Culture of masculinity, alcohol consumption and risk to cancer: an international survey
Bibliographic record
Abstract
Objective: To understand the underlying cultural effects of masculinity on alcohol consumption and the associated risk for cancer. Method: An exploratory online survey. Data was collected (2018-2019) from 176 men living in 9 countries who responded to an online survey in English, French, Italian, Portuguese, or Spanish. Socio-demographic data and responses to close-ended questions were compiled as descriptive statistics. Responses to the open-ended questions were analyzed using thematic analysis with the pre-established themes: alcohol consumption and its acceptance for men in respondents’ ethno-cultural groups; and thoughts about scientific evidence concerning the consumption of alcohol in high concentration and heightened risk of cancer. Results: Most respondents were under 30 years of age (33.7%). Results across the linguistic sub-samples indicate that among 10 statements, alcohol consumption is part of most students’ life (18.8%), it facilitates acceptance in social groups (16.9%), and it is not repressed at social gatherings (16.6%). Construction (27.5%) was the top among professions in which alcohol consumption is most common. Among situational factors related to alcohol consumption, respondents chose stress (18.1%), unemployment or unstable job (18.0%), and financial trouble (17.9%). Perceptions of acceptance of alcohol consumption are influenced by traditional masculinity-related values, beliefs, and behaviors and the acknowledged lack of cancer literacy were revealed as conditions promoting a risk for cancer. Conclusion- Alcohol consumption is normalized to a certain extent among men of different ages and backgrounds. Evidence informs policymakers and health promoters as they develop legislation and programming to limit unhealthy behavior related to alcohol consumption.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".