‘Half-breeds,’ racial opacity, and geographies of crime: law’s search for the ‘original’ Indian
Bibliographic record
Abstract
Discussions of hybridity have proliferated in cultural geography and in social and cultural theory. What has often been missing from these accounts are the ways in which mixed-race identities have been forged, contested, and embodied spatially. Inspired by recent calls in cultural geography to rematerialize race and drawing from the growing literature on law and geography, this article examines the material dimensions of hybridity, how it was legally produced, gained traction, and slipped in the quotidian spaces of everyday encounters. Focused on late-19th and early-20th-century British Columbia (Canada), I trace the emergence of the ‘half-breed’ as a new racial personage and juridical taxonomy that unsettled racial hierarchies and spatial distinctions between aboriginal and white settler populations. Unlike other colonial contexts, mixed-race peoples on Canada’s west coast did not threaten European superiority alone but were believed to endanger the protection and assimilation of aboriginal peoples. Proximities between ‘half-breeds’ and ‘Indians’ were politically charged for two reasons. First, racial differentiations between these populations were often imperceptible, and second, their putative distinctions were closely bound up with concerns over territory and with aboriginal well-being. The racial opacity of mixed-race peoples created some sites of mobility for those in-between. However, their unknowability shored up the uncertainties of colonial knowledge production and the limits of existing racial repertoires, creating persistent demands for new markers of racial otherness in the process. Crime and immorality became potent signifiers of racial inferiority aimed at differentiating half-breeds from Indians and providing authorities with additional optics through which to problematize and govern their affective and geographical encounters.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.018 | 0.117 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| 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".