Climate change impacts, conservation and protected values: Understanding promotion, ambivalence and resistance to policy change at the world conservation congress
Bibliographic record
Abstract
The impacts of climate change imply substantive changes to current conservation policy frameworks. Debating and formulating the details of these changes was central to the agenda of the Fourth World Conservation Congress (WCC) of the International Union for Conservation of Nature (IUCN). In this paper, we document the promotion of, and resistance to, various proposals related to revising conservation policy given climate impacts as they unfolded at this key policy-setting event. Our analysis finds that, during one-on-one interviews, many experts acknowledged the need for new policy means (including increased interventions) and revised policy objectives given anticipations of habitat and species loss. However, this same pattern and the implied willingness to consider more controversial strategies were less evident at public speaking events at the WCC. Rather, active avoidance of contentious topics was observed in public settings. This resulted in the reinforcement (not revision) of conventional policy means and objectives at this meeting. We suggest that this observation can at least partly be explained by the fact that the difficult trade-offs (species for species or land base for land base) implied by nascent proposals severely violate prevailing value-based conservation commitments and so understandable resistance to change is observed.
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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 | 0.027 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| 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".