Abstract
Three studies conducted among fifth and sixth graders examined how school contexts disrupt the achievement of working-class students by staging unfair comparison with their advantaged middle-class peers. In regular classrooms, differences in performance among students are usually showcased in a way that does not acknowledge the advantage (i.e., higher cultural capital) experienced by middle-class students, whose upbringing affords them more familiarity with the academic culture than their working-class peers have. Results of Study 1 revealed that rendering differences in performance visible in the classroom by having students raise their hands was enough to undermine the achievement of working-class students. In Studies 2 and 3, we manipulated students’ familiarity with an arbitrary standard as a proxy for social class. Our results suggest that classroom settings that make differences in performance visible undermine the achievement of the students who are less familiar with academic culture. In Study 3, we showed that being aware of the advantage in familiarity with a task restores the performance of the students who have less familiarity with the task.
Keywords
Although the relationship between social class and academic achievement has been documented in countless studies, the processes by which social class translates into differences in academic achievement are far from fully understood. The present article focuses on how classroom arrangements and social class interact to reproduce social inequality, an overlooked cause of the social-class achievement gap.
Social class is associated with important economic and cultural differences known to dramatically affect educational outcomes (APA Task Force on Socioeconomic Status, 2007). Relative to middle-class families, low-income families face important structural and economic barriers that can deprive them of basic necessities, such as enough food or access to adequate educational facilities or resources (e.g., Ackerman, Brown, & Izard, 2004; Duncan & Brooks-Gunn, 1997). Partly because of the same barriers, working-class parents are also less likely than those from the middle class to engage in cultural practices that facilitate academic success, such as reading stories to children or frequenting museums (e.g., Bradley, Corwyn, McAdoo, & Garcia Coll, 2001). But these inequalities do not tell the whole story.
Educational contexts also play a role in the gap in achievement between social classes. For example, classrooms are not immune from negative stereotypes about social class that disrupt the achievement of low-income students and boost self-efficacy among their better-off peers (Croizet & Millet, 2012). Academic contexts can also prompt competitive motivation (rather than mastery goals), which impairs the achievement of working-class students and facilitates that of the middle-class students (Smeding, Darnon, Souchal, Toczek-Capelle, & Butera, 2013). Far from being neutral, however, education is inherently saturated with implicit cultural norms that advantage middle-class students (Bourdieu & Passeron, 1990; Stephens, Markus, & Phillips, 2014). Indeed, academic contexts value some forms of language use (Carter, 2003; Lahire, 1993), academic attitudes (Blackledge, 2001), school knowledge (Lareau & Weininger, 2003), bodily posture (Bourdieu, 1979), and models of agency (Stephens et al., 2014) that are closer to the cultural dispositions shaped in the middle class (Lareau, 2003). For instance, education favors the use of written language, the expression of personal opinions, and interest in the arts and literature, all things that match the cultural practices of middle-class families (Lareau, 2001).
This unequal overlap between academic and family cultural practices indicates that academic norms reflect some degree of cultural arbitrariness (Bourdieu & Passeron, 1990; Labov, 1970). This cultural arbitrariness has consequences. Being at ease with these norms makes middle-class students more familiar with academic expectations and gives them a head start in the classroom. Familiarity with the academic standards therefore constitutes a cultural capital (Bourdieu & Passeron, 1990; Lamont & Lareau, 1988). However, entering the classroom with more cultural capital does more than facilitate performance: Because classrooms are conceived to be as a level playing field, having higher cultural capital also means being perceived as being smarter (Kelley, 1967; Plaut & Markus, 2005).
