Urbanization, migration and alcohol use in a population of Greenland Inuit
Bibliographic record
Abstract
OBJECTIVE: To analyse the effects of migration and urbanisation on alcohol intake among a population of Greenland Inuit. STUDY DESIGN: Population-based cross-sectional study of 4,139 Inuit randomly selected from Denmark and four areas of western Greenland. Data collection was based on interviews and self-administered questionnaires. METHODS: The association between different aspects of alcohol intake (quantity of intake, occasional heavy drinking, and the modified CAGE questionnaire) and place of living were analysed using a chi-square test and logistic regression analysis. RESULTS: The population living in Denmark had a higher mean alcohol intake than those living in Greenland. Drinking above the sensible drinking limits (21 drinks per week for men and 14 drinks per week for women; where one drink contains 12 g alcohol) was also more prevalent in the population living in Denmark, whereas a higher proportion of those living in Greenland was abstaining. In contrast to the higher alcohol intake in the population living in Denmark, a higher proportion of individuals with episodes of heavy drinking (binge drinking), was observed in both large and small communities in Greenland. A higher proportion of positive results on the modified CAGE test, measuring alcohol dependence, were also seen in large communities in Greenland. We found no statistically significant differences in alcohol intake between Inuit living in large and small communities in Greenland. When comparing Inuit living in Denmark according to length of stay in Denmark, we found a significantly increase in prevalence of binge drinking with length of stay, while no significant variation with length of stay was found for other alcohol parameters. CONCLUSION: Our findings suggest that the alcohol intake among Inuit, living in Denmark and in Greenland respectively, differs in relation to total intake, drinking patterns and a measure of alcohol dependence. Whether this may be attributed to urbanization, or to migration, is not clear.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".