Employee well‐being attribution and job change intentions: The moderating effect of task idiosyncratic deals
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We developed and tested a research model in which employee well‐being human resource (HR) attribution differentially influences the intention to change jobs across organizations (i.e., external job change intention) versus that within the same organization (i.e., internal job change intention). Furthermore, we posited that task idiosyncratic deals (I‐deals) moderated the relationships between employee well‐being HR attribution and external and internal job change intentions. Results indicated that employee well‐being HR attribution was negatively related to external job change intention, but positively related to internal job change intention. Further, task I‐deals significantly moderated the relationships between employee well‐being HR attribution and external and internal job change intention. Specifically, employee well‐being HR attribution played a less important role in reducing external job change intention when task I‐deals were high rather than low. On the other hand, high task I‐deals significantly strengthened the positive relationship between employee well‐being HR attribution and internal job change intention. Our study extends the careers literature by differentiating the impact of employee well‐being HR attribution on job change intentions within an organization compared with that across organizations and the important role of supervisors in enhancing or mitigating these effects.
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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 | 0.001 | 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