In the experiments reported here, our goal was to document a general process through which this contingent advantage unfolds in the classroom. Our hypothesis was that school fuels the social-class achievement gap by enabling unfair social comparisons among students. More specifically, we argue that educational contexts undermine the achievement of disadvantaged students by showcasing differences in students’ performance in a way that does not acknowledge the reality that certain students, because of their social background, are already familiar with the academic standard. Indeed, being outperformed by other students can threaten self-image (Huguet et al., 2009; Muller & Butera, 2007; Rogers & Feller, 2016) and trigger self-doubt about incompetence that taxes cognitive resources and undermines higher cognition (Autin & Croizet, 2012). Because of their relative lack of familiarity with academic standards, working-class students should therefore be prone to experience debilitating social comparisons.
We tested this hypothesis in three studies conducted among fifth and sixth graders in their regular classrooms. Given the well-documented social-class differences in familiarity with academic culture (Lahire, 1993, 2008; Lareau, 2003), Study 1 focused on reading comprehension. Our goal was to examine whether rendering students’ performance differences visible in the classroom without acknowledging disadvantages in cultural capital was enough to widen the achievement gap between social classes. Social class is confounded with multiple variables and processes; therefore, in Studies 2 and 3, we manipulated cultural capital (i.e., students’ familiarity with an arbitrary academic standard) as a proxy for social class. In Study 2, we used an arbitrary written language, and students were made more or less familiar with it through a training exercise before being tested on the language. Finally, in Study 3, to test whether being oblivious to the disadvantage regarding academic standards is related to the underachievement of the students who have less familiarity with academic standards, we also manipulated awareness of the disadvantage.
Study 1
In Study 1, we examined whether academic situations that make differences in students’ performance visible in the classroom impaired working-class students’ performance in reading comprehension, an exercise with which such students would be less familiar (e.g., Lahire, 1993). Sixth graders took a difficult reading-comprehension test and had to answer successive questions displayed on the board. So that any differences in the students’ performance were visible, we asked students to raise their hands each time they completed an answer. In another condition, no such requirement was made, thereby minimizing the visibility of differences in students’ performance. We expected that simply having students raise their hands would lead working-class students to experience a disruptive social comparison, which we expected would undermine their achievement.
Method
Participants
A total of 953 students in the sixth grade (40 classrooms, 8 middle schools) voluntarily enrolled in the experiment with administrative authorization and parental consent (456 girls, 497 boys; mean age = 11.5 years, SD = 0.90). Sample size was determined by the number of schools that agreed to participate in the study. To ensure the anonymity of the collected data (sex, date of birth, occupation of parents, and students’ academic level in French—i.e., their grade point averages), the schools attributed a random identification code to each student by the school administration, and we used this code to match students’ performance and administrative records. We excluded from the analyses the data from 16 students who had specific reading disorders and from 2 students for whom parental occupations were unknown. We also excluded the data from 191 students whose parents’ occupation (e.g., “military personnel,” “intermediate civil servant”) could not be classified as either working class or upper middle class (see the criteria in the next section; Croizet & Claire, 1998). The proportion of working-class students and upper-middle-class students did not differ across schools, χ2(7, N = 744) = 8.10, p = .324, or classrooms, χ2(39, N = 744) = 27.70, p = .912, which suggests that school and classroom composition was relatively consistent. The final sample included 744 students in the sixth grade, assigned to groups for social class as described in the next paragraph. Finally, in each school, classrooms were randomly assigned to one of the two assessment conditions (visibility of differences in achievement: visible vs. not visible).
Social class
Social class was assessed according to parental occupations (see Croizet & Claire, 1998). It was the only indicator available from the French school authorities. Information about ethnicity was not available because this information cannot legally be collected in France. Social-class ranking was determined by the highest level of occupation held by either parent. For example, if the mother was a physician and the father a manual worker, the student was assigned to the upper-middle-class group. Separate analyses conducted regarding social class, defined by either the father’s or mother’s occupation, yielded similar results. Students in the working-class group included children of manual laborers (55.4%), administrative workers (24.1%), other blue-collar workers (employees, artisans, farmers, 12.7%), and unemployed persons (7.8%). Students in the upper-middle-class group included children of managers (63.8%), researchers and professors (23.6%), professionals (10%), and miscellaneous occupations (2.6%). Our final sample included 473 working-class students and 271 upper-middle-class students.
