WILDLIFE HEALTH AND THE NORTH AMERICAN MODEL OF WILDLIFE CONSERVATION
Bibliographic record
Abstract
The management of wildlife in the United States and Canada, including the monitoring and maintenance of the health of wildlife populations and the ecosystems on which they depend, are conducted under a set of principles that aim for sustainable use. This set of principles is known as the North American Model of Wildlife Conservation (the Model), and it guides wildlife management and conservation decisions in both countries. The purpose of this perspective is to highlight how wildlife health is an important part of the Model and is vital to its future. It is proposed that wildlife health and the Model support one another. First, the history and fundamental ideas of a public trust that shaped the Model are reviewed. Next, wildlife health is defined and examples are offered that highlight how the Model supports wildlife health and how health affects the Model, as well as the limitations or threats if one moves away from the Model's defining principles. Finally, controversies surrounding the Model are reviewed and a perspective on the future is offered, based in large part on the work of Aldo Leopold. Leopold's thinking about health of the land and its organisms was well ahead of its time, and the scientific underpinnings of his writings in making the case for wildlife health and the Model are recounted. As a simple addendum to Leopold's land ethic, a plea for a health ethic is called for, whereby healthy wildlife and healthy landscapes are an obligation of the Model and modern society because health “tends to preserve the integrity, stability and beauty of the biotic community.”41
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.041 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".