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Record W1992610553 · doi:10.1027/0227-5910.25.4.156

Intentional and Unintentional Injuries Across Health Regions in Alberta, Canada

2004· article· en· W1992610553 on OpenAlex
Angus H. Thompson, Kim Borden, Kathy Belton

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCrisis · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsUniversity of Alberta
FundersNational Center for Injury Prevention and Control
KeywordsOccupational safety and healthSuicide preventionInjury preventionPoison controlPopulationHuman factors and ergonomicsEmpirical researchGeographyEnvironmental healthMedicinePsychology

Abstract

fetched live from OpenAlex

The growing practice of including intentional injuries (suicide and interpersonal violence) under the injury control umbrella has produced some controversy. The present study was designed to determine whether or not there might be an empirical basis for this initiative from an ecological point of view by examining the associations among unintentional and intentional injuries across 17 geographically defined health regions. The study was set in the Province of Alberta, Canada, where health services were delivered to a population of 2.96 million persons in 1999 through 17 regional health authorities. The results of a principal components analysis showed that nearly all causes of injury-hospitalization loaded on a single factor. It was not possible to produce separate factors for intentional and unintentional injuries. The strong intercorrelation among all measures suggests that there is an empirical basis for the view that intentional and unintentional injuries belong under the same conceptual umbrella, at least at the ecological level.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.307
Teacher spread0.294 · 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