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Hierarchical linear models estimate relationships for each country and for Romanian- and Hungarian-language strata. Mean peer SES and individual SES correlate positively with achievement, while SES variance does not. Mean disciplinary climate predicts achievement in several countries; climate heterogeneity shows limited explanatory power.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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MULTILEVEL STUDY WITH ROMANIAN  \nMINORITY-STRATA EVIDENCE  \nImre PÉNTEK, Magda ILLYÉS, Éva BÁLINT-SVELLA  \nAbstract: This comparative study utilizes the PISA 2022 data from Estonia, Finland, Germany, Hungary, and Romania to consider how student socioeconomic status (SES), peer SES composition, SES inequality, and disciplinary climate –both positive and negative– align with mathematics achievement. For each country and for both Romanian- and Hungarian-language strata, hierarchical linear models were estimated. Mean peer SES and individual SES had consistent positive relationships with achievement, while SES variance did not have a significant relationship with achievement. Mean disciplinary climate was a predictor of achievement in several countries while heterogeneity (or variation) in disciplinary climate did not explain achievement variation. The strata analyses provided evidence of sharper SES-based disparities among students in the Hungarian-medium schools and more pronounced disciplinary-climate effects for children attending Romanian-medium schools. Overall, the results demonstrate greater importance of average peer contexts rather than between-school inequality in SES.  \nKey words: PISA 2022; multilevel modelling; socioeconomic status; peer effects; school climate  \n1. Introduction  \nSocioeconomic stratifications continue to structure educational inequality and are a significant area of empirical study. Researchers have reported a substantial association between students’ socioeconomic status (SES) and their academic performance, including mathematics achievement data on international standardized assessments (PISA; OECD, 2019, 2023, 2024; Sirin, 2005) . Previous work has described SES as a multidimensional factor that can operate through a variety of mechanisms, such as material and learning resources, parental expectations, and other similar cognitively stimulating environments (Reardon, 2011) . Perhaps most importantly, SES is more than just individual traits or characteristics. The socioeconomic makeup of students' schools and friend groups can positively or negatively influence students' outcomes, and these contextual factors can have a uniquely strong and independent relation to learning outcomes.  \n1.1 Peer Effects and Contextual SES: Beyond Mean SES Toward Peer-Exposure Models  \nA considerable body of research has demonstrated that the socioeconomic composition of schools most often quantified by the mean SES of students' peers-is positively correlated to student outcomes (Lüdtke et al., 2009, Marks, 2014, Van Ewijk & Sleegers, 2010). More recently, this body of work has advanced the analysis by highlighting the possibility that socioeconomic heterogeneity among students within schools may also influence students' means of opportunity and learning environments. SES variation may have implications for the distribution of social capital, academic expectations, and peer norms (Borman & Dowling, 2010) . While these notions may occur in a theoretical sense, in regular reporting of PISA results, little attention is paid to measures of SES dispersion among students within each school, either as variance or polarization.  \nThe current study addresses this omission; we analyze two interrelated aspects of contextual SES. The first is peer SES exposure, which we operationalize as the mean ESCS at the school level, which serves as a gauge of the SES context of students. The second is peer SES heterogeneity, which we measure as variance in ESCS within schools, which builds upon the student diversity dimension of SES. Both of these distinctions follow network-based models of peer effects, which postulates that achievement-related behaviors and norms spread through the networks created by exposure, imitation, and reinforcement (Bramoullé et al, 2009; Sacerdote, 2011) .  \nIn such theories, mean SES is the initial exposure to the ","cbCait3I1i91WEE9","https://ap.wps.com/l/cbCait3I1i91WEE9","pdf",395360,14,"English","# Introduction\n## Peer Effects and Contextual SES: Beyond Mean SES Toward Peer-Exposure Models\n## School Climate and Structural Conditions in PISA 2022","[{\"question\":\"Which factors are analyzed as predictors of mathematics achievement in the study?\",\"answer\":\"The study analyzes students’ socioeconomic status (SES), peer SES composition, SES inequality, and disciplinary climate (both positive and negative) as predictors of mathematics achievement using PISA 2022 data.\"},{\"question\":\"What is the relationship between mean SES/peer SES and mathematics achievement?\",\"answer\":\"Mean peer SES and individual SES show consistent positive relationships with mathematics achievement across the analyzed contexts.\"},{\"question\":\"Do SES inequality and disciplinary-climate heterogeneity explain achievement variation?\",\"answer\":\"SES variance does not significantly relate to achievement, and while mean disciplinary climate can predict achievement, within-school disciplinary-climate heterogeneity does not meaningfully explain achievement variation.\"}]","SOCIOECONOMIC STATUS, DISCIPLINARY CLIMATE, AND PISA 2022 MATHEMATICS ACHIEVEMENT - A FIVE COUNTRY MULTILEVEL STUDY WITH ROMANIAN MINORITY-STRATA EVIDENCE | PDF",1792065073,35]