Did Emotional Intelligence Traits Mitigate COVID-19 Uncertainty Effects on Financial Institutions’ Board Decision-Making Process?
Bibliographic record
Abstract
This study uses a qualitative research mixed methods design to explore the Coronavirus pandemic’s uncertainty effect on mature board governance practices and a board decision processes framework within 16 large Australian financial services entities. Findings provide support for two effects. Firstly, the Coronavirus pandemic had led to a hesitation effect on the board members on-going journey of developing a conscious sense of ‘self’ and awareness. Secondly, the skills and diversity of personalities of directors comprising the board has a positive impact on the effectiveness and success of strategic decisions. The ongoing ambiguity impact of the Coronavirus pandemic on effective board decision-making processes was investigated. The board members expressed confidence in the Australian financial services sector’s ability to overcome the global Coronavirus pandemic’s temporary uncertainty impact on board decision processes frameworks. Future research may extend the focus to senior executives’ or owners’ EI personality traits to investigate the relationship between such individual’s or teams’ traits and ongoing effective board decision-making processes during uncertainty in either developing or developed countries or a cross-cultural study.
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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 | 0.001 | 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 | 0.001 |
| 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".