Depoliticization of Violence: Critical Limits of Risk Environment Frameworks in Drug Use Research
Bibliographic record
Abstract
The risk environment framework (REF) is a widely-accepted tool in policy research related to drug use. Its prevalence warrants a critical exploration of its strengths and weaknesses. This critical appraisal is a comprehensive analysis of the REF by definition and through relevant examples of its use within the context of public health evaluations, social science research, and epidemiological strategies in substance use-related policy. We examine the tensions inherent to a risk environment analysis, centering on its deficit-based lens of behavior, risk, and harm. This narrative review argues for shifts in frameworks within drug policy research away from individual- and community-level blame.
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 | 0.119 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.004 | 0.050 |
| Scholarly communication | 0.016 | 0.025 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".