[Nursing in prison: inmates as patients].
Bibliographic record
Abstract
There are very few studies investigating the work nurses do in prisons. Based on data stemming from a research in Psychodynamics of Work and a literature review, this paper describes nursing practices in a Canadian penitentiary institution. Three male nurses and two female nurses participated in three two-hour long focus group sessions. Central sources of pleasure that emerged from the focus groups were the scope of nursing care practice ; the autonomy and collaboration with physicians; nursing care practices devoid of moral value judgments, the humanitarian approach, caring and the wish to make a difference in the lives of the inmates ; the pride connected to this unusual professional context, and the recognition by peers and inmates. The main sources of suffering on the other hand were the feeling that rehabilitation was more an ideal than reality ; the paradox of providing both care and safety ; the scary characteristics of working alone ; the fear of lawsuits, and the feeling of being observed continuously. The resulting data we discuss show the issues of a certain dissociation that exists between the patient and the inmate, the fear of contamination of a healthcare nursing identity by the place of practice, but also the feeling of plenitude and sublimation. The conclusion stresses the tension that exists between security and caring, distance and proximity.
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.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".