Accessing drug treatment courts do age, race or gender matter?
Bibliographic record
Abstract
To ensure equitable access to diversion from custody, Canadian drug treatment courts should accept referrals whose age, gender, and Indigenous race proportions are similar to probation or custody admissions. Of particular concern are Indigenous offenders, who are over-represented in Canada’s community and institutional corrections systems. To examine the influence of these extra-legal factors, we assessed referrals to the Winnipeg, Manitoba drug treatment court ( N = 288). Provincial corrections data from Statistics Canada’s adult key indicator report, eight years of official records drug court data (2006–2014), and local male sentenced inmate admission data were analyzed. Age, gender, and Indigenous status did not influence referral. Indigenous male referrals to the drug treatment courts were generally higher risk than females or other males. Correctional institutions data showed that Indigenous male inmates had more convictions for violence and higher street gang membership rates, thus attempting to increase drug court referral poses significant challenges. In Manitoba, substantial custody reductions of offenders overall and Indigenous male offenders in particular will require more radical solutions than the drug court.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".