“Jail isn’t the answer for these inmates”: how to respond to methamphetamine use in prisons
Bibliographic record
Abstract
PURPOSE: The correctional system continues to face challenges with responding to and managing methamphetamine use among incarcerated individuals. This study aims to uncover what resources and policies could better help correctional workers deal with these challenges. The authors also examined methamphetamine's impact on correctional work and staff well-being. DESIGN/METHODOLOGY/APPROACH: = 269) in Manitoba, Canada, featuring questions about their experiences related to methamphetamine use in populations under their care, what supports are needed to adequately address the concern, and the potential effects on self and their occupational responsibilities. Using NVivo software, survey responses were analysed using an emergent theme approach. FINDINGS: Correctional workers believed policies and protocols for managing methamphetamine use and withdrawal are currently inadequate. Correctional workers reported having monthly contact with incarcerated individuals experiencing methamphetamine withdrawal, posing safety concerns to them and other incarcerated individuals. Respondents proposed more education and training on managing incarcerated people withdrawing from methamphetamines, related to the symptoms of use and withdrawal and how to support persons detoxing. Increased human and material resources were reported as being needed (e.g. more nurses onsite and better screening devices). Respondents also desired more medical intervention, safe living spaces for methamphetamine users and programming to support addiction. ORIGINALITY/VALUE: The current study unpacks correctional workers' perspectives, support desires and their experiences managing methamphetamine use amongst incarcerated people. The authors discuss the required knowledge to respond to gaps in prison living, re-entry and related policy needs.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".