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Record W4409335417 · doi:10.1177/27551938251327904

Feeling the Structural: School-Based Educators’ Perspectives on Indigenous Child Suicidality in Canada

2025· article· en· W4409335417 on OpenAlexafffundabout
Jordan McVittie, Jeffrey Ansloos

Bibliographic record

VenueInternational Journal of Social Determinants of Health and Health Services · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Toronto
FundersCanada Research Chairs
KeywordsIndigenousMental healthThematic analysisPsychological interventionPublic healthPovertyPoison controlSuicide preventionFeelingMedicineChild abusePsychologyQualitative researchPsychiatryEnvironmental healthPolitical scienceNursingSociologySocial psychology

Abstract

fetched live from OpenAlex

Suicide is a critical public health issue disproportionately affecting Indigenous communities in Canada, especially children. Research on child suicide remains scarce, resulting in a limited understanding of its risk and protective factors. Identified risk dimensions include mental and behavioral health, relational issues, and significant adverse childhood experiences like abuse, and bullying. Studies on Indigenous youth and adults also emphasize the effects of colonization, public policy on child welfare, and systemic racism. The lack of research specifically addressing Indigenous child suicidality underscores the urgent need for tailored research. This article presents findings from a study engaging First Nations and Inuit educators, revealing factors linked to suicidal distress among Indigenous children. Through reflexive thematic analysis, three major themes emerged: the proximal emotional toll of distal risk factors, the impact of adverse childhood experiences, and the role of material deprivation in enhancing risk. Insights from educators are vital for developing targeted interventions to improve prevention efforts.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0300.011
Scholarly communication0.0050.002
Open science0.0020.007
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.396
Teacher spread0.373 · 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 designQualitative
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

Citations3
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Social Determinants of Health and Health ServicesSame topicSuicide and Self-Harm StudiesFrench-language works237,207