Yong Jei Lee
Biographic Data
| ID | 3759363 |
|---|---|
| NAME | Yong Jei Lee |
| GIVEN NAMES | Yong Jei |
| FAMILY NAME | Lee |
| SIGNATURE | LEE Y J |
| AFFILIATIONS | University of South Florida, Sarasota, USA |
| ORCID | 0000-0003-4672-2079 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 12 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Not Just for Adults
This study examines whether crime locations are similar or different for juveniles and adults by comparing the distribution of offenses across land uses and their changes over time. Using 6 years of crime data from Colorado Springs, we calculated rank products for each of 35 land uses, stratified by age group and offense type, and summarized rank stability with interquartile ranges. Findings show both similarities and disparities in the rank orde…
What Do We Know About Hot Pot Spots? Does Who Owns Matter
This study examines how place management practices influence crime distribution at pot shops. We assess whether these practices explain the varying crime levels observed across different pot shops. Using data from Colorado Springs, Colorado, we apply a Poisson distribution to compare expected and actual crime distributions among pot shop owners. Multilevel Poisson regression models are then employed to quantify the extent to which crime variation…
Improving Recidivism Forecasting With a Relaxed Naïve Bayes Classifier
Correctional authorities require accurate, unbiased, and interpretable tools to predict individuals’ chances of recidivating if released into the community. However, existing prediction models have serious limitations meeting these requirements. We overcome these limitations by applying an established medical diagnostic approach: a relaxed naïve Bayes classifier. Using logistic regression in the form of a naïve Bayes classifier, we estimate the w…
Redefining Recidivism Prediction
This study explores the effectiveness of machine learning algorithms in predicting recidivism, focusing on the impact of race and geographic location variables. Leveraging a dataset from the prisons in Georgia, we assess six algorithms’ forecasting performance, both with and without these key variables. Our findings indicate that geographic location generally enhances predictive accuracy more consistently than race across models. This research hi…
Crime Prevention in the Classroom
This study examines school-based crime prevention tactics using a place management framework in conjunction with deterrence and labeling theoretical perspectives. We examine the effects of four different aspects of place management on student offending and explore whether and how the effects are distinctive for female versus male students. We analyze survey data from students and principals across three waves of the Rural Substance abuse and Viol…
Land use and sexual harassment
Sexual harassment and gang rape in Egypt have garnered attention from both traditional and digital media. This study employed a volunteer HarassMap to analyse sexual harassment crimes (SHCs) across Egypt from a spatial perspective. The specific aims were to apply the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm to locate clusters of reported SHCs, and to assess their spatial dependence on land use t…
Deviant Identity and Offending
This study examines deviant identity in relation to youth offending by combining items tapping both self-appraisal and reflected appraisal. In particular, using survey data from 3,446 Korean youth across five waves of the Korea Youth Panel Survey (KYPS), findings from group-based trajectory modeling (GBTM) present four distinct offending groups—a high-rate chronic group, stable non-offending group, adolescence-limited group, and declining group. …
Following their Lead
This study examines the effect that individuals’ perceptions of police have on their adoption of crime prevention measures. Unlike past research that conceptualized police perceptions as inversely associated with crime prevention, we introduce a framework that distinguishes between the traditional policing and community policing/procedural justice models. We analyze multilevel data from Canada’s General Social Survey for 13 crime prevention measu…
Why Your Bar Has Crime but Not Mine
Interpretations of two bodies of crime-place research conflict. Land use and crime studies claim particular facilities increase crime. Risky facilities studies show most places of a single type have little or no crime, but a few of that type have a great deal of crime. How can a facility be generally criminogenic and mostly safe? To resolve this conflict, we make use of the fact that a single owner can own multiple facilities and each owner may h…
Comparing measures of the concentration of crime at places
Crime and land use in Pittsburgh
Comparing measures of the concentration of crime at places
Crime and land use in Pittsburgh
Land use and sexual harassment
