Racially "Indian", Legally "White": The Canadian State's Struggles to Categorize the Métis, 1850-1900
Bibliographic record
Abstract
The Canadian state has constantly been faced with a paradox: differentiated rights and regulations required it to define the boundaries of the invented category "Indian," yet it was never able to do so satisfactorily. The existence of mixed-ancestry and Métis people disrupted its seemingly clear categories of "Indian" and "White." This thesis asks three central research questions: how did the Canadian state understand the category they called "half breeds;" what cultural and intellectual ideas informed these notions; and what was their impact? There was no single meaning or understanding of the term "Half Breed," but it was in fact characterized by inconsistency, ambiguity, contradiction, and confusion. There were two significant opposing forces at play: 1) the need to consolidate the power of the emerging state, which usually meant grouping the Métis and people of mixed ancestry in with “Indians” in order to better control them, and 2) the desire to save money, which usually meant separating out “half breeds” as a way of reducing the number of status Indians (to minimize the scope of the state’s fiscal responsibilities). The Métis presented themselves as a free “civilized” Indigenous People, but for the government, the term "half breed" was most useful as a floating signifier, with no stable meaning. In an era of increasing state rationalization, the sliding signifier allowed for flexibility in otherwise rigid laws and policy, aiding the state in navigating between its often-conflicting goals. Only in a few instances did the state recognize the Métis as a distinct People. Because of discrimination and the lack of official recognition, many Métis people were dispossessed and hid their heritage. On the other hand, this very ambiguity could provide a degree of freedom, and Métis today are working to define themselves as a distinct people and to fight for their inherent Indigenous rights.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.037 | 0.015 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".