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Record W653376775 · doi:10.5860/choice.39-5801

Protecting biological diversity: roles and responsibilities

2002· article· en· W653376775 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Environmental ethicsPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Catherine Potvin, Margaret Kraenzel, and Gilles Seutin asked scientists from developing countries to summarize their experiences of international collaboration and to suggest attitudes and practices that would lead to more fruitful exchanges with northern scientists. They also asked scholars to provide an analytical framework in which these issues could be discussed and to identify possible solutions to questions such as: What are the responsibilities of first world scientists involved in conservation actions in developing countries? How can biologists work toward the protection of biodiversity while being respectful of the human desire for a better future? The resulting papers analyse specific situations encountered in countries such as Democratic Republic of Congo, Madagascar, India, and Panama and discuss the philosophical basis for environmental research. They also examine the work of two institutions whose projects in developing countries have been particularly effective through outreach and attention to local values and needs and who propose a pluralistic view of conservation biology ethics. Protecting Biological Diversity seeks to encourage students and professionals involved in conservation projects to adopt culturally sensitive attitudes that will lead to greater effectiveness and efficiency in conservation and greater respect for the differences of others. Contributors include H Baser (Canadian International Development Agency, Ottawa), P. Butler (Rare Centre for Tropical Conservation, Saint Lucia), R. Cansari (McGill University), A.K. Gupta (Indian Institute of Management, India), M. Martinez-Velarde (Universidad Santa Maria la Antigua, Panama), L. Mubalama (Institut congolais pour la conservation de la nature, Zaire), B.J Norton (School of Public Policy, Atlanta), L. Packard (Texas A&M University), M.H. Parizeau (Universite Laval), L.H. Rakotovao (Centre national de recherche en environnement, Madagascar), V. Regis (Rare Centre for Tropical Conservation (Saint Lucia), P. Weeks (The Environmental Institute of Houston), and G. Wigley (Ottawa).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.038
Scholarly communication0.0160.010
Open science0.0020.017
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.145
GPT teacher head0.289
Teacher spread0.144 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations10
Published2002
Admission routes1
Has abstractyes

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