A study of the Yin and Yang model of leadership for individual and collective leadership development
Bibliographic record
Abstract
Using the Yin and Yang Model of Leadership, this research engaged in embedded action research by studying feedback from 2,277 leaders in Canada and France who experienced the Yin and Yang Model in the context of leadership programs between 2008 and 2015. Leadership theories have continued to abound since the early 20th century and leadership scholars have increasingly called for integrative strategies and multilevel models that can address leadership development from an individual level as well as from a relational level. Three complementary studies of 52 individual and collective leadership development interventions, using the multilevel Yin and Yang Model of Leadership, with appreciative (yin) and its intentional (yang) principles as the underlying framework, were conducted by the author. The results from all three studies strongly support: (a) the model’s multilevel accessibility for leadership development at the individual, dyad, group and organization levels; (b) the use of appreciation and intentionality as two complementary and integrative leadership factors; and (c) the easy application and re-application of the model by participants from all walks of life. These results call for more research on each of the two principles as generative leadership attitudes, their interrelated dynamic as a guiding model for self-mastery and self-leadership, the applications to groups and collective leadership development, and the model’s general accessibility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".