Fostering and framing international social research on alcohol and other drugs: A tribute to<scp>R</scp>obin<scp>R</scp>oom
Bibliographic record
Abstract
This commentary concentrates on three aspects of Robin Room's research history: the extent and scope of his research, his role as a builder of research milieus and his importance for the creation of research networks. It is not intended to be a comprehensive analysis, but rather illustrative. A supplementary table provides information on 24 international research projects that Robin Room led or where he played a significant role. In addition to looking at his scientific production history as reflected in databases, when preparing this essay the authors consulted 38 researchers who had worked or presently work with him in various projects, groups or in the research institutes where has held leadership positions. We posed questions pertaining to: major research issues over the past 50 years, the involvement of Robin Room in various projects, the ways in which these projects had contributed to social science or practice and Robin's contributions to the creation of research milieus.
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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 | 0.054 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.045 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".