Using machine learning-based systems to help predict disengagement from the legal proceedings by women victims of intimate partner violence in Spain.

ABSTRACT: Intimate partner violence against women (IPVW) is a pressing social issue which poses a challenge in terms of prevention, legal action, and reporting the abuse once it has occurred. However, a significant number of female victims who file a complaint against their abuser and initiate legal proceedings, subsequently, withdraw charges for different reasons. Research in this field has been focusing on identifying the factors underlying women victims' decision to disengage from the legal process to enable intervention before this occurs. Previous studies have applied statistical models to use input variables and make a prediction of withdrawal. However, none have used machine learning models to predict disengagement from legal proceedings in IPVW cases. This could represent a more accurate way

SUBMITTER: Escobar-Linero E 

PROVIDER: S-EPMC10246857 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature