Ninja Training Meets Management Education: Integrating Taijutsu into an MBA Complexity Leadership Course
Bibliographic record
Abstract
In this paper I describe the integration of taijutsu, a martial art emerging from the Japanese ninja tradition, into an MBA complexity leadership course. There is broad consensus amongst leadership scholars that intangible qualities such as humility, courage, and uncertainty tolerance are particularly important in complex contexts. There is, however, little consensus as to how such qualities can be effectively cultivated. I review the literature related to martial arts training in management education and discuss the pedagogical challenges of developing both the competencies and capacities required to lead in complexity. I introduce taijutsu and describe several training drills and a facilitation methodology intended to help students develop practical fluency with systems thinking and its implications for leadership and decision-making. Student reflections highlight increased engagement along with potential perspectival and behavioral shifts as promising areas for further investigation. I close by making a case for deeper integration of informational and transformational learning within management education.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".