“I Feel Like I’m About to Walk Out of Prison Blindfolded”: Prison Programming and Reentry
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
abstract: People who participate in correctional treatment programming are viewed as making positive steps towards their reentry into society. However, this is often assessed through a simple “yes” or “no” response to whether they are currently participating without much emphasis on how, why, or to what degree that participation is meaningful for reentry preparedness. The present study aims to a) identify to what extent there is variation in the degree to which women participate in programming and are prepared for reentry, b) identify the characteristics that distinguish highly-involved programmers from less involved programmers, c) identify the characteristics that distinguish women who are highly-prepared for reentry from women who are less prepared, and d) assess whether levels of involvement in programming relates to levels of reentry preparedness. The sample comes from interviewer-proctored surveys of 200 incarcerated women in Arizona. Two indices were created: one for the primary independent variable of program involvement and one for the dependent variable of reentry preparedness. Logistic and multivariate regressions were run to determine the indices’ relatedness to each other and the characteristic variables. The two indices did not have a statistically significant relationship with each other. However, variation across them is found. This indicates that programmers may not be a homogenous group and that they may engage with programming to varying degrees based on a multitude of indicators.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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