Leading through paradox: Navigating tensions in transformative networks
Bibliographic record
Abstract
Abstract Managing multiple paradoxes is critical to transformative systems leadership, particularly in the context of translocal networks. In this paper, we explore a novel aspect of Earth Stewardship: how leaders of these networks harness paradox management to generate and scale innovative sustainability solutions. By integrating seemingly contradictory forces, such as harmony and disruption, cohesion and autonomy, and reflection and action, leaders foster dynamic environments conducive to both innovation and transformative learning. We identify three key paradoxes: (1) the embrace of harmony and disruption, fostering transformative learning; (2) the tension between cohesion and autonomy, which promotes innovation by scaling solutions within diverse contexts; and (3) the interplay between reflection and action, which enhances metis, a crucial strategy for navigating the uncertainties of transitioning systems. These paradoxes, when embraced rather than resolved, enable translocal networks to catalyze systemic changes. This paper explores how these leadership practices drive sustainability solutions, an essential yet underexamined aspect of Earth Stewardship.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".