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Record W4386571517 · doi:10.1111/fcre.12759

Judicial decision‐making in family court involving children with autism spectrum disorder

2023· article· en· W4386571517 on OpenAlexaffabout
Emilie Lahaie, Karine Poitras, Rachel Birnbaum

Bibliographic record

VenueFamily Court Review · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsThe King's UniversityEducation and Early Childhood DevelopmentWestern UniversityUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsFamily courtAutism spectrum disorderPsychologyAutismChild custodyPopulationPrimary careDevelopmental psychologyPsychiatryMedicineFamily medicineLawCriminologyPolitical science

Abstract

fetched live from OpenAlex

Abstract The prevalence of autism spectrum disorder (ASD) in children and adolescents has increased over the past decade. Consequently, the courts and experts are more likely to be exposed to these children whose needs are highly heterogeneous. The present study aims to document judicial decision‐making about children with autism spectrum as well as the parenting recommendations made by experts involved in these cases. There were 104 court decisions reviewed in Quebec over the past ten years. The results show that 85.6% of the decisions included a child custody assessment and that judges are more likely to order primary care to mother (56%). However, shared parenting (27%) and primary care to the father (17%) were also ordered in disputes involving an autistic child. Bivariate analyses revealed that challenges with parental monitoring and supervision were associated with court‐ordered parenting arrangements. The present study revealed that a child custody assessment as well as father custody are more often observed than in the general population. This study highlights the need for further research to shed light on the best interests of children with ASD following the separation of their parents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.369
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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