A model for predicting court decisions on child custody

Awarding joint or sole custody is of crucial importance for the lives of both the child and the parents. This paper first models the factors explaining a court’s decision to grant child custody and later tests the predictive capacity of the proposed model. We conducted an empirical study using data...

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Main Authors: José Félix Muñoz Soro, Carlos Serrano-Cinca
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530287/?tool=EBI
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author José Félix Muñoz Soro
Carlos Serrano-Cinca
author_facet José Félix Muñoz Soro
Carlos Serrano-Cinca
author_sort José Félix Muñoz Soro
collection DOAJ
description Awarding joint or sole custody is of crucial importance for the lives of both the child and the parents. This paper first models the factors explaining a court’s decision to grant child custody and later tests the predictive capacity of the proposed model. We conducted an empirical study using data from 1,884 court rulings, identifying and labeling factual elements, legal principles, and other relevant information. We developed a neural network model that includes eight factual findings, such as the relationship between the parents and their economic resources, the child’s opinion, and the psychological report on the type of custody. We performed a temporal validation using cases later in time than those in the training sample for prediction. Our system predicted the court’s decisions with an accuracy exceeding 85%. We obtained easy-to-apply decision rules with the decision tree technique. The paper contributes by identifying the factors that best predict joint custody, which is useful for parents, lawyers, and prosecutors. Parents would do well to know these findings before venturing into a courtroom.
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spelling doaj.art-682c3397f4b34c0ab26fd6c3593f22492022-12-21T21:25:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-011610A model for predicting court decisions on child custodyJosé Félix Muñoz SoroCarlos Serrano-CincaAwarding joint or sole custody is of crucial importance for the lives of both the child and the parents. This paper first models the factors explaining a court’s decision to grant child custody and later tests the predictive capacity of the proposed model. We conducted an empirical study using data from 1,884 court rulings, identifying and labeling factual elements, legal principles, and other relevant information. We developed a neural network model that includes eight factual findings, such as the relationship between the parents and their economic resources, the child’s opinion, and the psychological report on the type of custody. We performed a temporal validation using cases later in time than those in the training sample for prediction. Our system predicted the court’s decisions with an accuracy exceeding 85%. We obtained easy-to-apply decision rules with the decision tree technique. The paper contributes by identifying the factors that best predict joint custody, which is useful for parents, lawyers, and prosecutors. Parents would do well to know these findings before venturing into a courtroom.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530287/?tool=EBI
spellingShingle José Félix Muñoz Soro
Carlos Serrano-Cinca
A model for predicting court decisions on child custody
PLoS ONE
title A model for predicting court decisions on child custody
title_full A model for predicting court decisions on child custody
title_fullStr A model for predicting court decisions on child custody
title_full_unstemmed A model for predicting court decisions on child custody
title_short A model for predicting court decisions on child custody
title_sort model for predicting court decisions on child custody
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530287/?tool=EBI
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