Extraction, Indigenous Dispossession and State Power: Lessons from Standing Rock and Wet’suwet’en Resistance
Bibliographic record
Abstract
When Indigenous-led resistance to land- and water-killing projects threatens extraction, settler-colonial state and corporate institutions use security mechanisms to eliminate such “threats.” Using as case studies the pipeline conflicts of the Wet’suwet’en Nation’s (especially Unist’ot’en Camp’s) resistance to Coastal GasLink (CGL) in British Columbia (BC), Canada, and the Standing Rock Sioux Tribe’s resistance to the Dakota Access Pipeline (DAPL) in North Dakota, United States (US), this paper explores how fossil-fuel extraction interacts with critical infrastructure (CI) securitization to further Indigenous land dispossession. I argue that although the Wet’suwet’en and Standing Rock cases both involved the state and corporations criminalizing Indigenous resistance to extraction—to uphold fossil-fuel capital interests—the Wet’suwet’en case is unique because Canadian actors attempted to pacify resistance through symbolic appeals to Indigenous rights. Indigenous communities across the world are violently oppressed for peacefully defending their water, land, and communities. However, the motives and strategies of violence are unique for every colonial jurisdiction exercising violence, and for every Indigenous community impacted. I compare and contrast the rationales and strategiesof both cases through an in-depth content analysis of passages from TigerSwan surveillance and BC Supreme Court injunction documents. I discuss my findings within theoretical debates on dispossession and securitization.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.036 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".