Bibliographic record
Abstract
Drug offenders account for nearly 20% of state prison inmates, almost half of federal inmates, and a quarter of those on probation (Carson & Sabol, 2012; Maruschak & Parks, 2012). National estimates indicate that over half of drug offenders are rearrested within 3 years of release from prison (Langan & Levin, 2002). This points to the need to provide treatment to those with substance use problems, yet relatively few receive treatment while in prison (Mumola & Karberg, 2006). Federal, state, and local agencies must do a better job of identifying those in need of treatment and of providing effective interventions aimed at substance use. Many of the articles in this issue of the International Journal of Offender Therapy and Comparative Criminology have implications for substance use treatment. The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013) included a number of revisions to the diagnostic criteria, including criteria for substance related disorders. Whereas the DSM-IV (4th ed.; APA, 1994) treated substance abuse and dependence as two disorders, the DSM-5 combines these into one category, substance use disorder, and revised the criteria for moderate and severe substance use disorder. Kopak, Metze, and Hoffman examine the impact of the revisions by comparing diagnoses under both DSM-IV and DSM-5 guidelines as they relate to alcohol use disorder. Understanding the impact of the new guidelines is important as they have implications for the nature of substance use treatment. Many drug offenders receive treatment services in the community. Drug treatment courts (DTC) are estimated to serve over 100,000 participants at any given time in the United States (Huddleston & Marlowe, 2011). There is ample research to suggest DTC can reduce recidivism, but more research is needed to know when and how drug courts work best, both in the United States and elsewhere (Mitchell, Wilson, Eggers, & MacKenzie, 2012; Shaffer, 2011). Somers, Rezansoff, and Moniruzzaman explore the predictors of success in a Canadian DTC. Using recidivism as an outcome measure, they examine the effectiveness of the program across a number of sub-groups. This is
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".