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Record W2508970606 · doi:10.52922/ti154878

Self-inflicted deaths in Australian prisons

2016· book· en· W2508970606 on OpenAlexaboutno aff
Matthew Willis, Ashleigh Baker, Tracy Cussen, Eileen Patterson

Bibliographic record

VenueAustralian Institute of Criminology eBooks · 2016
Typebook
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPrisonQuarter (Canadian coin)Suicide preventionCommissionMedicineRoyal CommissionPoison controlInjury preventionPsychiatryMedical emergencyCriminologyPsychologyPolitical scienceLawGeography

Abstract

fetched live from OpenAlex

The AIC has operated the National Deaths in Custody Program since 1991, following a recommendation by the Royal Commission into Aboriginal Deaths in Custody. This study updates and extends an earlier AIC study, which examined the important issue of self-inflicted deaths in prison custody using deaths in custody data for the period 1999–2013. Regrettably, suicide remains a common cause of death in prison; however, it is no longer the most common cause of death. While self-inflicted deaths constituted half of all prison deaths between 1980 and 1998, they have declined to the point that between 2004 and 2013—the most recent decade for which data are available—they represented around a quarter of prison deaths. This decrease reflects the considerable progress made by corrective services administrators in developing policies and practices, and implementing cell designs, that address suicide risk factors. Nonetheless, these data and coronial findings suggest there is still room for improvement, particularly in responding to prisoners with psychiatric needs and in the management of unsentenced prisoners.

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), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.144
GPT teacher head0.404
Teacher spread0.260 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2016
Admission routes1
Has abstractyes

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