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博碩士論文 etd-0813112-124256 詳細資訊
Title page for etd-0813112-124256
論文名稱
Title
女性毒品受刑人再犯預測模型之研究
A Study of Recidivism Prediction Models for Women Drug Prisoners
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
70
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2012-07-24
繳交日期
Date of Submission
2012-08-13
關鍵字
Keywords
再犯、Logistic迴歸分析、再犯間隔時間、毒品受刑人、存活分析
recidivism, Logistic Regression Analysis, drug prisoners, Survival Analysis, recommitting time interval
統計
Statistics
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中文摘要
本文以矯正機關現行「毒品再犯危險性評估表」中所列10個因子為基礎,結合文獻中所發現對毒品再犯有影響的18個因子,利用再犯預測模型,對女性毒品受刑人出獄後的再犯情況予以預測,希能提升機關現有再犯預測效率。
本研究以97至100年間高雄女子監獄出監毒品受刑人1,029人為樣本,追蹤至100年底再犯罪情形,考慮兩組危險因子,第一組為僅利用10個因子的「評估表因子」,第二組為包含全部28個因子的「整體因子」,分別運用Logistic迴歸分析及存活分析,除篩選影響再犯及再犯間隔時間危險因子外,更進一步預測其出監後可能再犯機率及再犯間隔時間。
實證結果發現,以評估表因子運用Logistic迴歸進行預測,再犯篩檢率為58.4%;若以整體因子預測,再犯篩檢率提升至73.3%。以存活分析四種常用機率分配預測再犯間隔時間,中位數預估結果遠優於平均數,依評估表因子預測,四種機率分配預測再犯時點與實際再犯時點誤差日數小於60天及小於180天個數,占實際再犯個案比例最高為2.5%、9.6%;若依整體因子預測,誤差日數小於60天及小於180天個數,占實際再犯個案比例提升至10.2%、27.3%。
Abstract
The paper constructs recidivism prediction models for women drug prisoners, using the 10 factors evaluated in "drug recidivism risk assessment form" by correctional institutions and the 18 factors studied in the literature. With the new recidivism prediction model, I hope to help improving the prediction accuracy of women drug prisoners’ recidivism.
The sample in the paper includes 1,029 drug prisoners released from Kaohsiung Women's Prison between 2008 and 2011. All criminal records are traced until the end of 2011. Two sets of potential risk factors of recidivism are considered in the paper. The first set only contains the factors in the evaluation form, and the second set includes all relevant factors. Using Logistic Regression Analysis and Survival Analysis, the effects of potential risk factors on recidivism are examined. I also predict the probability and the time interval of recidivism.
Using the Logistic regression model with the risk factors only in the evaluation form, 58.4% of recidivism can be correctly predicted. While extending the set of potential risk factors, the screening rate of recidivism can be enhanced to 73.3%. The median forecast results are far superior to the average forecast in Survival Analysis. With the potential risk factors in the evaluation form, the difference of predicted recidivism date and the actual date is less than 60 days and less than 180 days in 2.5% and 9.6% of sample respectively. With all relevant risk factors, prediction, the share of sample whose difference of predicted recidivism date and the actual date is less than 60 days and less than 180 days are significantly improved to 10.2% and 27.3% respectively.
目次 Table of Contents
論文審定書 i
誌 謝 ii
摘 要 iii
Abstract iv
目錄 vi
圖目錄 vii
表目錄 viii
第一章 緒論 1
第一節 研究動機與目的 1
第二節 研究架構 3
第二章 收容人再犯現況及文獻探討 5
第一節 台灣地區各類收容人再犯現況 5
第二節 文獻探討 7
第三章 研究方法與樣本特性分析 15
第一節 研究方法 15
第二節 樣本特性分析 23
第四章 實證結果 35
第一節 以Logistic迴歸分析探討再犯機率 35
第二節 以存活分析探討再犯間隔時間 42
第三節 模型效率評估 52
第五章 結論與建議 54
第一節 結論 54
第二節 建議 56
參考文獻 57
參考文獻 References
中文部分
1.王儷婷 (2005). 我國女性毒品再犯之實證研究. 犯罪防治研究所. 桃園縣, 中央警察大學. 碩士: 216.
