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Record W4410696468 · doi:10.1111/cfs.13314

Care Providers of Indigenous Children and Youth in the Child Welfare System: A Scoping Review

2025· review· en· W4410696468 on OpenAlexafffundabout
Amanda Rae Ervin, Anika Dirk, Hannah Odekina, Fatemeh Sahlehi Shahrabi, Chloe Luck, Mary Greenshields, Janice Victor

Bibliographic record

VenueChild & Family Social Work · 2025
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Lethbridge
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Lethbridge
KeywordsIndigenousWelfare systemWelfareSocial workFoster carePsychologySociologyDevelopmental psychologyNursingMedicineEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

ABSTRACT Indigenous children continue to be significantly over‐represented in child welfare systems in Canada, the United States, Australia and New Zealand. This scoping review represents a subset of a larger review, the objective of which was to consolidate the extant literature on Indigenous child welfare. The results from the broader review were categorized into 10 different subtopics, of which care provider experiences, the topic of this article, is just one. This review summarizes research pertaining to foster parents and kinship caregivers of Indigenous children within the child welfare system. Key findings included caregivers' financial challenges, rewards of fostering, barriers to providing Indigenous cultural and relational connections, barriers to recruiting Indigenous foster parents and mistrust of the child welfare system. Recommendations emphasized Indigenous‐run programmes, education and training for service workers and recruiting foster families willing to maintain youth connections to family and culture. This review further identifies a small but growing collection of Indigenous‐led or co‐authored scholarship that is bringing more balance and knowledge to a topic still dominated by Western research models and biases.

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)0.002
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0140.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes3
Has abstractyes

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