Gender, Race and Justification: The Value of Critical Discourse Analysis (CDA) in Contemporary Settler Colonial Contexts
Bibliographic record
Abstract
This paper outlines an approach to critical discourse analysis (CDA) that can be used to examine multiple forms of textual data as part of decolonial practice in any national context that is struggling to acknowledge both its colonial past and its ongoing colonial present. The author provides an explanation of what CDA is followed by a discussion of the methods used in a larger multi-level analysis focused on the impact of the defense witness testimony in a Canadian Pacific salmon fisheries case. The larger project has recently been published in the Windsor Yearbook of Access to Justice. This paper will show how elements of this approach have been used to identify and analyze the strategies of argumentation and justification that are foundational to gendered colonial discourses on race discrimination and property in R. v. Kapp. Contrary to the artificial dichotomy between theory and practice, CDA is not distinct from social and political action. It can instead play a role in identifying the obstacles to, and creating the conditions for, meaningful dialogue and sustainable collaboration.
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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 | 0.045 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.022 | 0.105 |
| Scholarly communication | 0.031 | 0.023 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.005 |
| 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".