Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Daniel Goleman perceptively and accurately noted that emotional intelligence is critical to leadership success, claiming that emotional intelligence is far more important to leadership emergence and effectiveness than intellectual capacity. Goleman’s research later confirmed an 85% relationship between emotional intelligence and leader effectiveness. It may be the most critical area for current and aspiring leaders to develop. While leadership scholars accept the importance of emotional intelligence for leadership and the fact that emotional intelligence can be developed, there appears to be some uncertainty around how emotional intelligence can be developed. The authors shed light on that area and provide current and aspiring leaders with some proven strategies for developing the four predominant components of emotional intelligence. The importance of emotional intelligence to leadership is well documented, and leaders would be well served by working to heighten their levels of emotional intelligence and, in doing so, increase their leadership potential, efficacy, and impact.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.012 | 0.021 |
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 it