Advancing Crime and Criminal Justice Research with Innovative Methods

Session Submission Type: Complete Thematic Panel

Abstract/Description

This panel highlights emerging voices in criminology, showcasing innovative methods to advance crime and criminal justice research. The first study employs a sparse machine learning approach to analyze bullying influence networks in Chinese schools, distinguishing between compliance-driven and defiance-driven peer interactions. The second study explores AI-simulated sociolegal survey experiments, assessing the potential and limitations of large language models in predicting human decision-making. The third study examines the reintegration of recovering drug users in China, applying life course theory to understand how “family face” restoration facilitates reconciliation and social acceptance. The final study leverages Chinese judicial documents and multilevel Tobit regression models to investigate how structural gender equality influences sentencing outcomes for male perpetrators of intimate partner violence. Collectively, these studies demonstrate the power of computational, experimental, and qualitative methodologies in deepening our understanding of crime, justice, and social dynamics in diverse cultural and legal contexts.

Sub Unit

• Area XI. Methodology / 80. Advances in Quantitative Methods

Individual Presentations

• Complier vs. Defier: A Sparse Machine Learning Approach to Understanding Bullying Influence Networks - Shiming Hao, College of Law, Yunnan University, China; Zhong Wang, College of Law, Hunan University, China; Yan Zhang, Sam Houston State University

• AI-Piloted Sociolegal Survey Experiments - Sishi Wu, California State University, San Bernardino

• Using Chinese Judgment Documents to Explore Structural Gender Equality and Sentencing Outcomes - Yuxuan Gu, The Chinese University of Hong Kong

• The Impact of Structural Conflict on Violent Crime and Countermeasures‌ - Jing Zhang, Beijing University of Technology

Chair

• Hua Zhong, The Chinese University of Hong Kong

Organized by a Division or external group?

Sponsored by:
ACCCJ (Association of Chinese Criminology and Criminal Justice),
ACS (Asian Criminological Society), and
ASC DIC (Division of International Criminology)