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Fathers' experiences with child welfare services

2012· article· en· W1574558169 on OpenAlexaffabout
Nick Coady, Sandra Hoy, Gary Cameron

Bibliographic record

VenueChild & Family Social Work · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWilfrid Laurier University
FundersU.S. Department of Health and Human Services
KeywordsWelfareWelfare systemService (business)Qualitative researchPrejudice (legal term)PsychologySocial WelfareSocial psychologyDevelopmental psychologyMedicineSociologyPolitical scienceBusinessSocial scienceMarketing

Abstract

fetched live from OpenAlex

ABSTRACT The lack of engagement of fathers by child welfare services is well‐documented in the literature as a serious problem. Towards addressing this problem, this paper reports the findings of interviews with 18 fathers about their involvement with child welfare services in Ontario, Canada. Qualitative analysis of the interviews yielded themes about what men saw as the positive and negative aspects of their involvement with child welfare. Positive aspects of service involvement for fathers included understanding and supportive workers, useful assistance from workers, being connected to useful resources and being given a ‘wake‐up call’. Negative aspects of service involvement included uncaring, unhelpful and unprofessional workers; prejudice against fathers; and experiencing the child welfare system as unresponsive, uncaring and rigid. Implications for practice are discussed with a view to improving the engagement of men in, and their experiences with, child welfare services.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0040.001
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.025
GPT teacher head0.341
Teacher spread0.316 · 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

Citations34
Published2012
Admission routes2
Has abstractyes

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