MétaCan
Menu
Back to cohort
Record W4402576237 · doi:10.1177/10497315241280547

Youth Receiving Child Welfare Services and their Preferred Relationships With Their Service Providers

2024· article· en· W4402576237 on OpenAlexafffundabout
A.K.M. Zafar Khan, Michael Ungar

Bibliographic record

VenueResearch on Social Work Practice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsDalhousie University
FundersNetworks of Centres of Excellence of Canada
KeywordsService providerGrounded theoryPsychological resilienceQualitative researchNova scotiaWelfareService (business)Service delivery frameworkSocial workPsychologySocial psychologySociologyBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

Purpose: This study explores the experiences of youth receiving Child Welfare Services (CWS) in Nova Scotia, Canada and their preferred relationships with different service providers and how these relationships may promote or hinder their resilience at different levels of risk exposure. Method: Qualitative interviews with 23 youth (aged 14–19) were analyzed using grounded theory. Results: The analysis revealed two core categories, relationship building and mentoring relationship as well as supporting themes that were modelled into a theoretical understanding of three distinct relationship patterns (parent-like, peer-like, and professional) that youth seek from their service providers. Findings discuss the category relationship building, comprising of two themes—youth mobility and multiple service providers; followed by a discussion on the three mentoring relationships. Conclusion: Implications address how salient features from these patterns of youth–worker relationships can be effectively integrated into service delivery.

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)0.002
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.996

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.150
GPT teacher head0.392
Teacher spread0.241 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueResearch on Social Work PracticeSame topicChild Welfare and AdoptionFrench-language works237,207