Should We Move the Whitebark Pine? Assisted Migration, Ethics and Global Environmental Change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.001 | 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) | 0.022 | 0.002 |
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 it