Analysis of Participation Levels in Activity Programming at a Correctional Mental Health Facility
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 paper examines factors of participation in activity programming, presenting the results of a secondary data analysis of resident records at a state-run forensic mental health treatment facility. Factors contributing to participation as well as characteristics of those with high participation means were examined within both a voluntary referralbased activity program and a mandatory structured activity program. The results suggest that, despite many differences between the samples of residents receiving the two programs, there were specific characteristics more common among those with higher participation means, such as a higher sum of activity hours per month, a higher mean sum of hours in each activity type per month, and a decreased length of stay (LOS). The results also demonstrated a therapeutic value to the activity programs offered, regardless of the voluntary or mandatory nature of the program.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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