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Record W4406320199 · doi:10.1111/jar.70006

‘I Don't Think I Have Ever Worked Harder on a Case’: Needs of Canadian Child Protection Workers and Parents With Intellectual Disabilities

2025· article· en· W4406320199 on OpenAlexafffundabout
Munazza Tahir, Virginie Cobigo

Bibliographic record

VenueJournal of Applied Research in Intellectual Disabilities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsIntellectual disabilityChild protectionPrejudice (legal term)PsychologyService (business)Service providerPerspective (graphical)Qualitative researchPublic relationsSocial psychologyNursingPolitical scienceMedicineBusinessSociologyPsychiatryMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: The current literature has established that prejudice in child protection cases with parents with intellectual disabilities continues to persist. However, complexities of these cases are not well-understood from the perspective of child protection workers. This study aimed to identify the needs of child protection workers and their views on factors that influence supports for parents with intellectual disabilities. METHOD: This qualitative study conducted semistructured interviews with child protection workers who have worked directly with parents with intellectual disabilities across five child protective agencies in three regions in Ontario, Canada (n = 11). RESULTS: Three major themes emerged after content analysis of interviews: (1) training and support needs of child protection workers; (2) key sources of support for parents; and (3) intersecting factors impacting decision-making. CONCLUSION: Social service agencies continue to be fragmented and better coordination across agencies is needed to meet the cross-sectoral needs of parents with intellectual disabilities.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.088
GPT teacher head0.361
Teacher spread0.273 · 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 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

Citations3
Published2025
Admission routes3
Has abstractyes

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