Crisis conservation and green extraction: biodiversity offsets as spaces of double exception
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
Extraction and conservation seem to be polar opposites, yet they entertain multiple relations as the 'greening' of extractive activities mobilizes conservation efforts to address the 'extinction crisis.' Drawing on a review of the literature and two case studies, this article discusses the politics of affinity and enmity shaping the extraction-conservation nexus, and partnerships. As crisis conservation and green extraction receive increased attention, the article suggests that the convergence of extraction and conservation is not only pragmatic, but also reflects shared discursive imaginaries and valuations of nature, practices materialized through spaces of 'double exception', and common politics of enmity directed at local communities that legitimize exclusionary practices rather than solve capitalism's contradictions.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it