Canada’s Indians (sic): (Re)racializing Canadian Sovereign Contours Through Juridical Constructions of Indianness in McIvor v. Canada
Bibliographic record
Abstract
While scholarship has recognized the role that sex discrimination has played in the naming of “Indians” in Canada, one aspect of this depiction has been minimized. In addition to the gendering of Indigenous subjectivities, Canada has consistently racialized us/them through practices of juridical categorization. The latest court case dealing with Indian registration, McIvor v. Canada, (re)produced this practice. This thesis explores McIvor to understand the relational struggles, limitations, and authority the courts engender when existing constructions of Indigenous legal recognition are challenged. I use Bourdieu’s (1987) juridical field to position “law” as a dynamic arena whereby hierarchical struggles generate social realities. I also utilize Moreton-Robinson’s (2000, 2001, 2004a) theory of patriarchal white sovereignty to understand the ways in which, through its juridical system, Canada is a racialized and racializing state. I seek to demonstrate how Canadian sovereignty is (re)produced through racialized constructions of Indigenous legal recognition in McIvor.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.052 | 0.022 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| 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".