Transferring the Principles of Effective Treatment into a “Real World” Prison Setting
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 principles of risk, need, and responsivity have been empirically linked to the effectiveness of treatment to reduce reoffending, but the transference of these principles to the inside of prison walls is difficult. Results from a sample of 620 incarcerated male offenders—482 who received either a 5-week, 10-week, or 15-week prison-based treatment program and 138 untreated comparison offenders—found that treatment significantly reduced recidivism (odds ratio of .56; effect size r of .10) and that the amount of treatment (e.g., “dosage”) played a significant role (odds ratios between .92 and .95 per week of treatment; adjusted effect size r of .01 and .02). These results indicate that prison-based treatment can be effective in reducing recidivism, that dosage plays a mediating role, and that there may be minimum levels of treatment required to reduce recidivism that is dependent on the level of an offender’s risk and need.
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.
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 | 0.001 | 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) | 0.000 | 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