MétaCan
Menu
Back to cohort
Record W3189378594 · doi:10.3138/jmvfh-2020-0047

A national survey of self-reported mental health of Veterans pursuing post-secondary education in Canada

2021· article· en· W3189378594 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Military Integration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMental healthFeelingHarmPsychiatryMedicineSuicide preventionPsychologyFamily medicinePoison controlMedical emergencySocial psychology

Abstract

fetched live from OpenAlex

LAY SUMMARY This article details self-reported mental health symptoms among Canadian Veterans pursuing post-secondary education in Canada. Participants reported high prevalence of psychological symptoms, most notably feeling exhausted (80.5%) and overwhelmed (78.9%). More than 1 in 10 respondents reported seriously considering suicide (13.4%), and 5.9% had attempted suicide in the past 12 months. Furthermore, 8.7% of respondents had indicated intentional self-harm (cut, burned, bruised, or otherwise injured themselves) within the past 12 months. The findings reflect significant mental health symptoms for Veterans attending Canadian colleges and universities, underscoring the need to provide tailored services to safely integrate Veterans into campus life.

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.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.358
Teacher spread0.320 · 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