US environmental NGOs and the Cree. An unnatural alliance for the preservation of nature?
Bibliographic record
Abstract
This article will attempt to understand the complex relations between indigenous peoples and environmental NGOs in the context of conflict caused by a hydroelectric development mega‐project in James Bay in subarctic Quebec. There is an ambiguity in the mediator and spokesperson role that NGOs take on in defending the cause of indigenous peoples, in so far as they oscillate between acting as mere middlemen, as brokers, and as patrons. Even beyond the tangle of multiple and conflicting interests, however, environmentalists are torn between their own conceptions of nature and those of the people they defend. Environmentalists are heirs to the notion, characteristic of the pioneers who discovered America through the prism of the Bible: a wild and threatening “wilderness”, to this, they have now added the objective of protecting nature against threats posed by humans. In both conceptions, which have successively haunted Western imaginations, nature offers to humans, when lost in its vastness and far from their fellows, a direct relation alongside God. How then might it be possible to work with the Cree, and indigenous peoples generally, to protect a nature that they do not regard as separate from humankind, but of which they are an integral part? How long will it remain possible to do without an analysis of the concept of nature conservation which, in the context of shared environmental causes, establishes our relation to others even as we exclude them?
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".