Not Part of the Job: An Analysis of Characterizations of Workplace Violence against Nurses in Canada by Unions and Professional Associations
Bibliographic record
Abstract
In the spring of 2019, Canada's House of Commons Standing Committee on Health reviewed the issue of workplace violence in healthcare and issued a report with nine recommendations. By summer that year, the Canadian Federation of Nurses Unions had two active campaigns on workplace violence characterized by a strong social media presence. In 2020, a private member's bill was sponsored to amend Canada's Criminal Code in cases of assault against a healthcare worker. In the face of these developments, we were interested in the framing of the problem of workplace violence by professional and labour organizations in Canada. We examined documents, websites and social media posts from selected nursing unions and professional associations, including both national and provincial organizations. We found that nursing unions and professional associations have distinctive views on workplace violence. We argue that these divergent understandings preclude the creation of consistent and successful political and organizational strategies that would help create safe workplaces for nurses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".