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Record W4402722363 · doi:10.32799/ijih.v20i1.42187

Sparks of Light, Sparks of Life

2024· article· en· W4402722363 on OpenAlexaffvenueabout
Jeffrey Ansloos, Shanna Peltier, Brenda Restoule, Renee Linklater

Bibliographic record

VenueInternational Journal of Indigenous Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoInstitute for Christian Studies
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

This article examines the critical issue of Indigenous mental health in Canada, focusing on First Nations, Inuit, and Métis. It underscores the urgency in addressing Indigenous mental wellness challenges, particularly the high rates of suicide, amid their rapid population growth. The study centers on the role of frontline responders in managing mental health and suicidal distress in these communities, and their work to promote life and mental wellness. Through a synthesis of psychological, critical, and Indigenous perspectives, the article reviews Canadian literature on Indigenous mental health and suicide prevention. The article then highlights reflexive insights derived from a knowledge-sharing event with 33 Indigenous mental health professionals, focusing on the unique challenges and opportunities in this field and the importance of life-affirming dialogues in suicide prevention. The article aims to integrate these insights into broader discussions on Indigenous mental wellness, health, and life promotion systems, proposing enhanced wellness and suicide prevention strategies and frameworks tailored to the needs and aspirations of Indigenous communities.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.183
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0340.059
Scholarly communication0.0150.010
Open science0.0010.014
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0060.001

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 head0.349
Teacher spread0.331 · 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 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

Citations0
Published2024
Admission routes3
Has abstractyes

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