A model for predicting court decisions on child custody
Resumen: 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.
Idioma: Inglés
DOI: 10.1371/journal.pone.0258993
Año: 2021
Publicado en: PLoS ONE 16, 10 (2021), e0258993[21 pp]
ISSN: 1932-6203

Factor impacto JCR: 3.752 (2021)
Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 29 / 74 = 0.392 (2021) - Q2 - T2
Factor impacto SCIMAGO: 0.852 - Multidisciplinary (Q1)

Tipo y forma: Article (Published version)
Área (Departamento): Área Economía Finan. y Contab. (Dpto. Contabilidad y Finanzas)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

Exportado de SIDERAL (2023-05-18-15:41:44)

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 Record created 2022-09-08, last modified 2023-05-19

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