Palliative care & the injustice of mass incarceration
Bibliographic record
Abstract
Due to the criminalization of marginalized people, many markers of social disadvantage are overrepresented among prisoners. With an aging population, end of life in prison thus becomes a social justice issue that nurses must contend with, engaging with the dual suffering of dying and of incarceration. However, prison palliative care is constrained by the punitive mandate of the institution and has been critiqued for normalizing death behind bars and appealing to discourses of individual redemption. This paper argues that prison palliative has much to learn from harm reduction. Critical reflections from harm reduction scholars and practitioners hold important insights for prison palliative care: decoupled from its historical efforts to reshape the social terrain inhabited by people who use drugs, harm reduction can become institutionalized and depoliticized. Efforts to address the harms of substandard palliative care must therefore be interwoven with the necessarily political work of addressing the injustice of incarceration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.026 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".