Correctional services during and beyond COVID-19
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
Correctional services, both institutional and within the community, are impacted by COVID-19. In the current paper, we focus on the current situation and examine the tensions around how COVID-19 has introduced new challenges while also exacerbating strains on the correctional system. Here, we make recommendations that are directly aimed at how correctional systems manage COVID-19 and address the nature and structure of correctional systems that should be continued after the pandemic. In addition, we highlight and make recommendations for the needs of those who remain incarcerated in general, and for Indigenous people in particular, as well as for those who are serving their sentences in the community. Further, we make recommendations for those working in closed-custody institutions and employed to support the re-entry experiences of formerly incarcerated persons. We are at a critical juncture—where reflection and change are possible—and we put forth recommendations toward supporting those working and living in correctional services as a way forward during the pandemic and beyond.
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) | 0.001 | 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