Materials and procedure
In each middle school, the experiment was conducted in the same room for all classrooms. Children took a national standardized reading-comprehension test that was difficult because it was designed for seventh graders 1 (Ministère de l’Education Nationale de la Recherche et de l’Enseignement Supérieur, 2003; also see Autin & Croizet, 2012). The experiment was introduced to the students as an assessment of their reading and comprehension ability. Students were first asked to read a difficult text, which remained available to them throughout the test. Then, they had to answer 15 questions displayed successively on slides, and students had 45 s to write each answer in a notebook. The reading test was scored according to the number of correct answers. Because some questions involved up to three answers, the possible score ranged from 0 to 20.
Visibility of differences in performance
In the visibility condition, performance differences among students were suggested: Students were required to raise their hands if they believed they had the answer before the allotted time. In the no-visibility condition, differences in performance remained unnoticed because students were explicitly told not to signal to the experimenter when they were done answering a question. After the experiment, students were thanked and debriefed. They were informed that the task was very difficult for sixth graders and that experiencing difficulty was normal and expected. To avoid contamination among participants within a given school, we ran the experiment in half a day, which involved obtaining special permission and organizing the time so that students in one given classroom could never pass students from other classrooms: Different recess times were scheduled, and each class group was escorted to the experiment room by a teaching assistant.
Results
Analyses were performed using the lme4 (Bates, Maechler, Bolker, & Walker, 2013) and lmerTest packages (Kuznetsova, Brockhoff, & Christensen, 2016) for the R software environment (Version 3.1.2; R Development Core Team, 2014). We relied on linear mixed modeling to deal with the nonindependence in the data—students were nested within classrooms, which were nested in schools (Westfall, Kenny, & Judd, 2014). The Bayesian information criterion (Schwarz, 1978) was used to evaluate the goodness of fit for each model (Pitt & Myung, 2002). All the mixed effects were tested using likelihood-ratio tests (Pinheiro & Bates, 2000). The model with the most complex adjustment (Barr, Levy, Scheepers, & Tily, 2013) and the smallest Bayesian information criterion was retained. It included by-school and by-classroom random intercepts, social class, the visibility of differences in performance, and the interaction of social class and the visibility of differences in performance as fixed effects. Because the number of participants varied across groups, a Satterthwaite correction was used to estimate degrees of freedom.
The number of correct answers on the reading-comprehension test constituted our dependent variable. We first tested for effects of gender and academic level in French, recoding each value as the deviation from the mean (i.e., x minus the mean of x). These analyses revealed significant main effects of both gender (boys: M = 8.92, SD = 3.98, 95% confidence interval, or CI = [8.64, 9.21]; girls: M = 9.80, SD = 4.08, 95% CI = [9.51, 10.09]), F(1, 743.60) = 12.00, p < .001, 2 and academic level, b = 0.60, 95% CI = [0.54, 0.75], F(1, 742.29) = 169.09, p < .001. However, these factors did not moderate the effects of our focal variables (visibility of differences in performance and social class) on reading-comprehension and were dropped from the reported analysis. The analysis yielded a main effect of social class: Reading-comprehension scores for working-class students, M = 8.28, SD = 3.77, 95% CI = [8.01, 8.55], were lower than those of upper-middle-class students, M = 11.21, SD = 3.84, 95% CI = [10.93, 11.48], F(1, 740.28) = 108.52, p < .001. The analysis also showed a main effect of the visibility of differences in achievement. Students’ performance was lower when differences in knowledge became visible through hand raising, M = 8.66, SD = 4.14, 95% CI = [8.36, 8.95], than when they were not, M = 10.06, SD = 3.83, 95% CI = [9.78, 10.34], F(1, 741.66) = 16.19, p < .001. These main effects were qualified by the expected interaction between social class and visibility, F(1, 740.39) = 23.80, p < .001 (see Fig. 1).
