The Role of Employee Self-Efficacy in Top-Down Burnout Crossover
Bibliographic record
Abstract
: Burnout has been a prominent topic in the management research for over 30 years. Yet few studies have explored the conditions that foster burnout from managers to employees (indirect crossover). Based on the principle of behavioral plasticity, we propose that self-efficacy is an adaptive resource that enables employees to counter the potentially crossover effects of burnout (ie, emotional exhaustion and cynicism). This proposal is partially supported by the results of a longitudinal analysis of educators (principals and teachers): a moderating effect of employee self-efficacy was found, but only for emotional exhaustion, which is considered the basic individual stress dimension of burnout. More specifically, managerial emotional exhaustion was associated with lower emotional exhaustion over time in employees who reported higher self-efficacy, with the inverse association for employees with lower self-efficacy. This suggests that managers' emotional exhaustion can indirectly affect the experience of a congruent emotional state in their subordinates. Theoretical and practical implications are discussed.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".