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3.呂美櫻 (2007). 臺灣地區毒品再、累犯間隔時間與行為模式之研究. 統計學系. 新北市, 國立臺北大學. 碩士: 103.
4.李明謹 (2009). 成年犯罪人再犯影響因素之追蹤研究. 犯罪防治研究所. 桃園縣, 中央警察大學. 碩士: 211.
5.李思賢, 吳憲璋, 黃昭正, 王志傑與石倩瑜 (2010). "毒品罪再犯率與保護因子研究: 以基隆地區為例." 犯罪學期刊 13(1): 81-106.
6.林宗穎 (2002). 一般化犯罪理論對受保護管束之毒品犯罪者再犯之解釋. 青少年兒童福利研究所. 台中縣, 靜宜大學. 碩士: 107.
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10.張聖照 (2007). 假釋受刑人再犯預測研究. 犯罪防治研究所. 桃園縣, 中央警察大學. 博士: 278.
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英文部分
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3.Blumstein, A. and J. Cohen (1979). "Estimation of Individual Crime Rates from Arrest Records." The Journal of Criminal Law and Criminology 70(4): 561-585.
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5.Cox, D. R. (1972). "Regression models and life-tables." Journal of the Royal Statistical Society. Series B (Methodological): 187-220.
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7.Cox, D. R. and E. J. Snell (1968). "A general definition of residuals." Journal of the Royal Statistical Society. Series B (Methodological): 248-275.
8.DeJong, C. (1997). "Survival Analysis and Specific Deterrence: Integrating Theoretical and Empirical Models of Recidivism." Criminology 35(4): 561-576.
9.Gendreau, P., T. Little, and C. Goggin (1996). "A Meta‐analysis of The Predictors of Adult Offender Recidivism: What Works." Criminology 34(4): 575-608.
10.Hepburn, J. R. and C. A. Albonetti (1994). "Recidivism Among Drug Offenders: A Survival Analysis of the Effects of Offender Characteristics, Type of Offense, and Two Types of Intervention." Journal of Quantitative Criminology 10(2): 159-179.
11.Huebner, B. M. (2006). "Drug Abuse, Treatment, and Probationer Recidivism." Chicago: Illinois Criminal Justice Information Authority.
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15.Kruttschnitt, C., C. Uggen, and K. Shelton (2000). "Predictors of Desistance Among Sex Offenders: The Interaction of Formal and Informal Social Controls." Justice Quarterly 17(1): 61-87.
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19.Schwaner, S. L. (1998). "Patterns of Violent Specialization: Predictors of Recidivism for a Cohort of Parolees." American Journal of Criminal Justice 23(1): 1-17.
20.Silver, E., W. R. Smith, and S. Banks (2000). "Constructing Actuarial Devices for Predicting Recidivism." Criminal Justice and Behavior 27(6): 733-764.
21.Smith, L. G. and R. L. Akers (1993). "A Comparison of Recidivism of Florida's Community Control and Prison: A Five-year Survival Analysis." Journal of Research in Crime and Delinquency 30(3): 267-292.
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23.Stewart, K., P. J. Gruenewald, and R. N. Parker (1992). "Assessing Legal Change: Recidivism and Administrative per se Laws." Journal of Quantitative Criminology 8(4): 375-394.
24.Toombs, N. J., B. B. Benda, and R. Flynncorwyn (1998). "Recidivism Among Arkansas Boot Camp Graduates After 12 Months." Journal of Offender Rehabilitation 26(1-2): 141-160.
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26.Visher, C. A. and R. L. Linster (1990). "A Survival Model of Pretrial Failure." Journal of Quantitative Criminology 6(2): 153-184.
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