Results for Study 1: reading-comprehension score (number of correct answers) as a function of social class (working class vs. upper-middle class), presented separately for classrooms in which differences in performance were visible and were not visible during the test (not visible: hand down vs. visible: hand raising). Scores ranged from 0 to 20. Error bars represent +1 SEM.
In accordance with our hypothesis, the social-class gap in reading comprehension increased when differences in performance were visible. As predicted, students from working-class backgrounds underperformed when the superior performance of their peers was suggested through hand raising, M = 7.09, SD = 3.52, 95% CI = [6.85, 7.35], compared with when it was not, M = 9.50, SD = 3.63, 95% CI = [9.24, 9.77], F(1, 742.14) = 54.21, p < .001. Students from upper-middle-class backgrounds, however, were not affected by visible differences in performance, F(1, 740.33) = 0.28, p > .250, indicating a possible ceiling effect or the fact that being at ease with the task brings enough sense of self-efficacy that downward social comparison offers no further benefit (Bandura, 1997).
Study 2
In Study 2, our goal was to further test the hypothesis that working-class students underperform because their lower familiarity with the culture of academic writing and linguistic norms leads them to think that if they lag behind, it is a sign of lower ability; such a construal is known to undermine higher cognition among sixth graders (see Autin & Croizet, 2012). In Study 2, we manipulated the level of familiarity with academic standards (i.e., cultural capital) as a proxy for social class. We designed a task that involved learning a new writing code. Two levels of familiarity with this arbitrary code were operationalized before students took a coding test without their being aware of it. As in Study 1, in one condition of the test, students had to raise their hands each time they completed a word. There was no such requirement in the other condition, which minimized the visibility of differences in performance. We hypothesized that having students raise their hands to signal completion should be detrimental to the achievement of their peers who were less familiar with the academic standards (i.e., those with the least cultural capital).
Method
Participants
A total of 131 students in the fifth grade (64 girls, 67 boys; mean age = 10.2 years, SD = 0.7) participated in their regular classrooms with consent of their parents and school authorities (five classrooms from five elementary schools). The sample size was determined by the number of schools that agreed to participate in the study. Additional data about students’ academic level (based on teachers’ evaluations) and social class (i.e., working class, intermediate, upper middle class, determined by parental occupation) were also collected. Social-class composition was relatively consistent across classrooms, χ2(8, N = 131) = 9.09, p = .334. Participants were randomly assigned to a 2 (level of familiarity: high vs. low) × 2 (visibility of performance differences: visible vs. not visible) between-participants design.
Task familiarity
First, during a familiarization phase, students performed a coding task and a filler task embedded in the same booklet. The coding task was modeled after the code subtest of the Wechsler Intelligence Scale for Children–4th edition (Wechsler, 2004). It involved learning the association between a series of letters and a corresponding set of symbols, as if the students were learning a new written code. For that purpose, participants had to write down the symbols associated with a given letter as specified in an available code key. The filler task involved easy basic arithmetic (e.g., “8 + 3 = ?”). The tasks were presented in a single booklet to avoid arousing suspicion about the experimental manipulation. In the high-familiarity condition, students spent 75% of the allotted time working on the coding task and 25% of the time on the filler task. In the low-familiarity condition, the percentages were reversed.
Visibility of differences in performance
After the familiarization phase, students took a coding test described as an assessment of memory and comprehension abilities. It involved coding 15 pairs of words without the code answer key. Each pair was presented simultaneously to all students, who had 45 s to write down the corresponding symbols for each pair. In the visibility condition, students were instructed to raise their hands each time they completed a word before the allotted time. When the time was up, the children who also had coded an almost complete answer but missed one letter were asked to raise their hands. Then the hand-raising instruction was given to those who had almost a complete answer minus two letters, and finally to those who were short by three letters. In the no visibility condition, students simply performed the task. Finally, students were fully debriefed and thanked for their participation.
