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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Public Library of Science (PLoS)
2021
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oai:doaj.org-article:682c3397f4b34c0ab26fd6c3593f22492021-11-04T06:07:19ZA model for predicting court decisions on child custody1932-6203https://doaj.org/article/682c3397f4b34c0ab26fd6c3593f22492021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530287/?tool=EBIhttps://doaj.org/toc/1932-6203Awarding 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.José Félix Muñoz SoroCarlos Serrano-CincaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10 (2021) |
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Medicine R Science Q José Félix Muñoz Soro Carlos Serrano-Cinca A model for predicting court decisions on child custody |
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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. |
format |
article |
author |
José Félix Muñoz Soro Carlos Serrano-Cinca |
author_facet |
José Félix Muñoz Soro Carlos Serrano-Cinca |
author_sort |
José Félix Muñoz Soro |
title |
A model for predicting court decisions on child custody |
title_short |
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_sort |
model for predicting court decisions on child custody |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doaj.org/article/682c3397f4b34c0ab26fd6c3593f2249 |
work_keys_str_mv |
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