Should We Move the Whitebark Pine? Assisted Migration, Ethics and Global Environmental Change
Bibliographic record
Abstract
Some species face extinction if they are unable to keep pace with climate change. Yet proposals to assist threatened species’ poleward or uphill migration (‘assisted migration’) have caused significant controversy among conservationists, not least because assisted migration seems to threaten some values, even as it protects others. To date, however, analysis of ethical and value questions about assisted migration has largely remained abstract, removed from the ultimately pragmatic decision about whether or not to move a particular species. This paper uses the case study of the whitebark pine, a keystone species of sub-alpine habitats in western North America, to consider how particular cases of assisted migration may be ethically approached. After taking into account the value of species, wildness, place, ecosystems, culture and sentient animals, we conclude that, on balance, there appear to be good reasons to move the whitebark pine.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".