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
Violence in the health care workplace is occurring in a covert fashion; it is occurring at the patient bedside. However, data on workplace violence tend to be underreported and relatively scarce. This article identifies and examines the phenomenon of unreported and underreported workplace violence against nursing staff that is virtually hidden. Health care executives need to be attuned to this type of violence because it may significantly affect their ability to recruit and retain nursing staff. This article provides a synthesis of literature and data from health services administration and nursing and human resources, as well as the experience of the first author. Workplace violence in health care is a critical issue that must be addressed from legal, financial, ethical, and human resources management perspectives. It is a problem for staff providing direct care services to patients with Alzheimer disease. This article suggests strategies and offers a framework for meeting the challenges of managing hidden workplace violence. In addition to the more discrete consequences of violence including physical injury, physical disability, trauma, or even death, the complementary organizational effects call for thoughtful managerial planning and critical thinking. Guidelines for preventing and addressing workplace violence in health care organizations are also published by the Occupational Safety and Health Administration.
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 | 0.000 | 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 | 0.002 | 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