Bibliographic record
Abstract
The aim of this paper is to reflect on the past decade of research and community action on alcohol and especially on some of the presentations given in the three previous international meetings on community action: in Ontario 1989, San Diego 1992, and Greve Florence 1995. The projects reported on are diverse, reflecting the different cultures represented, but there are also common strands. Among these common strands is the growing consensus that at the heart of successful evaluated community action projects is a process of reciprocal and respectful communication: between different community sectors and also between the community and researchers. While there is increased acknowledgment of the knowledge community sectors bring to planning and implementing community action, there is also an increasing focus on the role of the researcher in providing research-based knowledge to facilitate the development of effective community strategies to reduce alcohol-use-related harm. This is in contrast to a research role which emphasizes only outcome evaluation. Another development apparent through the years covered in the international meeting is the use of more naturalistic approaches to evaluation in acknowledgment that experimental design may not be feasible or scientifically appropriate for the evaluation of community action projects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.049 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".