Leadership of the Heart: Lessons From a 21st Century Arab Monarch
Bibliographic record
Abstract
The past half a century has witnessed a universal and publicly acknowledged bankruptcy of strong ethical and moral leadership within corporations and nations alike, aptly summed up by President Obama in 2009, as: “the attitude that’s prevailed from Washington to Wall Street to Detroit for too long; an attitude that valued wealth over work, selfishness over sacrifice, and greed over responsibility”. Given the deteriorating state of ethical and humane leadership within much of the current crop of leaders of industry and governments, there are a few valuable lessons to be learned from the life and work of Sheikh Zayed, the monarch of the UAE until recently. Most important perhaps, were his traits of selflessness, sharing, consensus building and striving untiringly to uplift those under his care, eventuating in the transformation of the UAE under his watch, from a state of impoverishment to one of prosperity. There is little difference between modern day CEO’s, monarchs and nations’ leaders. However, whilst they all enjoy immense authority and power, how and to what end they use the same is a matter of personal choice, that eventually determines their legacies. As monarch of a fairly new state, despite being relatively free of legal or institutional compulsions, Sheikh Zayed’s choices were always premised on the ‘others first’ principle, that transformed the UAE to its current state. Surprisingly, despite such rare qualities, little has been written about him in the mainstream western academic leadership and ethics literature, which is a shortcoming this article seeks to rectify.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".