A Feeling of Unease: Distance, Emotion, and Securitizing Indigenous Protest in Canada
Bibliographic record
Abstract
Abstract Why do public officials sometimes avoid using security claims to frame an issue, even when there are strong incentives and historical precedent for doing so? Efforts to portray indigenous protest as a security issue are a recurring feature of Canada's settler colonial history. Recently, however, a series of public officials have emphatically rejected these kinds of claims. To explain this puzzle, I argue that a growing feeling of unease over the history of settler colonialism has transformed once acceptable security claims into sources of controversy and racism. Generated through diverse social repertoires linked to indigenous-led forms of reconciliation, this unease has resulted in officials facing pressure to distance themselves—through denials, apologies, and euphemisms—from claims that have become increasingly controversial. The result is not a direct end to the securitization of indigenous protest—some figures may actively court controversy, while others can still make these claims in private conversation or internal documents. Instead, the effect of this unease is to render these claims less publicly defensible and thus make security practices targeting indigenous communities appear increasingly illegitimate.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.041 | 0.036 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.009 |
| 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".