A Cross-National Study of School Violence

This study examines the predictors of school violence cross-nationally, testing the applicability of criminological theories of adult violence to violence in the school setting. Using hierarchical linear modeling (HLM), a method of multi-level linear analysis, of the 2007 Trends in International Ma...

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Main Author: Agnich, Laura Elizabeth
Other Authors: Sociology
Format: Others
Published: Virginia Tech 2014
Subjects:
Online Access:http://hdl.handle.net/10919/28160
http://scholar.lib.vt.edu/theses/available/etd-06292011-114002/
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spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-281602021-10-07T05:27:44Z A Cross-National Study of School Violence Agnich, Laura Elizabeth Sociology Ryan, John W. Fuller, Theodore D. Zhu, Haiyan Hawdon, James E. Miyazaki, Yasuo School Violence Student Victimization Student Achievement This study examines the predictors of school violence cross-nationally, testing the applicability of criminological theories of adult violence to violence in the school setting. Using hierarchical linear modeling (HLM), a method of multi-level linear analysis, of the 2007 Trends in International Math and Science Studies (TIMSS) data augmented with data from UN Human Development Reports, UN Demographic Yearbook, CIA World Factbook and the World Health Organization Mortality Database, I determine the predictors of school violence at the school and national levels to determine what variables account for cross-national variation in the level of school violence. Hierarchical linear modeling (HLM) takes into account the structure of nested data, and this study examines schools nested within nations. The relationships between school and national level inequalities, social disorganization, institutional anomie, social support, resource deprivation theories and school violence are tested. Violence is operationally defined as a continuum of aggression ranging from non-physical to physical (see Yu 2003), incorporating low-level as well as more serious forms of interpersonal violence. I find that measures of social disorganization, institutional anomie and resource deprivation at both the school and national levels predict higher levels of violence within schools. Surprisingly, homogeneity rather than heterogeneity is a significant predictor of physical bullying. In addition, math achievement and achievement score variation significantly predict the level of school violence cross-nationally. At the national level, placing too much emphasis on students' achievement on standardized tests may inadvertently create a culture conducive to school violence. Emphasizing a diverse range of ways to measure students' achievement other than standardized testing may reduce the likelihood that students experience strain and engage in violent behavior at school. This research is the first to use multi-level linear analysis to discern the school and national level predictors of school violence. Ph. D. 2014-03-14T20:13:36Z 2014-03-14T20:13:36Z 2011-05-11 2011-06-29 2011-07-21 2011-07-21 Dissertation etd-06292011-114002 http://hdl.handle.net/10919/28160 http://scholar.lib.vt.edu/theses/available/etd-06292011-114002/ Agnich_LE_D_2011.pdf In Copyright http://rightsstatements.org/vocab/InC/1.0/ application/pdf Virginia Tech
collection NDLTD
format Others
sources NDLTD
topic School Violence
Student Victimization
Student Achievement
spellingShingle School Violence
Student Victimization
Student Achievement
Agnich, Laura Elizabeth
A Cross-National Study of School Violence
description This study examines the predictors of school violence cross-nationally, testing the applicability of criminological theories of adult violence to violence in the school setting. Using hierarchical linear modeling (HLM), a method of multi-level linear analysis, of the 2007 Trends in International Math and Science Studies (TIMSS) data augmented with data from UN Human Development Reports, UN Demographic Yearbook, CIA World Factbook and the World Health Organization Mortality Database, I determine the predictors of school violence at the school and national levels to determine what variables account for cross-national variation in the level of school violence. Hierarchical linear modeling (HLM) takes into account the structure of nested data, and this study examines schools nested within nations. The relationships between school and national level inequalities, social disorganization, institutional anomie, social support, resource deprivation theories and school violence are tested. Violence is operationally defined as a continuum of aggression ranging from non-physical to physical (see Yu 2003), incorporating low-level as well as more serious forms of interpersonal violence. I find that measures of social disorganization, institutional anomie and resource deprivation at both the school and national levels predict higher levels of violence within schools. Surprisingly, homogeneity rather than heterogeneity is a significant predictor of physical bullying. In addition, math achievement and achievement score variation significantly predict the level of school violence cross-nationally. At the national level, placing too much emphasis on students' achievement on standardized tests may inadvertently create a culture conducive to school violence. Emphasizing a diverse range of ways to measure students' achievement other than standardized testing may reduce the likelihood that students experience strain and engage in violent behavior at school. This research is the first to use multi-level linear analysis to discern the school and national level predictors of school violence. === Ph. D.
author2 Sociology
author_facet Sociology
Agnich, Laura Elizabeth
author Agnich, Laura Elizabeth
author_sort Agnich, Laura Elizabeth
title A Cross-National Study of School Violence
title_short A Cross-National Study of School Violence
title_full A Cross-National Study of School Violence
title_fullStr A Cross-National Study of School Violence
title_full_unstemmed A Cross-National Study of School Violence
title_sort cross-national study of school violence
publisher Virginia Tech
publishDate 2014
url http://hdl.handle.net/10919/28160
http://scholar.lib.vt.edu/theses/available/etd-06292011-114002/
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