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
Nurses who practice with criminalized women will recognize this group as profoundly marginalized through multiple, intersecting mechanisms. The number of women imprisoned in North America, Latin America, Australia, and Western Europe continues to rise as it has for the past 20 years or more. As a nurse who has practiced almost exclusively with marginalized people, I have met and cared for many women whose health is made vulnerable by race, poverty, homelessness, mental health issues, and other factors. Many of them have been repeatedly incarcerated, experiencing chronically destabilizing cycles of getting arrested, going to jail, getting out, being homeless, getting arrested again, and repeating the cycle. To better understand the implications for nursing with respect to criminalized women, a focused review of the nursing and feminist scholarly literature on incarcerated women was conducted. The predominant themes and trends from both bodies of literature are presented and cross-compared. An analysis of what each body of scholarly work can offer to the other, including implications for nursing practice, concludes the literature review.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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