Fostering post‐conventional consciousness in leaders: why and how?
Bibliographic record
Abstract
Purpose The purpose of this paper is to clarify why and how leadership development programs should be used to foster post‐conventional consciousness in their participants. Design/methodology/approach Starting from the observation that current and future organizational challenges may be met with particular efficacy by leaders who operate in the post‐conventional stages of consciousness, this paper offers a comprehensive review of the work on consciousness development, the process by which it occurs, the distinctive abilities of leaders who have reached post‐conventional stages of consciousness and, finally, two practices which favour the emergence of these stages, namely mindfulness meditation and Bohm dialogue. Findings The paper shows how these two practices – little‐used in the management field – make it possible to reconcile the two main approaches to consciousness development: the recognition of one's cognitive, affective and operative patterns and their suspension in favour of a more direct contact with reality, in the here and now. Practical implications The paper highlights guiding principles for integrating such practices into leadership and management development programs. Originality/value Although the value of post‐conventional stages of consciousness in management and leadership roles is the subject of increasing discussion, to the authors' knowledge no work has yet thoroughly examined practices that foster post‐conventional development per se.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".