Managed Migration of Coast Redwoods: Subjectivity of Stakeholders in Oregon’s Land Use Planning Community
Bibliographic record
Abstract
The Earth’s climate is changing at a faster pace than the slow natural adjustment rates of most species to their rapidly shifting habitat conditions, especially for long-lived tree species, such as the iconic coast redwood Sequoia sempersqvirens. This may leave some species stranded in less than optimal environments, resulting in population extinctions and/or the need for human-assisted migration. However, the implementation of assisted migration does not come without economic, legal, political, ecological, and ethical issues. One of the most important and complex social questions regarding assisted migration is that of the land use planning community in the area being considered. This article explores the subjective beliefs among these stakeholders regarding managed migration of coast redwood trees into suitable habitats in Oregon. Q-methodology was used to structure the complexity of participants’ subjective beliefs into a few manageable themes to reveal broader socio-economic and environmental perspectives and shared ways of perceiving and valuing the relationship between social, economic, and environmental concerns. The findings of this study suggest two main factors 1) positively ranked values that align on new perspectives of utilitarian ecological values, and 2) positively ranked values that align on a land based communitarian perspective. This convergence suggests an ecologically aware land management ethos as opposed to the view of favoring human’s dominion over nature, and therefore bolsters the potential for the future success of managed migration of coast redwoods into suitable habitats in Oregon given the state’s existing land use policy.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".