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Record W2122659242 · doi:10.51952/9781447315674.ch002

Child protection: 40 years of learning but where next?

2014· book-chapter· en· W2122659242 on OpenAlexaboutno aff
Ray Jones

Bibliographic record

VenuePolicy Press eBooks · 2014
Typebook-chapter
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

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).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.291
Teacher spread0.238 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2014
Admission routes1
Has abstractyes

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