“Indians on White Lines”: Bureaucracy, Race, and Power on Northern British Columbian Traplines, 1925–1950
Bibliographic record
Abstract
After British Columbia imposed universal mandatory trapline registration in 1925, game wardens, Department of Indian Affairs officials, and Indigenous people in the provincial north quickly came into conflict over the place of Indigenous trappers, Indigenous claims to trapping territory, and the applicability of colonial game regulations to Indigenous communities. Although some scholars have suggested that the primary result was the large-scale dispossession of Indigenous communities, roughly half of the province’s registered traplines remained officially in “Indian” hands, raising questions about how bureaucrats recognized, classified, and sought to administer such lines. In practice, game law enforcement was often uncertain, arbitrary, and frequently governed by informal arrangements that existed alongside the official regulations. By the 1930s, trappers with Indian status had gained some measure of protection and exemption from the game laws, in part due to an energetic campaign by the federal Indian Department. To bureaucrats, however, the never-completed quest to define and solidify a racialized boundary between “Indian” and “white” trappers, trapping, and traplines often became as important as — or even more important than — the ostensible provincial goal of game conservation and the federal goal of Indigenous economic prosperity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.029 | 0.014 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".