Critical Discourse, Critical Action: An Analysis of Federal Discourse and Action in Response to the Final Report of the National Inquiry into Missing and Murdered Indigenous Women and Girls
Bibliographic record
Abstract
Violence against Indigenous women and girls is an unacceptable tragedy in Canada. The 2019 Final Report of the National Inquiry into Missing and Murdered Indigenous Women and Girls concluded Canada is guilty of "a race-based genocide of Indigenous Peoples ... which especially targets women, girls, and 2SLGBTQQIA people." Using an intersectional feminist research ethic, I undertake a critical discourse analysis to determine in what ways key concepts such as national myth, dismissals of harm against Indigenous peoples, and conceptualizations of genocide influenced the reactions of the five major federal political parties to the Final Report. I review the parties' respective commitments to action by analyzing their 2021 electoral platforms and compare their discourse in the wake of the release of the Final Report with their official platform commitments. In essence, the research's empirical contribution shows an enabling self-confirming relationship between the key concepts present in political discourse in response to the Final Report and a political party's path forward when it comes to addressing violence against Indigenous women and girls.
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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 | 0.032 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.045 | 0.070 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".