Contingency Management Programs in Corrections: Another Panacea?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The mantra of best practices in corrections, while well intended, may lead to iatrogenic consequences. Community corrections and prisons are under increasing pressures to manage their caseloads; moreover, the current accountability and get-tough agenda in corrections demands offenders take on more responsibility for their behaviors. As a consequence, we predict more episodes of “panaceaphilia” or quick fix solutions because corrections jurisdictions in the United States are under tremendous pressure to handle their populations at this point in time. In this article, we focus on contingency management programs as the potential next panacea, not because they do not have a proven track record of success, but because they require highly skilled staff and make great demands upon correctional agencies’ decision-making practices. To help counteract panaceaphilia from happening with contingency management, we describe the theory and practice of contingency management, the demands they place on programmers, the type of research needed to evaluate their effectiveness, and how to prevent these programs from turning into punitive punishment regimes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it