Results
We followed an analytical strategy similar to that specified for Study 1. We ran a linear mixed model with the level of familiarity, the visibility of differences in achievement, and the interaction between these two factors as fixed factors and classrooms as a random factor. The model included by-classroom random intercepts to account for variability across classrooms. The outcome variable was the number of correct answers on the coding task. First, we performed preliminary separate analyses that tested whether students’ social class or academic level (each value was recoded as the deviation from the mean, or x minus the mean of x) interacted with our manipulations. These preanalyses revealed a main effect of students’ academic level on coding performance, F(1, 127.56) = 6.43, p = .012, but no effect of social class F(2, 129.55) = 0.18, p > .25. The latter finding confirmed that the arbitrary academic standard we implemented was not related to social class. In addition, neither academic level nor social class interacted with our experimental design. These factors were therefore dropped from the analyses reported.
The analysis yielded a trivial main effect of familiarity: Students with higher familiarity performed better, M = 94.51, SD = 40.80, 95% CI = [87.46, 101.57], than those with lower familiarity, M = 46.86, SD = 32.09, 95% CI = [41.32, 52.41], F(1, 127.29) = 64.06, p < .001. This main effect was qualified by the expected interaction between familiarity and visibility of differences in achievement, F(1, 127.52) = 4.10, p = .045 (see Fig. 2). In accordance with our hypothesis, the achievement gap between the two levels of familiarity increased when differences in achievement were visible. As predicted, students with low familiarity performed more poorly when their peers’ performance was visible, M = 34.76, SD = 26.34, 95% CI = [30.20, 39.31], than when their peers’ performance was not visible, M = 58.62, SD = 33.13, 95% CI = [52.89, 64.34], F(1, 128.03) = 6.84, p = .010. Students in the high-familiarity condition were not affected by the visibility of differences in achievement, F(1, 126.96) = 0.07, p > .25. The results of Study 2 indicate that students who lack cultural capital (i.e., who are less familiar with an arbitrary academic standard than are their peers) underachieve when differences in performance become visible in the classroom. Our randomized design, which dissociated advantage or disadvantage from social class, precludes any interpretation in terms of stereotype threat, as lower familiarity could not be related to any group reputation of low ability in this study (Croizet & Claire, 1998).
Results for Study 2: number of correctly coded letters as a function of familiarity with the task (low vs. high), separately by visibility of differences in achievement (not visible: hand down vs. visible: hand raising). Scores ranged from 0 to 150. Error bars represent +1 SEM.
Study 3
In Study 3, we aimed to substantiate our claim that the way students make sense of the differences in performance staged in the classroom undermines the achievement of the students who are the least familiar with academic standards. Because the disadvantages in cultural capital are hidden, students who are less familiar with the standards have few options other than to interpret their experience of difficulty relative to others as a sign of intellectual inferiority (Kelley, 1967). We theorized that concerns arising from such interpretations, which disrupt working memory among sixth graders (Autin & Croizet, 2012), might dissipate if students became aware of the disadvantage present in the situation. Therefore, in one condition in Study 3, students were informed that some of their classroom peers were more familiar with the task because they had benefited from better training earlier (aware-of-disadvantage condition). In the other condition, which was similar to one of the conditions in Study 2, the advantage in familiarity remained hidden. All participants were asked to raise their hands if they completed the task within the allotted time. If the underperformance of students who are less familiar with a task compared with their peers is driven by a threatening interpretation of differences in performance (as we believe), changing the meaning of these differences should restore their achievement. Finally, manipulating the meaning of hand raising while maintaining hand raising constant across conditions allowed us to reject the possibility that it was hand raising per se that disrupted the performance of the students in our previous studies who were less familiar with the task.
