Racial inquiries: law and the political visibility of racism in the Air India inquiry
Bibliographic record
Abstract
Critical race scholarship has effectively documented how the legal institutions of liberal democratic states figure as both mechanisms of systemic racism and avenues of redress against these forms of power. This article offers new insights into the racial effects of these legal institutions by examining the epistemic dynamics of a Canadian public inquiry that was tasked with investigating why state institutions failed to prevent and successfully prosecute the bombings of two Air India flights, which investigators attributed to Sikh nationalist groups operating in Canada. Through a discourse analysis of documents generated during the inquiry, I track how its complex epistemic dynamics precluded recognition of the racial effects of Canadian state institutions. Approaching the inquiry as an instrument of juridical knowledge production and mechanism of political accountability, this article tracks the contingent processes through which liberal epistemologies of race are validated by state actors to extend race’s systemic conditions of existence.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.030 | 0.087 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| 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".