The patterns of alcohol use among Warsaw adolescents across 20 years - from 1988 to 2008
Bibliographic record
Abstract
Okulicz-Kozaryn, K. & Borucka, A. (2013). Patterns of alcohol use among Warsaw adolescents across 20 years—from 1988 to 2008. International Journal of Alcohol and Drug Research, 2(2), 37-44. doi: 10.7895/ijadr.v2i2.102 (http://dx.doi.org/10.7895/ijadr.v2i2.102)Aim: The study investigates patterns of alcohol drinking among 15-year-old Polish students in Warsaw over the past 20 years.Methods: Data were collected from six consecutive surveys, beginning in 1988 (N = 3918) and conducted every four years (in 2008, N = 1229).Results: Two-step cluster analysis across all six consecutive surveys indicated a clear differentiation of the social context of adolescent alcohol drinking patterns. Adolescents are least likely to drink alcohol alone (< 5%) or heavily with peers (< 10%), more likely to drink with parents (15%-20%), in moderate amounts with peers (11%-28%) or not at all (11%-27%), and most likely to be light social drinkers (30%-46%). Cross-gender comparisons suggest that traditional gender differences are fading away; the data show increases in moderate social drinking among females and abstinence among males.Conclusions: Our results confirm that adolescents’ patterns of alcohol use are stable over time, despite the social and political changes that have occurred in Poland since 1988, and reflect a pattern of mostly moderate drinking.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".