Leadership: a New Frontier in Conservation Science
Bibliographic record
Abstract
Leadership is a critical tool for expanding the influence of conservation science, but recent advances in leadership concepts and practice remain underutilized by conservation scientists. Furthermore, an explicit conceptual foundation and definition of leadership in conservation science are not available in the literature. Here we drew on our diverse leadership experiences, our reading of leadership literature, and discussions with selected conservation science leaders to define conservation-science leadership, summarize an exploratory set of leadership principles that are applicable to conservation science, and recommend actions to expand leadership capacity among conservation scientists and practitioners. We define 2 types of conservation-science leadership: shaping conservation science through path-breaking research, and advancing the integration of conservation science into policy, management, and society at large. We focused on the second, integrative type of leadership because we believe it presents the greatest opportunity for improving conservation effectiveness. We identified 8 leadership principles derived mainly from the "adaptive leadership" literature: recognize the social dimension of the problem; cycle frequently through action and reflection; get and maintain attention; combine strengths of multiple leaders; extend your reach through networks of relationships; strategically time your effort; nurture productive conflict; and cultivate diversity. Conservation scientists and practitioners should strive to develop themselves as leaders, and the Society for Conservation Biology, conservation organizations, and academia should support this effort through professional development, mentoring, teaching, and research.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.034 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| 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".