for poverty. This may reflect the relatively new immigrant status of this group of Arab Americans and the tendency of new immigrants to hew to beliefs in the potential of individuals to succeed by dint of hard work. Compared to European Americans, both Arab and African Americans lived in households with lower levels of parent education. However, Arab Americans were more likely than other students to discuss current events in their families and to have classmates who did the same. These ethnic differences in attention to current events and politics may reflect attention to U.S. policy in the Middle East as well as a greater awareness of stereotypes about their ethnic group.

Limitations There were several limitations of this study. First, besides classmates’ reports of family discussions of current events, we did not have other information about how students might learn about inequality at school through direct instruction or practices such as service learning. Second, our measure of the “ripple effects” of classmates’ family discussions of current events was an indirect measure of students’ exposure to a wider range of



information about factors contributing to inequality. For a more direct test, we would have had to include a measure of classmates’ sharing of information. Third, parental education was our only measure of an adolescent’s social class background, although this was the most relevant dimension of SES for the study’s purpose and adolescents have more accurate knowledge of parents’ educational attainment than they do of their occupation or income (Diemer, Mistry, Wadsworth, Lopez, & Reimers, 2013). Finally, we relied on open-ended responses on surveys. Using personal interviews might have allowed more probing of adolescents’ understanding. Nonetheless, this is one of only a handful of studies to examine adolescents’ understanding of inequality. In light of the pervasive effects of the economy on young people and of trends pointing to increasing inequality, more attention should be paid to how young people understand this very basic dimension of their society.

Conclusions Adolescents today are growing up in a more unequal society than that of earlier generations. The results of this study suggest that adolescents in better educated families have more knowledge about the factors contributing to inequality because they have more exposure to discussions of current events and politics. According to system justification theory, these youths’ capacities to challenge the system imply their greater cognitive complexity and tolerance of uncertainty and ambiguity (Jost et al., 2009). But that ability to critique the system and to tolerate uncertainty also reflects the safety net of privilege. In other words, it may be easier to critique the system from a position of advantage since one’s own group is less likely to suffer the consequences of an unequal system. Ironically, for those who do suffer the consequences of an unequal system, who have no other ways to manage uncertainty, endorsing individual responsibility and justifying the system may restore a sense of confidence and control (Jost et al., 2003). Concerning the function of beliefs about inequality, note that it was adolescents in the least privileged circumstances (whose parents had lower levels of education, whose schools were located in low-income communities, and whose classmates reported few discussions of current events at home) who were more likely to contend that people were poor because they did not work hard or had not studied in school and that people were rich because they were smart, motivated, worked and studied hard. These adolescents’ beliefs about social mobility are consistent with their behaviors: Despite high drop out rates in their schools, these adolescents have remained in school. Their beliefs in the efficacy of individual effort for social mobility echo the commitments noted in other studies of low-income groups (Bullock & Limbert, 2003; Dalbert, 2001; Kluegel & Smith, 1986). Such beliefs may be functional for low-income groups insofar as the links between motivation and beliefs in a just world (that people get what they deserve) are stronger for students from low SES backgrounds (Laurin, Fitzsimmons, & Kay, 2011). To persevere in school, it is functional for those with few safety nets to believe in a system that rewards individual effort. How else can they hope to attain the American dream?

2523 References

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Received May 8, 2012 Revision received June 9, 2014 Accepted July 11, 2014 䡲

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