Aggression and violence in health care professions
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
Although violence is increasing in most workplaces, it has become a significant problem in health care professions. Not only has the number of incidents increased but also the severity of the impact has caused profound traumatic effects on the primary, secondary and tertiary victims. More health care professionals than ever are suffering from symptoms of post-traumatic stress disorder. Addressing the problem of violence in the workplace has been exacerbated by a lack of a clear definition of what constitutes aggression and violence. As a result, some administrators have been slow to commit resources to prevent further incidents and mitigate the impact. This article describes the magnitude of the problem from both an academic research and an operational perspective. A definition is presented as an initial step towards standardizing the research, and establishing an appropriate baseline upon which intervention policies and procedures can be created. This benchmark will also help to encourage empirical research into aggression and violence in health care professions and other professions. Further research needs to be conducted to create a comprehensive instrument that can more accurately measure the range of incidents and the severity of the impact.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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