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Science, Ethical Arguments, and Management in the Preservation of Land for Grizzly Bear Conservation

2001· article· en· W2063999881 on OpenAlexaff
Maria Davradou, Gene Namkoong

Bibliographic record

VenueConservation Biology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsUniversity of British Columbia
FundersDirectorate for Biological Sciences
KeywordsGrizzly BearsEnvironmental ethicsUrsusGeographySociologyEcologyPhilosophyBiology

Abstract

fetched live from OpenAlex

Abstract: Environmental groups advocate the preservation of an area within British Columbia's coastal temperate rainforest as a sanctuary for grizzly bears ( Ursus arctos horribilis ). Debate among government, industry, and environmental spokespersons has provided arguments but no resolution. We have applied to this issue available biological knowledge on grizzly bears and the arguments of a range of ethical theories. The theories of three professionally trained ethicists were included: Tom Regan, Holmes Rolston III, and Arne Naess. Aldo Leopold's prominent position in the conservation movement justifies his “land ethic” as a fourth ethical theory. All four theories agree that the area should be preserved. Contrary to this fundamental agreement, the theories diverge when tested against a “hard” conservation scenario, the conflict between the protection of the last surviving grizzly bears versus the survival of a culturally distinct human tribe. Application of the principles developed by Regan and Naess recommend that human interests should override the preservation of grizzly bears, whereas Leopold's and Rolston's arguments favor the preservation of the area for the bears. Our work can be used as a model of how the gap between biological sciences, ethical theories, and ecosystem management can be bridged successfully.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.299
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2001
Admission routes1
Has abstractyes

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