Emerging Paths of Presencing Leadership: A Nature-Inspired Framework for Cultivating Presencing as a Way of Being
Bibliographic record
Abstract
This article reimagines leadership as an ecologically attuned practice of presencing, grounded in ethical responsiveness to nature’s underlying generative intelligence. It invites leaders to cultivate a nature-informed sensibility and imaginal attunement to emergence. Rooted in three naturesourced, orienting principles — the Rhizomic, Telluric, and Heliotropic — this framework integrates Dynamic Presencing’s (DP) foundational gestures of letting go, letting be, and letting come. These principles guide leaders through three interwoven narrative phases of leadership apprenticeship: Coming Home, Being Home, and Venturing Forth from Within. The Rhizomic principle invites a grounded, non-linear mode of leadership rooted in humility and openness, supporting leaders in releasing control and cultivating authenticity. The Telluric principle fosters deep inner presence and ethical discernment, enhancing the capacity to hold space with steadiness and care amid complexity. The Heliotropic principle aligns leaders with emergent possibilities, guiding their actions toward collective well-being and the unfolding of shared potential. Together, these principles illuminate the inner transformation required for presencing leadership—one guided by a nature-inspired wisdom ethic that is responsive to complexity and grounded in timely, coherent action. By reimagining presencing in this way, this DP framework empowers leaders to source their ethical action from a deeper ecological, more-than-human context.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".