Sexual harassment and gang rape in Egypt have garnered attention from both traditional and digital media. This study employed a volunteer HarassMap to analyse sexual harassment crimes (SHCs) across Egypt from a spatial perspective. The specific aims were to apply the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm to locate clusters of reported SHCs, and to assess their spatial dependence on land use t…
Crime and land use in Pittsburgh
Comparing measures of the concentration of crime at places
Following their Lead
This study examines the effect that individuals’ perceptions of police have on their adoption of crime prevention measures. Unlike past research that conceptualized police perceptions as inversely associated with crime prevention, we introduce a framework that distinguishes between the traditional policing and community policing/procedural justice models. We analyze multilevel data from Canada’s General Social Survey for 13 crime prevention measu…
Why Your Bar Has Crime but Not Mine
Interpretations of two bodies of crime-place research conflict. Land use and crime studies claim particular facilities increase crime. Risky facilities studies show most places of a single type have little or no crime, but a few of that type have a great deal of crime. How can a facility be generally criminogenic and mostly safe? To resolve this conflict, we make use of the fact that a single owner can own multiple facilities and each owner may h…
Deviant Identity and Offending
This study examines deviant identity in relation to youth offending by combining items tapping both self-appraisal and reflected appraisal. In particular, using survey data from 3,446 Korean youth across five waves of the Korea Youth Panel Survey (KYPS), findings from group-based trajectory modeling (GBTM) present four distinct offending groups—a high-rate chronic group, stable non-offending group, adolescence-limited group, and declining group. …
Crime Prevention in the Classroom
This study examines school-based crime prevention tactics using a place management framework in conjunction with deterrence and labeling theoretical perspectives. We examine the effects of four different aspects of place management on student offending and explore whether and how the effects are distinctive for female versus male students. We analyze survey data from students and principals across three waves of the Rural Substance abuse and Viol…
Land use and sexual harassment
Sexual harassment and gang rape in Egypt have garnered attention from both traditional and digital media. This study employed a volunteer HarassMap to analyse sexual harassment crimes (SHCs) across Egypt from a spatial perspective. The specific aims were to apply the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm to locate clusters of reported SHCs, and to assess their spatial dependence on land use t…
What Do We Know About Hot Pot Spots? Does Who Owns Matter
This study examines how place management practices influence crime distribution at pot shops. We assess whether these practices explain the varying crime levels observed across different pot shops. Using data from Colorado Springs, Colorado, we apply a Poisson distribution to compare expected and actual crime distributions among pot shop owners. Multilevel Poisson regression models are then employed to quantify the extent to which crime variation…
Improving Recidivism Forecasting With a Relaxed Naïve Bayes Classifier
Correctional authorities require accurate, unbiased, and interpretable tools to predict individuals’ chances of recidivating if released into the community. However, existing prediction models have serious limitations meeting these requirements. We overcome these limitations by applying an established medical diagnostic approach: a relaxed naïve Bayes classifier. Using logistic regression in the form of a naïve Bayes classifier, we estimate the w…
Redefining Recidivism Prediction
This study explores the effectiveness of machine learning algorithms in predicting recidivism, focusing on the impact of race and geographic location variables. Leveraging a dataset from the prisons in Georgia, we assess six algorithms’ forecasting performance, both with and without these key variables. Our findings indicate that geographic location generally enhances predictive accuracy more consistently than race across models. This research hi…
Not Just for Adults
This study examines whether crime locations are similar or different for juveniles and adults by comparing the distribution of offenses across land uses and their changes over time. Using 6 years of crime data from Colorado Springs, we calculated rank products for each of 35 land uses, stratified by age group and offense type, and summarized rank stability with interquartile ranges. Findings show both similarities and disparities in the rank orde…
Crime Patterns and Interventions (11 works) · Criminology (7 works) · Computer Science (6 works) · Psychology (6 works) · Crime, Illicit Activities, and Governance (5 works) · Sociology (5 works) · Crime prevention (3 works) · Criminal Justice and Corrections Analysis (3 works) · Geography (3 works) · Machine learning (3 works)