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
Retaining nurses is of significant concern to all hospitals but even more of a concern to northern and rural hospital managers. This study provides insights into factors related to nurses' intentions to remain. A sample of 122 nurses from 13 northern hospitals in Western Canada participated in the study. The nurses completed questionnaires and participated in structured interviews. A model was proposed which suggested that work experiences (job and decision latitude, feedback, perceptions of how viewed and treated by others, fairness of policies, and safety of the job environment) would be related to job satisfaction and then affective commitment. Age and tenure, and ties to the community were proposed as predictors of continuance commitment. Both affective and continuance commitments were expected to be related to intention to remain in the hospital. The model was partially supported by regression analyses. Work experiences predicted job satisfaction and affective commitment. Affective commitment, continuance commitment, and ties to the community are related to nurses' intentions to remain. Supplemental analyses indicated that the strongest relationships were found for management's views and treatment of nurses, knowledge and ability utilization, safe environment, and fairness of organizational policies.
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 | 0.000 | 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) | 0.001 | 0.004 |
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