Resistance and Opposition: Analyzing the Defeat of Bill 57 in the Manitoba Legislature as an Act of Indigenous Counter-Securitization Discourse
Bibliographic record
Abstract
Abstract Securitization scholars in Canada have investigated how settler-colonial governments discursively construct extractive infrastructure and policing on Indigenous lands as “critical” for Canada’s economic security. Less literature exists about how Indigenous activists through provincial institutions counter colonial securitization discourse and legislation. This article interrogates discourse in the Manitoba Legislature pertaining to three “critical infrastructure” bills presented by the PC government during the fall 2020 and winter 2021 sessions: Protection of Critical Infrastructure Act (Bill 57), Animal Diseases Amendment Act (Bill 62), and The Petty Trespassers Amendment and Occupiers’ Liability Amendment Act (Bill 63). The study combines an analysis of the bills’ debates, drawn from Hansard, with an interview with then-official opposition house leader, Nahanni Fontaine, to explore the interactions between securitization and counter-securitization discourse(s) and defeat of Bill 57. The study hypothesizes that Indigenous MLAs’ counter-securitization discourse reconstructed the bills as attacks on Indigenous ontological, environmental, and physical security.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.024 | 0.031 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| 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".