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Record W2898158379 · doi:10.1176/appi.ps.201700505

RISING SUN: Prioritized Outcomes for Suicide Prevention in the Arctic

2018· article· en· W2898158379 on OpenAlexfundno aff
Pamela Y. Collins, Roberto A. Delgado, Charlene Apok, L Báez, Peter Bjerregaard, Susan Chatwood, Cody L. Chipp, Allison Crawford, Alex E. Crosby, Denise A. Dillard, David Driscoll, Heidi Ericksen, Jack Hicks, Christina Viskum Lytken Larsen, Richard McKeon, Per Jonas Partapuoli, Anthony G. Phillips, Beverly Pringle, Stacy Rasmus, Sigrún Sigurðardóttir, Anne Silviken, Jon Petter Stoor, Yury A. Sumarokov, Lisa Wexler

Bibliographic record

VenuePsychiatric Services · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersNational Institute of Mental HealthGovernment of CanadaU.S. Department of State
KeywordsIndigenousPsychological interventionSuicide preventionEquity (law)PovertyPoison controlPolitical scienceMental healthEnvironmental healthStakeholderEconomic growthGeographyMedicinePsychologyPublic relationsNursingPsychiatry

Abstract

fetched live from OpenAlex

The Arctic Council, a collaborative forum among governments and Arctic communities, has highlighted the problem of suicide and potential solutions. The mental health initiative during the United States chairmanship, Reducing the Incidence of Suicide in Indigenous Groups: Strengths United Through Networks (RISING SUN), used a Delphi methodology complemented by face-to-face stakeholder discussions to identify outcomes to evaluate suicide prevention interventions. RISING SUN underscored that multilevel suicide prevention initiatives require mobilizing resources and enacting policies that promote the capacity for wellness, for example, by reducing adverse childhood experiences, increasing social equity, and mitigating the effects of colonization and poverty.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.425
Teacher spread0.378 · 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 designObservational
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

Citations21
Published2018
Admission routes1
Has abstractyes

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