Science, Ethical Arguments, and Management in the Preservation of Land for Grizzly Bear Conservation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".