Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.033 | 0.034 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.002 | 0.027 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.033 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".