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Record W2054091948 · doi:10.1080/13811110600582661

A Study of Multi-media Suicide Education in Nunavut

2006· article· en· W2054091948 on OpenAlexaffabout
John Haggarty, John Craven, B. K. Roy Chaudhuri, Zach Cernovsky, Patricia Kermeen

Bibliographic record

VenueArchives of Suicide Research · 2006
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsSt. Joseph's Care Group
Fundersnot available
KeywordsSuicide preventionHAMLET (protein complex)Human factors and ergonomicsInjury preventionPoison controlPsychologyOccupational safety and healthMedical educationApplied psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

A CD-ROM on suicide prevention was evaluated in an Inuit hamlet to examine if knowledge is acquired after viewing this multi-media format of education. Twenty-four respondents showed knowledge increased after viewing. Forty six percent had never used a computer yet 95% felt the technology could train counselors. Such technology may improve knowledge and skills in this cultural setting and perhaps may be useful in other cross-cultural environments.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.540
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.247
GPT teacher head0.550
Teacher spread0.303 · 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

Citations10
Published2006
Admission routes2
Has abstractyes

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