Compulsory drug detention center experiences among a community-based sample of injection drug users in Bangkok, Thailand
Bibliographic record
Abstract
BACKGROUND: Despite Thailand's official reclassification of drug users as "patients" deserving care and not "criminals," the Thai government has continued to rely heavily on punitive responses to drug use such as "boot camp"-style compulsory "treatment" centers. There is very little research on experiences with compulsory treatment centers among people who use drugs. The work reported here is a first step toward filling that gap. METHODS: We examined experiences of compulsory drug treatment among 252 Thai people who inject drugs (IDU) participating in the Mitsampan Community Research Project in Bangkok. Multivariate logistic regression was used to identify factors independently associated with a history of compulsory treatment experience. RESULTS: In total, 80 (31.7%) participants reported a history of compulsory treatment. In multivariate analyses, compulsory drug detention experience was positively associated with current spending on drugs per day (adjusted odds ratio [AOR] = 1.86; 95%CI: 1.07 - 3.22) and reporting drug planting by police (AOR = 1.81; 95%CI: 1.04 - 3.15). Among those with compulsory treatment experience, 77 (96.3%) reported injecting in the past week, and no difference in intensity of drug use was observed between those with and without a history of compulsory detention. CONCLUSION: These findings raise concerns about the current approach to compulsory drug detention in Thailand. Exposure to compulsory drug detention was associated with police abuse and high rates of relapse into drug use, although additional research is needed to determine the precise impact of exposure to this form of detention on future drug use. More broadly, compulsory "treatment" based on a penal approach is not consistent with scientific evidence on addressing drug addiction and should be phased out in favor of evidence-based interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".