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Schools as Precipitants of Crime: The Routine Activities and the Sociology of Place

Schools as Precipitants of Crime: The Routine Activities and the Sociology of Place
学校作为犯罪的诱因:日常活动和地方社会学
批准号:
0071124
负责人:
James Lynch
金额:
$0.41万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-06-01 至 2001-05-31

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中文摘要
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英文摘要
SES 0071124PI: James P Lynch, Caterina P Gouvis This project uses extensive Census data to study variations in crimes against school children throughout the day. The area of study will be a large county (about 750,000 residents) in Maryland. Crime victimization rates come from all incidents of person crimes reported to the police from 1992 through June 1999. The overall goal of the research is to assess hypotheses derived from an established perspective in criminology, called "routine activity." According to this view, crime rates are importantly influenced by opportunities, surveillance, and the mix of actors in a setting. To date, studies to assess this perspective have been hampered by inadequate data bases; the number of people who are potential crime victims has not been known, so it is difficult to assess crime rates. Using children enrolled in schools and focusing on crimes that take place at the school should solve that problem, leading to cleaner tests of the hypotheses than have previously been conducted. The main benefit of this research will be to produce a good test of this perspective in the sociology of deviance. This view is considerably more structural than individualistic perspectives, which focus, for instance, on characteristics of perpetrators rather than on properties of social situations.
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Workshop on Logic and Systems Biology
  • 批准号:
    1430556
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.0万
  • 财政年份:
    2014
  • 负责人:
    James Lynch
  • 依托单位:
Workshop on Logic and Systems Biology
  • 批准号:
    1231446
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.8万
  • 财政年份:
    2012
  • 负责人:
    James Lynch
  • 依托单位:
Collaborative Research for Developing ATD: Bayesian Methods in Syndromic Surveillance: CAR Models and Computational Implementation
Dynamic Models and Decision Making for Complex Reliability Systems
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