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Record W2140709876 · doi:10.1177/0011392111400788

Thinking Goudge: Fatal child abuse and the problem of uncertainty

2011· article· en· W2140709876 on OpenAlexaffabout
Gerald Cradock

Bibliographic record

VenueCurrent Sociology · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsReflexivityChild protectionChild abuseJudgementHomicideCertaintyCriminologyRisk societyPoison controlSociologyPsychologySuicide preventionSocial psychologyLawMedicinePolitical scienceSocial scienceMedical emergencyEpistemology

Abstract

fetched live from OpenAlex

The increased valuation of children’s lives characteristic of modern society emphasizes the problem of child abuse. Beginning in the 1960s, increased public awareness of child abuse led to increased attention to the professions concerned with child homicide. This attention has taken the form of inquiries into children’s deaths that historically concentrated on social work ‘error’. Recent inquiries have expanded their attention to other professions, particularly the medical and policing professions. Ontario’s Goudge Inquiry centred on paediatric forensic pathology but, rather than focusing concern on murdered children, considered the moral hazard of wrongful convictions stemming from an overzealous concern with child abuse. The inquiry thus raises the problem of what evidence is certain, and how this certainty is evaluated. In turn, this makes the risk of child abuse reflexive insofar as under conditions of uncertainty professional medical judgement contains reflexive risk conditions. Because of these reflexive conditions, professional willingness to engage in child protection is being undermined and therefore threatens to paralyse the larger child protection project.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0140.078
Scholarly communication0.0110.012
Open science0.0020.007
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.296
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations11
Published2011
Admission routes2
Has abstractyes

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