Framing, Suppression, and Colonial Policing Redux in Canada: News Representations of the 2019 Wet’suwet’en Blockade
Bibliographic record
Abstract
In early 2019, the Royal Canadian Mounted Police (RCMP) intervened at the Gidimt’en Access Checkpoint in northern British Columbia (BC) and arrested 14 land defenders, garnering global media attention. To explore the ways that settler common sense ( Rifkin 2013 ) is assembled and perpetuated in Canada, this paper examines how Wet’suwet’en mobilization is framed in news media coverage. Situating our work in relation to settler colonial studies and informed by the writings of Indigenous scholars, we use critical discourse analysis to assess mainstream news media framings of the Wet’suwet’en struggle. Drawing from literature on social movement suppression, we discern three main themes in these texts that work to validate the RCMP’s excessive use of force against land defenders and delegitimize the Wet’suwet’en’s claim to sovereignty. While this framing set the stage for sustained corporate incursions, police surveillance, and occupation across unceded Wet’suwet’en territory, we suggest negative framing as well as activist use of social media to visualize state repression may have created the conditions for what Hess and Martin (2006) call backfire.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.031 | 0.020 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".