Addressing health workers’ exposure to violence at Lebanese emergency departments: What do the stakeholders think?
Bibliographic record
Abstract
Healthcare settings are notorious for exposing their employees to high levels of verbal and physical violence. A recent study on occupational violence at Lebanese Emergency Departments (EDs) revealed that 70% of surveyed ED workers were exposed to at least one incidence of violence over the last twelve months. Acting on the findings of this study a multi-stakeholder policy forum was held with key ED stakeholders to discuss possible policy and practice changes to reduce health workers’ exposure to occupational violence. Stakeholder deliberations revealed that the root causes of violence in EDs could be classified under three main categories relating to the administration of EDs including the presence of antiviolence policies, the management of human resources, and balancing patient expectations. Stakeholders built a consensus on a number of remedial actions at the societal, health care facility and policy levels. Engaging with various stakeholders in an open forum was a unique initiative that contributed to building a consensus among key stakeholders on a road map to help protect health workers in EDs and beyond.
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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 | 0.029 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".