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Record W2947512937 · doi:10.32799/ijih.v13i2.32061

Rethinking Indigenous Suicide

2018· article· en· W2947512937 on OpenAlexafffundvenueabout
Jeffrey Ansloos

Bibliographic record

VenueInternational Journal of Indigenous Health · 2018
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Toronto
FundersGovernment of Canada
KeywordsSuicidologyIndigenousMainstreamIdeologyContext (archaeology)SociologyPraxisCriminologySocial scienceSuicide preventionPoison controlPolitical scienceEnvironmental ethicsMedicinePoliticsLawGeographyEnvironmental healthEcologyArchaeology

Abstract

fetched live from OpenAlex

Suicide is one of the most significant issues facing Indigenous communities throughout Canada. The rate of Indigenous deaths by suicide is severely disproportionate to that of the general public. While the last three decades have seen substantial investments in suicidology research within the Canadian context, rates of Indigenous deaths by suicide have remained relatively stable, and little remains known about effective means to reduce Indigenous deaths by suicide. A movement of critical suicidology scholars across health and social sciences is beginning to challenge the mainstream approach of suicidology research and suicide prevention, citing concerns about the ideological and epistemic foundations. In this article, the author highlights how these critiques are relevant to Indigenous contexts. Challenging a range of assumptions, the author considers the need to rethink the ideological foundations of research on Indigenous suicide. Finally, the author considers two methodological projects that are integral to forming a critical approach to Indigenous suicidology research and Indigenous suicide prevention praxis–culturally grounded research and decolonizing research.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.394
Teacher spread0.336 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations66
Published2018
Admission routes4
Has abstractyes

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