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Record W2551307046 · doi:10.1097/yco.0000000000000295

Preventing suicide in indigenous communities

2016· review· en· W2551307046 on OpenAlexaffabout
Simon Hatcher, Allison Crawford, Nicole Coupe

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2016
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsIndigenousMedicineGeographyEcologyBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To provide an update on recent studies on suicide prevention in indigenous populations with a focus on recently colonised indigenous peoples in Canada, the United States, Australia and New Zealand. RECENT FINDINGS: There have been several recent reviews on suicide prevention in indigenous populations with high suicide rates. However most of them describe the problem and there is little new that is available on effective interventions. One randomized controlled trial of a package of measures focusing on cultural identity in Maori who had recently self-harmed compared to usual care found little effect on suicidal behavior but it did significantly reduce presentations to hospital for any reason after one year. SUMMARY: The reasons for the limited evidence include a lack of ring fenced funding and a lack of research infrastructure; the problem of high rates of suicide but small numbers; and the difficulty in creating effective collaborations between researchers and communities. Potential solutions include identifying specific research funding; improving capacity in indigenous research; putting effort into accurate identification and recording of ethnicity; and thinking about the problem of suicide in recently colonised populations as a global problem to enable large scale high quality studies to take place.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.148
GPT teacher head0.451
Teacher spread0.303 · 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
GenreReview

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
Published2016
Admission routes2
Has abstractyes

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