When do challenge‐hindrance stressors differentially effect employees' ability to meet work deadlines?
Bibliographic record
Abstract
Abstract This study adds to the extant research by investigating the differential effects of challenge‐hindrance stressors on employees' ability to meet work‐related deadlines. We also examine the mediating role of emotional exhaustion and moderating role of core self‐evaluation (CSE) in this process. Using multi‐source, time‐lagged data (N = 203) collected from employee‐supervisor dyads, this study pinpoints an important reason why employees experience of challenge and hindrance stressor invoke differential effects on their ability to meet work‐related deadlines is that they feel emotionally exhaustion when faced with stressful work demands. However, employees with high CSE can control themselves in these uncertain situations such that the indirect effects of challenge‐hindrance stressors on timely completion of work tasks, via exhaustion, are less salient for them. The study implications suggest that HR managers and decision makers need to openly communicate the risks and challenges associated with the work demands so that employees can appraise these tasks as either challenging or hindrance. Moreover, involving employees with high levels of CSE would further increase the chances that employees will complete their work tasks on time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".