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Record W2129748850 · doi:10.3390/ijerph8072692

Work and High-Risk Alcohol Consumption in the Canadian Workforce

2011· article· en· W2129748850 on OpenAlexaffabout
Alain Marchand, Annick Parent‐Lamarche, Marie-Ève Blanc

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2011
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsOddsEnvironmental healthConsumption (sociology)WorkforceOdds ratioAlcohol consumptionLogistic regressionOccupational safety and healthDemographyHuman factors and ergonomicsGerontologyPoison controlMedicinePsychologyAlcoholSociologyEconomics

Abstract

fetched live from OpenAlex

This study examined the associations between occupational groups; work-organization conditions based on task design; demands, social relations, and gratifications; and weekly high-risk alcohol consumption among Canadian workers. A secondary data analysis was performed on Cycle 2.1 of the Canadian Community Health Survey conducted by Statistics Canada in 2003. The sample consisted of 76,136 employees 15 years of age and older nested in 2,451 neighbourhoods. High-risk alcohol consumption is defined in accordance with Canadian guidelines for weekly low-risk alcohol consumption. The prevalence of weekly high-risk alcohol consumption is estimated to be 8.1% among workers. The results obtained using multilevel logistic regression analysis suggest that increased work hours and job insecurity are associated with elevated odds of high-risk alcohol consumption. Gender female, older age, being in couple and living with children associated with lower odds of high-risk drinking, while increased education, smoking, physical activities, and, and economic status were associated with higher odds. High-risk drinking varied between neighbourhoods, and gender moderates the contribution of physical demands. The results suggest that work made a limited contribution and non-work factors a greater contribution to weekly high-risk alcohol consumption. Limits and implications of these results are 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 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)0.008
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 score0.063
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
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 integrity0.0000.002
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 head0.170
GPT teacher head0.443
Teacher spread0.273 · 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 teacher head, 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

Citations56
Published2011
Admission routes2
Has abstractyes

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