Leading through the uncertainty of <scp>COVID</scp> ‐19: The joint influence of leader emotions and gender on abusive and family‐supportive supervisory behaviours
Bibliographic record
Abstract
Abstract As COVID‐19 was a highly novel virus in 2019, it brought risks that are difficult to quantify and rampant uncertainty to the fore. We focus on how leaders navigate such an uncertain context. Drawing upon appraisal theories of emotions, we first argue that under the context of high uncertainty, leaders experience emotions relating to their perceptions of (un)controllability: anxiety and hope. We predict that these have differential behavioural consequences; leaders' anxiety about the pandemic relates to abusive supervision, whereas leaders' hope relates to family‐supportive supervision. Integrating research on gender roles, we theorize that counter to common stereotypes, men's leadership would be more affected by their emotions. At the same time, women would provide leadership behaviours needed by their followers irrespective of their emotions; namely, refraining from abusive and providing family‐supportive supervision. Our hypotheses were supported using a sample of 137 leader‐follower dyads in the early phases of the pandemic. Our research has significant implications for appraisal theories of emotions by demonstrating that the behaviours of women, compared to men, may be less affected by their emotions. These findings present a significant departure from previous literature by revealing an important boundary condition of appraisal theories of emotions.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".