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Record W2055575178 · doi:10.1080/01639620701233100

Strain, Emotion, and Suicide Among American Indian Youth

2007· article· en· W2055575178 on OpenAlexaboutno aff
Melissa L. Walls, Constance L. Chapple, Kurt D. Johnson

Bibliographic record

VenueDeviant Behavior · 2007
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral strain theoryAngerStressorPsychologyClinical psychologyTest (biology)Suicide preventionGeneral partnershipPoison controlSocial psychologyDevelopmental psychologyMedicinePolitical scienceMedical emergency

Abstract

fetched live from OpenAlex

In this article, we test the utility of Agnew's general strain theory to explain suicidal behaviors among American Indian youth. Data from 721 American Indian adolescents from the Midwest and Canada were collected in partnership with participating reservations/reserves and a research team. We investigate the effects of strains/stressors on suicide, including tests of mediating effects of negative emotions on relationships between stressors and suicidality. We found that several strains/stressors were related to suicidality, including coercive parenting, caretaker rejection, negative school attitudes, and perceived discrimination. We also found that depressive symptoms and anger mediated the effects of several key predictors of suicidality. We discuss the theoretical and policy implications of our work for the general strain theory and for American Indian suicide in general.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.040
GPT teacher head0.328
Teacher spread0.288 · 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 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

Citations64
Published2007
Admission routes1
Has abstractyes

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