Child Abuse Tort Claims Against Public Bodies
Bibliographic record
Abstract
Foreword, Allan Levy Suing health authorities in Ireland: recent legal developments, Ann Power Child abuse claims against public authorities under the Human Rights Act 1998, Jane Wright Child abuse compensation claims: a practitioner's perspective, Elizabeth-Anne Gumbel Child abuse tort claims against public bodies in Italy, Roberto Caranta Child abuse tort claims against public bodies in South Africa, Rosalind English Liability for government actions: a comparative study of English and American law, Helene Goldberg Antipodean perspectives on child welfare tort claims against public authorities, Geoff McLay Child abuse and the failure to protect: liability of public authorities in Canada, Margaret Hall Child welfare and state liability in France, Duncan Fairgrieve National report on Germany, Martina Kunnecke Child abuse tort claims in the Netherlands, Cees van Dam.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.035 | 0.017 |
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".