Method
Participants
A total of 136 students in the fifth grade (60 girls, 76 boys; mean age = 10.7 years, SD = 0.97) participated in their regular classrooms with the authorization of their parents and school authorities (six classrooms of six elementary schools). The sample size was determined by the number of schools that agreed to participate in the study. Students’ academic level (based on teachers’ evaluation) and social class assessed by parental occupation were collected but dropped from analyses because they did not interact with our design. The six classrooms were relatively homogeneous regarding social-class composition, χ2(10, N = 136) = 6.41, p = .780. Students were randomly assigned to a 2 (familiarity with the task: high vs. low) × 2 (awareness of disadvantage: aware vs. unaware) between-participants design.
Task familiarity
The two conditions of familiarity were very similar to those in Study 2, except that all children were explicitly instructed to learn the associations between letters and symbols to minimize variability in students’ spontaneous strategies.
Awareness of advantage in familiarity
After the familiarization phase, students took a coding test similar to that in Study 2, except that they had to decode 12 pairs of symbols. All participants were required to raise a hand if they finished before the allotted time, making differences in achievement visible in all conditions. In the awareness condition, participants were informed that some of them spent 75% of their time (“15 training exercises out of 20”) preparing for the test, whereas other participants spent only 25% of their time on this task (“5 training exercises out of 20”). As in the unawareness condition of Study 2, no information was provided to the participants about familiarization.
Results
Following the analytical strategy of previous studies, we analyzed the number of correct answers with a linear mixed model; we included level of familiarity, awareness of the advantage in having familiarity (unawareness vs. awareness), and the interaction between these two factors as fixed factors, and we included classrooms as a random factor. The outcome variable was the number of correct answers on the coding task. Preliminary analyses assessing whether social class or academic level interacted with our experimental design yielded no main effect of social class, F(2, 128.26) = 1.61, p = .204, and a main effect of academic level, F(1, 131.31) = 9.83, p = .002, indicating again that the arbitrary academic standard that we implemented was unrelated to social class. As in Study 2, neither social class nor student’s academic level interacted with our design. These factors were dropped from further analyses.
The analysis yielded a trivial main effect of familiarity: Students who were more familiar with the task, M = 98.94, SD = 23.32, 95% CI = [94.98, 102.89], performed better than their peers who were less familiar with the task, M = 68.26, SD = 31.35, 95% CI = [62.95, 73.58], F(1, 130.27) = 50.02, p < .001. This main effect was qualified by the expected interaction between familiarity and awareness of the advantage in having familiarity, F(1, 130.00) = 7.03, p = .009 (see Fig. 3). As hypothesized, the students who were less familiar with the task performed better when the advantage in familiarity was unveiled, M = 78.26, SD = 31.05, 95% CI = [72.99, 83.53], than when it remained hidden, M = 58.26, SD = 28.72, 95% CI = [53.39, 63.14], F(1, 130.04) = 10.51, p = .001. No such effect was observed for the students who were more familiar with the task, F(1, 130.05) = 0.26, p > .250. This finding provides evidence that what matters is how visible differences in performance are interpreted. Study 3 showed that when students were left unaware of the advantage some of them enjoyed, the students who were less familiar with the task (compared with peers who were more familiar) underachieved when differences in performance were visible in the classroom. However, when raised hands meant that some students were advantaged, and therefore not necessarily smarter, witnessing differences in performance did not harm the achievement of the students who were less familiar with the task. Finally, because all students raised their hands, the findings for this study allow us to reject the possibility that hand raising per se explains the performance drop reported in Studies 1 and 2.
Results for Study 3: number of correctly decoded symbols as a function of level of familiarity with the task, separately for students who were aware of the disadvantage in levels of familiarity with the task and those who were not. Differences in performance were visible in all conditions (i.e., hands were raised). Scores ranged from 0 to 120. Error bars represent +1 SEM.
