Organizational Commitment and Nurses Characteristics as Predictors of Job Involvement
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
OBJECTIVE: To predict nurses' job involvement on the basis of their organizational commitment and personal characteristics at a large tertiary hospital in Saudi Arabia. DATA SOURCES: Data were collected in 2015 from a convenience sample of 558 nurses working at a large tertiary hospital in Riyadh, Saudi Arabia. STUDY DESIGN: A cross-sectional correlational design was used in this study. Data were collected using a structured questionnaire. PRINCIPAL FINDINGS: All commitment scales had significant relationships. Multiple linear regression analysis revealed that the model predicted a sizeable proportion of variance in nurses' job involvement (p < 0.001). CONCLUSIONS: High organizational commitment enhances job involvement, which may lead to more organizational stability and effectiveness.
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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) | 0.000 | 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