Bibliographic record
Abstract
The UK has had 40 years of learning about how to protect children from neglect and abuse. Based on the welfare state infrastructure built in the 1940s (Timmins, 1995), services, policies and practice have been developed incrementally to respond to and capture the learning. The consequence has been that when compared to other countries, the UK now has one of the lowest incidences of child deaths following the abuse and neglect of children, and this success has been stable and maintained for many years (Pritchard and Williams, 2009). It was 40 years ago in 1973 that there was a major public inquiry into the death of a seven-year-old girl from abuse (Department of Health and Social Security, 1974). Maria Colwell died in Brighton, having been neglected and abused in her family home and then violently assaulted by her stepfather. There had been other inquiries before, such as that into the death of Dennis O’Neill, a 14-year-old boy killed by his foster-father (Home Office, 1945), but what was new in 1973 was the media attention given to the Maria Colwell inquiry. In particular, anger about Maria’s awful life and death was turned from the perpetrators of her neglect and abuse and directed at one of the professionals, Diana Lees, Maria’s social worker, who sought to help families and to protect children. She was vilified in the press, described as ‘the defendant’ during the inquiry’s proceedings, and harassed and threatened by a baying mob, who shouted at her during the hearings and chased her outside the inquiry, causing her to need police protection (Butler and Drakeford, 2011).
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.018 | 0.037 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.020 | 0.038 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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".