Discussion
Across three behavioral studies, we showed that classrooms magnify the social-class achievement gap by enabling social comparisons that undermine the performance of working-class students. Classrooms indeed usually showcase differences in performance in a way that does not acknowledge the advantage given to students whose social class affords them a greater familiarity with the implicit standards valued in education (Bourdieu & Passeron, 1990). Study 1 revealed that simply having students raise their hands to signal completion during a difficult reading test undermined the performance of the working-class students, whose lower familiarity with the academic language is well established (Lahire, 2008; Lareau, 2003). Because social class is confounded with multiple factors and processes, we manipulated students’ familiarity with an arbitrary academic standard as a proxy for social class. In Study 2, the experimentally disadvantaged students underperformed when the higher performance of the experimentally advantaged students was suggested through hand raising, which proves that an arbitrary and hidden advantage can fuel the achievement gap. Study 3 showed that making students aware of this advantage in cultural capital could change the story: Despite the visibly better achievement of their peers, the students who were less familiar with the task did not underachieve when the disadvantage in the levels of familiarity with the task was revealed.
Contributing to a growing body of work, our findings confirm that reproduction in education is not simply the product of prior differences among students: Educational contexts can amplify the social-class achievement gap (Smeding et al., 2013; Stephens, Fryberg, Markus, Johnson, & Covarrubias, 2012). Our research is the first to provide a direct test of the hypothesis, initially formulated by Bourdieu (1974), that educational settings perpetuate social inequality by “giving recognition to a cultural heritage . . . , to a social gift treated as a natural one” (p. 32). Relying on randomized experimental designs, we showed that classroom situations set the stage for disruptive social comparisons that harm the achievement of students who are less familiar than their peers with the arbitrary codes and standards valued in education. Because education is generally conceived as a level playing field (Guinier, 2015), students are left with few options other than to interpret their experience of difficulty relative to others as a sign of intellectual inferiority, a construal detrimental to higher cognition among children (Autin & Croizet, 2012). Our findings indicate that making students aware of the disadvantage conferred to some of them restores the performance of the students who are less familiar with academic standards
We operationalized disadvantage in cultural capital as variations of students’ familiarity with an arbitrary academic standard. Research has documented that, compared with poor parents, upper-middle-class parents engage in a form of parenting that indeed leads to the transmission of vocabulary and communication skills that are valued in school (Lareau, 2003). These language dispositions constitute an important aspect of cultural capital (Lareau & Weininger, 2003). But cultural capital encompasses many other outcomes of class socialization, such as body posture, cognizance of “legitimate” cultural knowledge (e.g., visiting art exhibitions), sense of entitlement (Lareau, 2003), or cultural models of self (Stephens et al., 2012). Future research will have to examine whether unawareness of the advantage in these other aspects of cultural capital can amplify, through social comparison, the social-class achievement gap.
In summary, our research reveals how regular educational contexts can magnify social inequalities. Simply having students raise their hands in the classroom to signal achievement, a practice widely used for classroom management (Ryan, Cooper, & Tauer, 2013; Tanner, 2013), can have a debilitating impact on the achievement of working-class students. We showed that this predicament results from a construal of the academic situation that ignores the arbitrary advantage conferred to upper-middle-class students. Our research suggests that changing the construal that the classroom is a level playing field can offer better learning opportunities for children from disadvantaged backgrounds.
Footnotes
Acknowledgements
The authors would like to thank Dominique Knutsen and Dominique Muller for their help with data analysis.
Action Editor
Brian P. Ackerman served as action editor for this article.
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.
Funding
This research was supported in part by a grant from the Contrat Projet Etat Région (13e CPER programme 11 and 14e CPER – INSECT – Contexte), Université de Poitiers, France.
Open Practices
All data and materials have been made publicly available via the Open Science Framework and can be accessed at https://osf.io/7d5b5/ and https://osf.io/jbfbp/, respectively. The complete Open Practices Disclosure for this article can be found at http://journals.sagepub.com/doi/suppl/10.1177/0956797616676600. This article has received badges for Open Data and Open Materials. More information about the Open Practices badges can be found at https://osf.io/tvyxz/wiki/1.%20View%20the%20Badges/ and 
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Notes
References
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