Conceptualizing structural violence in the context of mental health nursing
Bibliographic record
Abstract
This article explores how the intersections of gendered, racialized and neoliberal dynamics reproduce social inequality and shape the violence that nurses face. Grounded in the interviews and focus groups conducted with a purposeful sample of 17 registered nurses (RNs) and registered practical nurses (RPNs) currently working in Ontario's mental health sector, our analysis underscores the need to move beyond reductionist notions of violence as simply individual physical or psychological events. While acknowledging that violence is a very real and disturbing experience for individual nurses, our article casts light on the importance of a broader, power structure analysis of violence experienced by nurses in this sector, arguing that effective redress lies beyond blame shifting between clients/patients and nurses. Our analysis illustrates how assumptions about gender, race and care operate in the context of global, neoliberal forces to reinforce, intensify and create, as well as obscure, structural violence through mechanisms of individualization and normalization.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".