Leaders and Emotional Intelligence: A View from Those Who Follow
Bibliographic record
Abstract
Abstract-Boyatzis and Goleman state that Emotional Intelligence (EI) "is an important predictor of success." In their book Primal Leadership, they refer to "the leadership competencies of emotional intelligence: how leaders handle themselves and their relationships." The leadership exercises reported here examined the practices of effective and ineffective leaders as identified by individuals who have worked under such leaders (ie, followers/subordinates). We sought to ascertain to what extent these practices are related to EI. The 2-year data from these leadership exercises show the strong relationships between perceived leadership effectiveness and emotionally intelligent leadership practices as observed by leaders' followers. For example, whether considering the practices that made effective leaders effective or the practices that ineffective leaders needed to adopt or significantly improve upon (in the eyes of subordinates), these practices were almost exclusively related to EI. These findings are supported in the EI literature, as is the strength of subordinates' assessments in predicting leadership effectiveness.
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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 | 0.000 |
| 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) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".