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Record W4393037863 · doi:10.1177/03085759231216068

Supporting older youth in care: The role of caregivers

2024· article· en· W4393037863 on OpenAlexaffabout
Greggory Cullen

Bibliographic record

VenueAdoption & Fostering · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsMount Royal University
Fundersnot available
KeywordsPsychologyNursingGerontologyDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

Adolescents living in care are vulnerable to a range of negative outcomes. Although the mental health and substance use problems of foster youth are widely documented, significantly less research examines the influence of caregivers on these two dimensions of health and wellbeing. Given the importance of caregivers to the development of adolescents in child welfare, the present study investigates the relationship between caregiver characteristics, caregiver attachment and placement type on mental health and substance use. The sample consists of 1,093 young people taken from the 2016 Ontario Looking After Children project who are between 16 and 17 years of age. Findings suggest that caregiver attachment, caregiver gender and the caregiver’s school expectations are all significantly associated with mental health and substance use among this population. Results will inform child welfare professionals about a number of risk-predictive factors of mental health and substance use problems among a sample of young people preparing to transition to adulthood. These findings will help service providers design policies and intervention strategies to improve the future outcomes of youth involved in child welfare.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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 designQualitative
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
Published2024
Admission routes2
Has abstractyes

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