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Record W2589442618 · doi:10.1177/1077559517690829

Examining Child Welfare Decisions and Services for Asian-Canadian Versus White-Canadian Children and Families in the Child Welfare System

2017· article· en· W2589442618 on OpenAlexaffabout
Barbara Lee, Esme Fuller‐Thomson, Barbara Fallon, Tara Black, Nico Trocmé

Bibliographic record

VenueChild Maltreatment · 2017
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsChild protectionNeglectChild abuseWelfareWhite (mutation)Poison controlChild neglectMedicineSuicide preventionClosure (psychology)Injury preventionOccupational safety and healthOddsPsychologyEnvironmental healthPsychiatryPolitical scienceLogistic regressionNursing

Abstract

fetched live from OpenAlex

Using administrative child welfare data from the Ontario Child Abuse and Neglect Data System (OCANDS), this study compared the profiles of Asian-Canadian and White-Canadian children and families that experienced a case closure after an investigation instead of being transferred to ongoing child protection services (CPS). Child protection investigations involving Asian-Canadian and White-Canadian children and families that were transferred to ongoing CPS presented a different profile of case characteristics and caregiver and child clinical needs. Asian-Canadian children and families received ongoing CPS for over a month longer than White-Canadian children and families and were less likely (odds ratio [ OR] = 0.39) to be reinvestigated for any form of maltreatment-related concerns within 1 year after case closure. It appears that child protection investigations involving Asian-Canadian children and families are less likely to be closed prematurely than White-Canadian children and families, and the child protection system may be meeting the needs of Asian-Canadian communities. Alternatively, it is possible there is unaccounted biases that may be reflective of systemic problem of discriminative practices in the child protection system. Further research is needed to explore this phenomenon.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.267
Teacher spread0.240 · 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 teacher head, not a consensus.

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

Citations7
Published2017
Admission routes2
Has abstractyes

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