Initiation of opiate addiction in a Canadian prison: a case report.
Bibliographic record
Abstract
BACKGROUND: In North America, the harms of illicit drug use have been responded to primarily through law enforcement interventions. This strategy has resulted in record populations of addicted individuals being incarcerated in both Canada and the United States. The incarceration of non-violent drug offenders has become increasingly controversial as studies demonstrate the harms, including elevated HIV risk behavior, of incarcerating injection drug users. Other harms, such as the initiation of illicit drug use by prison inmates who previously did not use drugs, have been less commonly described. CASE PRESENTATION: We report on the case of an individual who initiated non-injection opiate use in a Canadian prison and developed an addiction to the drug. Upon release into the community, the individual continued using opiates and sought treatment at a clinic. The patient feared that he might initiate injection use of opiates if his cravings could not be controlled. The patient was placed on methadone maintenance therapy. CONCLUSION: While anecdotal reports indicate that initiation in prison of the use of addictive illicit substances is frequent, documentation through clinical experience is rare, and the public health implications of this behavior have not been given sufficient attention in the literature. Strategies of incarcerating non-violent drug offenders and attempting to keep illicit drugs out of prisons have not reduced the harms and costs of illicit drug use. Effective, practical alternatives are urgently needed; expanded community diversion programs for non-violent drug offenders deserve particular attention.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".