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
Bullying is one of the most concerning forms of aggression in health care organizations. Conceptualized as an emotion-based response, bullying is often triggered by today's workplace challenges. Unfortunately, workplace bullying is an escalating problem in nursing. Bullying contributes to unhealthy and toxic environments, which in turn contribute to ineffective patient care, increased stress, and decreased job satisfaction among health care providers. These equate to a poor workforce environment, which in turn increases hospital costs when nurses choose to leave. Nurse managers are in positions of power to recognize and address negative workplace behaviors, such as bullying. However, emerging leaders in particular may not be equipped with the tools to deal with bullying and consequently may choose to overlook it. Substantive evidence from other disciplines supports the contention that individuals with greater emotional intelligence are better equipped to recognize early signs of negative behavior, such as bullying. Therefore, fostering emotional intelligence in emerging nurse leaders may lead to less bullying and more positive workplace environments for nurses in the future.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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