Children in Conflict with Law: Reforming Juvenile Justice Legislation

Abstract

Juvenile justice systems operate at the difficult intersection of child protection, public safety, legal accountability, and the developmental capacity of children to understand the consequences of unlawful conduct. Recent changes in social behaviour, digital exposure, cyberenabled offending, and the increasing complexity of cases involving children in conflict with law have created challenges that conventional legal assessment mechanisms may not adequately address.  This study identifies a research gap in the absence of transparent, child-rights-sensitive analytical frameworks capable of evaluating juvenile justice reform without converting predictive technologies into automated mechanisms for determining guilt, punishment, or transfer to adult courts. To address this gap, the manuscript proposes a ChildCentred Juvenile Justice Reform Analytics Framework (CJRAF) that combines interpretable machine learning, natural language processing, legal-policy indicators, and structured child-welfare variables for research and policy evaluation. The framework is designed to analyse patterns relating to case duration, rehabilitation needs, procedural safeguards, institutional intervention, educational vulnerability, family support, and justice outcomes while explicitly excluding protected or highly sensitive characteristics from automated decision recommendations.