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Record W3126168949 · doi:10.3138/jmvfh-2020-0011

Identifying release-related precursors to suicide among Canadian Veterans between 1976 and 2012

2021· article· en· W3126168949 on OpenAlexafffundvenueabout
Linda VanTil, Kristen Simkus, Elizabeth Rolland-Harris, Alexandra Heber

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsPublic Health Agency of CanadaVeterans Affairs Canada
FundersCanadian Psychological AssociationCanadian Armed ForcesU.S. Department of Veterans Affairs
KeywordsOfficerSuicide RiskDemographyMilitary serviceMedicineService memberSuicide preventionGerontologyMilitary personnelMedical emergencyPoison controlPolitical scienceSociology

Abstract

fetched live from OpenAlex

LAY SUMMARY The Veteran Suicide Mortality Study describes the risk of death by suicide for Canadian Veterans using data linkage at Statistics Canada. The study includes Veterans released with Regular Force or Reserve Force Class C service over the period 1976-2012. Both male and female Veterans had higher risk of suicide if they released at non-officer ranks. For men, the risk of suicide death peaked around four years after release from the military. For women, the risk of suicide death peaked around 20 years after release. This study provides information for the timing of 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)0.001
metaresearch head score (Gemma)0.004
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 score0.038
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.004
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.341
Teacher spread0.282 · 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

Citations8
Published2021
Admission routes4
Has abstractyes

Explore more

Same venueJournal of Military Veteran and Family HealthSame topicSuicide and Self-Harm StudiesFrench-language works237,207