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Record W2905449797 · doi:10.7202/1054238ar

Un nouvel enjeu de santé publique au Canada

2018· article· fr· W2905449797 on OpenAlexaffvenueabout
Rae Spiwak, Brenda Elias, Jitender Sareen, Mariette Chartier, Shay‐Lee Bolton, Florence Dubois

Bibliographic record

VenueCriminologie · 2018
Typearticle
Languagefr
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Chaque année, dans le monde, entre 48 et 50 millions de personnes se retrouvent endeuillées à la suite d’un suicide. Au Canada seulement, ce sont 4 000 individus qui se suicident chaque année, laissant derrière eux un grand nombre de personnes qui doivent faire face au caractère traumatisant et complexe du suicide. Dans un contexte qui avait déjà vu la tentative de suicide être décriminalisée en 1972, la présente étude se penche sur ce qui apparaît désormais constituer une nouvelle problématique de santé publique : le soutien aux personnes endeuillées à la suite d’un suicide. Nous discuterons à cet égard de quelques acteurs clés qui ont influencé les politiques canadiennes sur le sujet : les tribunaux, la Constitution ou encore des groupes qui avaient un intérêt spécifique par rapport à cet enjeu. Les questions de santé associées à ce type de deuil de même que la question de la nécessité de l’intervention seront abordées. Enfin, divers aspects émergents de ces politiques qui demandent encore à être éclairés seront examinés, de même que la nécessité de distinguer les approches à court, moyen et long terme quand on intervient auprès de personnes touchées par ce type de deuil.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.671

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0110.005
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.206
GPT teacher head0.386
Teacher spread0.180 · 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 designNot applicable
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

Citations3
Published2018
Admission routes3
Has abstractyes

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