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Record W1994356653 · doi:10.15270/43-1-289

LAY FORUMS IN CHILD WELFARE

2014· article· nl· W1994356653 on OpenAlexaffabout
Jeanette Schmid

Bibliographic record

VenueSocial Work/Maatskaplike Werk · 2014
Typearticle
Languagenl
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPunitive damagesAdversarial systemWelfareChild protectionIndigenousFoster careDisconnectionService providerPolitical scienceEconomic growthSociologyService (business)Public relationsPublic administrationEconomicsLawEconomy

Abstract

fetched live from OpenAlex

Dealing with child abuse presents many challenges to both policy makers and service providers internationally. Societies have responded differently to this issue (Gough, 1996). In Western countries two broad streams have emerged: one adversarial, the other consensual. The “child protection” approach, common in countries such as the UK, USA, Canada and Australia, has been criticised as being punitive and adversarial, typically marginalising the voice and experience of service users (Merkel-Holguin, 2004; Waldegrave, 2006; Waldfogel, 1998). A more collaborative approach to child welfare is captured in the “family services” and “community care” models, respectively typical of Europe and of aboriginal communities in “developed” countries. It should be noted that the limited literature on child welfare systems operating in “developing” countries implies that services mostly conform to a “child protection” approach as they tend to be residual, deficit based and treatment oriented, and are heavily skewed towards residential care options (Pilotti, 1999; Stockholm University, 2003; Xiaoyuan & Xioaming, 2003). Indigenous helping approaches co-existing with these systems have typically been overlooked. The “community care” model hence constitutes the only child welfare model that formally articulates indigenous approaches.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.013

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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations23
Published2014
Admission routes2
Has abstractyes

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