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
Following recent studies in Florida and Canada, we examine the effects of prison visitation on recidivism among 16,420 offenders released from Minnesota prisons between 2003 and 2007. Using multiple measures of visitation (any visit, total number of visits, visits per month, timing of visits, and number of individual visitors) and recidivism (new offense conviction and technical violation revocation), we found that visitation significantly decreased the risk of recidivism, a result that was robust across all of the Cox regression models that were estimated. The results also showed that visits from siblings, in-laws, fathers, and clergy were the most beneficial in reducing the risk of recidivism, whereas visits from ex-spouses significantly increased the risk. The findings suggest that revising prison visitation policies to make them more “visitor friendly” could yield public safety benefits by helping offenders establish a continuum of social support from prison to the community. We anticipate, however, that revising existing policies would not likely increase visitation to a significant extent among unvisited inmates, who comprised 39% of our sample. Accordingly, we suggest that correctional systems consider allocating greater resources to increase visitation among inmates with little or no social support.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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