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Leadership: a New Frontier in Conservation Science

2009· article· en· W2155798651 on OpenAlexaff
JIM C. MANOLIS, Kai M. A. Chan, Myra E. Finkelstein, Scott E. Stephens, Cara R. Nelson, Jacqualine B. Grant, Michael P. Dombeck

Bibliographic record

VenueConservation Biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Ecology, Wildlife Education
Canadian institutionsUniversity of British Columbia
FundersSociety for Conservation Biology
KeywordsFrontierConservation scienceGeographyPolitical scienceRegional scienceEnvironmental ethicsEcologyArchaeologyBiodiversityBiologyPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.057
GPT teacher head0.290
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations91
Published2009
Admission routes1
Has abstractyes

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