Integrative review on place-based and other geographically defined responses to drug-related threats in communities
Bibliographic record
Abstract
A key element in successive Irish drugs strategies has been the involvement of nongovernmental \norganisations and public agencies at various levels, from the local to the national, \nwith the participation of communities and local stakeholders being central to Action 4.1.39 of \nthe current strategy (Department of Health 2017). The key role accorded to Local and Regional \nDrug and Alcohol Task Forces in responding to drug-related threats confirms the importance \nof working in partnership with communities, which is a central principle of the World Health \nOrganization Ottawa Charter (WHO 1986) and the Action Framework of the European Monitoring \nCentre for Drugs and Drug Addiction (EMCDDA 2021). It is useful, in this context, to review the \ninternational literature on interventions that seek to tackle drug-related harms at the local level \nby involving communities, with a view to providing a more comprehensive evidence base that \ncan contribute to policy debates in Ireland. The aim of this report is thus to provide a summary \nof the international evidence on place-based initiatives in the context of drug-related harms.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".