Putting a Human Face on Child Welfare: Voices from the Prairies
Bibliographic record
Abstract
The chapters in this book represent a selection of the many very fine presentations made at the Prairie Child Welfare Consortium's (PCWC) 3rd bi-annual Symposium, held in Edmonton, Alberta, November 23–25, 2005. The theme of that Symposium was Putting a Human Face on Child Welfare.\nSharon McKay's article "Development of the Prairie Child Welfare Consortium" at the beginning of this book provides a brief history of the beginnings of the PCWC, illustrating not only its practical, but more importantly the philosophical development. Readers will find that this philosophy informs a great deal of the writing in the 11 chapters of this book.\nThe chapters of Putting a Human Face on Child Welfare: Voices from the Prairies are presented in no particular order, and one is not more important than another. Each presents its unique perspective and represents somewhat different constituents. Collectively, the chapters of this book form a product that is one way of raising the voices of the Prairies, especially as it relates to the important challenges we face at the present time in child welfare.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".