Unveiling the shadows: School bullying and students' ability erosions in Chinese compulsory schools

IF 5.2 1区 经济学 Q1 ECONOMICS 中国经济评论 Pub Date : 2024-10-18 DOI:10.1016/j.chieco.2024.102292
Yunsen Li , Dan He , Yilin Wang , Guochang Zhao , Jing Yang
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Abstract

Drawing upon data from the National Children's Study of China, this research investigates the school bullying victimization and its associations with the ability erosions among students in Chinese schools. Three key findings emerge. First, results suggest that the primary factors affecting bullying victimization mainly include authoritarian parenting, limited positive social interactions on campus, adverse experiences, and exposure to teacher and peer smoking. Second, estimates indicate that bullying victimization is significantly associated with ability erosions, particularly among students from relatively advantaged backgrounds. The further Oster's test, falsification test, and reverse causality check confirm the validity of the associations and suggest some causal effect of victimization on the student outcomes. Lastly, the Oaxaca-Blinder decomposition shows that lower human capital investments derived from social interactions are the most significant contributors to the ability erosion linked to bullying victimization. These findings highlight the critical importance of social interactions both at home and in schools.
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揭开阴影中国义务教育阶段校园欺凌与学生能力消退
本研究利用中国全国儿童研究的数据,调查了中国学校中学生遭受校园欺凌的情况及其与能力削弱之间的关联。研究得出了三个重要发现。首先,研究结果表明,影响校园欺凌受害情况的主要因素包括家长专制、校园中积极的社会交往有限、不良经历以及教师和同伴吸烟。其次,估计结果表明,欺凌受害与能力侵蚀有显著关联,尤其是在背景相对优越的学生中。进一步的奥斯特检验、证伪检验和反向因果关系检验证实了这些关联的有效性,并表明受害对学生的结果产生了一定的因果效应。最后,奥克萨卡-布林德分解法显示,社会交往所带来的较低人力资本投资是造成与欺凌受害相关的能力削弱的最主要原因。这些发现凸显了家庭和学校中社会交往的重要性。
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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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