Perspectives on wildlife health in national parks: concurrence with recent definitions of health
Bibliographic record
Abstract
A Delphi exercise involving 17 senior national parks’ biologists in the United States of America and Canada examined how evolving concepts of wildlife health resonated with Parks’ needs. Participants examined wildlife health as a multi-factorial cumulative effect that provides capacity to cope with a changing world. They agreed that this concept of health was consistent with Parks’ goals and provided insight on various aspects of wildlife health in national parks. Social and environmental determinants of health were perceived to be greater threats to wildlife health than etiological hazards such as pathogens, the more typical focus of wildlife health efforts. While social and anthropogenic factors are primary drivers of these threats, participants did not explicitly rank social variables as the more important drivers of wildlife health nor did the majority view health as a social construct. The results clearly show support for moving toward a contemporary approach of wildlife health management, as opposed to disease management, and for the need of collective, team-based approaches to protecting the suite of determinants of health.
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 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 | 0.062 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".