Offender Treatment Attrition and its Relationship with Risk, Responsivity, and Recidivism
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
This investigation examined factors contributing to attrition from correctional treatment and the implication that treatment noncompletion may have for issues concerning risk, recidivism, and responsivity. Participants included 93 violent offenders who had been referred to an intensive treatment program in a maximum security correctional facility. Descriptive information, program participation, and recidivism data were gathered from comprehensive institutional and police records. Treatment noncompleters had less formal education and less employment history in the community. They were more likely to be of aboriginal ancestry and classified to maximum security, scored more poorly on several treatment process variables, and were higher risk offenders. Subsequent analyses demonstrated that very high-risk aboriginal offenders were particularly vulnerable to dropping out of treatment (80%). The findings are discussed with respect to the principles of risk and responsivity.
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 | 0.000 | 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) | 0.000 | 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