Working under threat: Fear and nurse–patient interactions in a forensic psychiatric setting
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
The purpose of this article is to present the results of a study conducted in a Canadian medium-security forensic psychiatric facility. The primary objective of this qualitative research was to describe and comprehend how fear influences nurse-patient interactions in a forensic psychiatric setting. Eighteen semistructured interviews with nurses were used as the primary source of data for analysis. In brief, the results from this research indicate, as other researchers have demonstrated, that within this highly regimented context, nurses are socialized to incorporate representations of the patients as being potentially dangerous, and, as a result, distance themselves from idealistic conceptions of care. Moreover, the research results emphasize the implication of fear in nurse-patient interactions and particularly how fear reinforces nurses' need to create a safe environment in order to practice. A constant negotiation between space, "at risk" bodies and security takes place where nurses are forced to scrutinize their actions in order to avoid becoming victims of violence. In parallel, participants also described how being able to self-identify with patients enabled therapeutic interventions to take place. However, exposure to the patient's criminal history fostered negative reactions on the nurses' part, which impede nursing work.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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