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
Purpose The purpose of this paper is to examine the relationship between abusive supervision and employee health and safety outcomes in Study 1 and to examine the effect of inconsistent leadership, operationalized as the interaction between transformational leadership and supervisor incivility, on employee safety participation in Study 2. Design/methodology/approach In Study 1, survey data were gathered from n =145 healthcare workers. In Study 2, survey data were gathered from n =177 nurses. Findings A partially mediated structural model was estimated in Study 1 and the results show that the model provided a good fit to the data χ 2 (1)=1.27, p =0.23. Abusive supervision predicted safety climate ( β =−0.41, p <0.01) and psychological health ( β =−0.27, p <0.01). Safety climate, in turn, predicted psychological health ( β = 0.40, p <0.01) and safety participation ( β = 0.37, p <0.01). Study 2: moderated regression analysis showed that inconsistent leadership significantly predicted employee safety participation, F (5,144)=4.46, p <0.01. Originality/value Theoretical and practical implications for creating psychologically healthy workplaces through interventions aimed at improving leader effectiveness are discussed.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it