Social and Epidemiological Research on Alcohol: Research Presented at Meetings of the Kettil Bruun Society between 1983 and 2017
Bibliographic record
Abstract
Aims: The Kettil Bruun Society (KBS) is a leading international society, known in full as the Kettil Bruun Society for Social and Epidemiological Research on Alcohol. This paper aims to analyse research presented at KBS annual meetings and provide an overview of the developments in the research agenda in the field. In this way we try to gain insight into worldwide developments in the research agenda on social and epidemiological research on alcohol between 1983 and 2017. Methods: For the period 1983–1992, all annual meetings were the object of study. For the period after 1993, three sample periods of the annual meetings were used. The current paper is the fourth overview paper in a series. All papers have been reviewed with regard to their content, the research methods used, the country of origin, and the gender of the presenting authors. Results: The number of papers presented at the annual KBS meetings increased from 35 in 1983 to over 160 in the years after 2009. In the period 1983–2017, the percentage of papers on policy and prevention doubled. Surveys have been the most popular research method in the period reviewed here. Conclusions: The KBS is the international society for this type of research, and developments within the KBS give an indication of the worldwide developments in the research agenda on social and epidemiological research on alcohol between 1983 and 2017.
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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 | 0.021 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".