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Record W1999207593 · doi:10.1080/09595230500170274

Alcohol and suicide at the population level-the Canadian experience

2005· article· en· W1999207593 on OpenAlexaboutno aff
Mats Ramstedt

Bibliographic record

VenueDrug and Alcohol Review · 2005
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
FundersSocialdepartementet
KeywordsPer capitaDemographyAlcohol consumptionSuicide preventionConsumption (sociology)PopulationGeographyPoison controlMedicineEnvironmental healthAlcoholSociology

Abstract

fetched live from OpenAlex

Studies suggest that the population level link between alcohol and suicide differs across countries and between men and women. The aim of this paper was to estimate the relationship between alcohol consumption and suicide in Canada and to put the results in a comparative perspective. The relationship was elucidated for whole Canada, different provinces and also separately for men and women. The total suicide rate in Canada increased significantly by around 4% as alcohol consumption increased by one litre per capita, suggesting that approximately 25 - 30% of Canadian suicides were related to alcohol. The relationship was stronger for women than for men. A significant effect was found in all provinces except from Quebec, but the overall regional variation was not statistically significant. In an international perspective, the relationship for women was somewhat weaker than in Sweden and Norway, but larger than in Finland, the United States and Southern European countries. For men, the association was similar to what is found in the United States and Finland, weaker than in Sweden, Norway and Russia but stronger than in Southern European countries. The results only partly support the idea that intoxication frequency explains national differences in this relationship. Possible explanations for the stronger association among women are also discussed.

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 score0.029
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.097
GPT teacher head0.374
Teacher spread0.276 · 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

Citations54
Published2005
Admission routes1
Has abstractyes

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