MétaCan
Menu
Back to cohort
Record W4408839568 · doi:10.1177/10443894251317628

The Mediating Role of Leaving School and Social Support Networks in the Relationship Between the Placement Experiences and Contact With the Criminal Justice System of Youth Aging Out of Care

2025· article· en· W4408839568 on OpenAlexafffund
Christophe Gauthier-Davies, Thomas J. Esposito, Martín Goyette

Bibliographic record

VenueFamilies in Society The Journal of Contemporary Social Services · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsNational Circus SchoolUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et CultureCanada Foundation for Innovation
KeywordsCriminal justiceCriminologyPsychologySocial contactDevelopmental psychologySocial psychologySociology

Abstract

fetched live from OpenAlex

Studies suggest that some characteristics of placement experiences (instability and group placement) as well as leaving school and lack of supportive networks are associated with criminal justice system involvement. Other studies suggest that these placement experiences can negatively affect the educational outcomes and social support networks of youth aging out of care. It is therefore likely that a lack of social support networks and leaving school mediate the relationship between placement experiences and adult justice involvement. This study aims to examine whether support networks and leaving school during the transition out of placement mediate the relationship between placement experiences and justice system involvement. The results show that the relationship between placement experiences and post-placement criminal justice system involvement is mediated by leaving school but not by social support networks.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.023
GPT teacher head0.292
Teacher spread0.268 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueFamilies in Society The Journal of Contemporary Social ServicesSame topicChild Welfare and AdoptionFrench-language works237,207