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Record W2088982490 · doi:10.1002/car.755

Safeguarding disabled children in residential settings: what we know and what we don't know

2002· article· en· W2088982490 on OpenAlexaboutno aff
Alina Paul, Pat Cawson

Bibliographic record

VenueChild Abuse Review · 2002
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsSafeguardingResidential careRespite careVulnerability (computing)Child protectionPsychologyVulnerable adultMedicinePsychiatryNursing

Abstract

fetched live from OpenAlex

Abstract Research in America, Canada, Australia and Britain has revealed that disabled children are particularly vulnerable to abuse. Their likelihood of attending residential institutions, their dependency on others for personal care and the lack of opportunities for them to alert others to maltreatment or comprehend the nature of abusive acts all increase levels of risk. Over the last decade, there has been increasing public and professional concern about the abuse of children in residential establishments, resulting in a number of inquiries. However, the abuse of disabled children in residential settings has received little attention. Despite residential schools, care homes and respite care being widely used by disabled children, there is a paucity of knowledge regarding the standards of child protection in these establishments. This article explores the research literature revealing the vulnerability of disabled children to abuse when living away from home, what measures can be taken to help protect them and the limitations of available data as a basis for planning child protection measures. Copyright © 2002 John Wiley & Sons, Ltd.

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)0.008
metaresearch head score (Gemma)0.020
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 score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.006
Scholarly communication0.0040.009
Open science0.0020.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.018
GPT teacher head0.280
Teacher spread0.262 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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