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Differences in Roma and non-Roma students’ ratings of their peers’ popularity: an inquiry into the oppositional culture in Hungarian schools with the use of a survey experiment


Oppositional culture theory posits that students who belong to oppressed ethnic minority groups define their ethnic identity in opposition to the majority of students. Minority students might restrict their achievements and effort in schools to gain popularity since they believe that their peers regard investing in pro-school attributes as a betrayal of their own culture and adaptation to the majority culture. Thus, peer pressure might explain why minority students’ performance lags behind that of their majority peers. We tested this theory among 584 seventh- and eighth grade (13–14-year-old) students in 38 ethnically diverse Hungarian classrooms. We conducted a vignette experiment in which students rated the “coolness” of fictive vignette persons whose attributes (GPA, effort, and school behavior) were randomly combined. Each student rated 12 randomly chosen vignettes. We found that Roma students rated their peers as less popular if the peers had a good GPA in classrooms with high ethnic diversity. We did not find a significant Roma/non-Roma gap in pro-school attributes in other domains such as effort and school behavior, or in non-pro-school attributes in any domain. Accordingly, we conclude that differences in ethnic identity explain little of the Roma/non-Roma achievement gap in Hungarian schools. Therefore, oppositional culture between Roma and non-Roma students appears to occur in context-specific and sporadic ways in Hungary.

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  1. However, some prior work has investigated different ethnic minorities (Hajdu et al. 2019; Kisfalusi 2018; van Tubergen and van Gaans 2016; Çelik 2015).

  2. OCT uses the term ‘Black’ when it refers to the African American population, the latter which is a politically more correct expression than the former. Since OCT uses metaphorical language (‘acting White’) which becomes imbued with meaning when opposed to the term ‘Black,’ we sporadically use the term Black without wishing to ignore the need to use more politically correct language.

  3. Furthermore, OCT is “constructed” from the perspective of minority students. The theory makes predictions only about how minority students perceive their minority peers. However, it is agnostic about how minority students perceive their majority peers (if the latter, for example, are doing well at school). More specifically, OCT says little about whether minority students oppose doing well in school in general (regardless of peers’ ethnicity) or if they employ double standards (i.e. they oppose certain attitudes if their own kin also hold them, but accept them if majority peers do).


  5. One school no longer exists, one school was flooded and the students distributed between other schools, and one school did not want to participate.

  6. Out of the 60 classrooms in the analytical sample, in 46 classrooms the survey response rate was more than 80%. The response rate was below 50% (38.5%) in one classroom.

  7. Omitting ethnicity as one of the main characteristics of the vignette person was done for practical and theoretical reasons. The practical reason is that some classroom teachers would have refused to participate in the survey if we had included ethnicity as one of the vignette person’s main characteristics. These classroom teachers argued that mentioning ethnicity in the questionnaire would enhance preexisting prejudice within the classroom. The theoretical reason for the omission is that ethnic identity is a social construct (Hogg and Reid 2006; Telles and Paschel 2014) with fluid boundaries (Boda 2018, 2019). Therefore, including ethnicity as one of the vignette person’s main characteristics would have biased our measurement. In this case, individual stereotypes about Roma would have been activated. Furthermore, obtaining information about both students’ and vignette persons’ ethnicity would have resulted in the identification of a combination of same/mixed ethnic relationships. For modeling these combinations, OCT does not provide guidance. OCT is specific about the relationship between minority students and their (minority) peers and leaves aside the issue of potential double standards (the relationship between minority students and majority peers).

  8. For example, there were good students who did not do homework, and diligent students with weak academic performance. The full set of the deployed 48 vignettes is available in the Online Appendix.

  9. A possible contra-argument is that abstract scenarios can yield more generalizable results, since they lead to information equivalence concerning the background scenario (Dafoe et al. 2018).

  10. Accordingly, we chose random-effect models instead of fixed-effect models. This choice was supported by the corresponding Hausman test which showed no difference between fixed- and random-effects models. This is an indication that the more effective random-effects model should be chosen.


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This research is funded by a grant from the Hungarian National Research, Development and Innovation Office (NKFIH), Grant Number: FK 125358. The support from the János Bolyai Research Scholarship of the Hungarian Academy of Sciences and from the New National Excellence Program (ÚNKP) of the Ministry of Human Capacities are acknowledged (Grant Number: ÚNKP-19-4-BCE-07).

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Correspondence to Tamás Keller.

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Keller, T. Differences in Roma and non-Roma students’ ratings of their peers’ popularity: an inquiry into the oppositional culture in Hungarian schools with the use of a survey experiment. Qual Quant 54, 1233–1255 (2020).

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