I Could Turn You to Stone: Indigenous Blockades in an Age of Climate Change
Bibliographic record
Abstract
Indigenous Peoples in Canada and around the world have, for years, used blockades and direct action when alternative means of asserting their rights have failed. The Secwépemc First Nation of British Columbia, Canada, has a myth where a character, Sk’elép, encounters strangers who try to “transform” him, but fail. He tells them he could turn them to stone, but he will not. This myth is used as a lens to reflect, from a settler perspective, on the potential for future Indigenous-led blockades, which could reach the point of mass economic shutdowns, in response to a lack of action on both Indigenous rights and climate change. Up until now, the policy of most colonial nations has been to deal with Indigenous blockades by force or at best with localised solutions. This policy will not work regarding climate change. This article proposes that the Western world faces a stark choice: truly embrace “free, prior, and informed consent” (FPIC), or else face the possibility of large scale shutdowns from a growing alliance of Indigenous Peoples, environmentalists, and concerned citizens.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.046 | 0.037 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".