From nation to population: the racialisation of ‘Métis’ in the Canadian census<sup>†</sup>
Bibliographic record
Abstract
ABSTRACT. Between 1996 and 2001 the ‘Métis population’ of Canada skyrocketed from 204,000 to 292,000, an astonishing and demographically improbable increase of 43 per cent. Most puzzling about this ‘increase’ is not so much the unpersuasive explanations offered by statisticians and others but, more fundamentally, the underlying assumption that such a thing as a ‘Métis population’ exists at all. In contrast, I argue that such an idea constitutes an artifact of Canada's racial/colonial episteme in which ‘the Métis’– formerly an indigenous nation invaded and displaced in the Canadian nation‐state's westward expansion – have been reduced in public and administrative discourse to include any indigenous individual who identifies as Métis: reduced, in other words, to (part of) a race. The paper argues further that the authority of the Canadian census as a privileged forum of contemporary meaning‐making in Canadian society is such that the lack of explicit Census categories to distinguish Métis Nation allegiance further naturalises a racialised construction of Métis at the expense of an indigenously national one.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".