Bibliographic record
Abstract
Exclusion on various scales and in a variety of forms was central to the reimagining of the north Pacific coast as Euro-Canadian or American space, including restricting the entry of Japanese migrants at international borders, the denial of the of the full rights of citizenship to Japanese immigrants and Indigenous people, and barring access to certain kinds of occupations by law or in practice. On both sides of the Canada-US border, exclusion also sometimes took the form of overt expulsion. This chapter examines instances where Japanese and Chinese labor migrants and settlers were driven out of towns in British Columbia, Alaska, and the Yukon, arguing that the use of mob violence was integral to the reimagining of this region as “white”. Like government-sanctioned forms of exclusion, the expulsion of Japanese migrants mirrored efforts to erase the presence of Indigenous people, including the Taku River Tlingit near Atlin, B.C., from the colonial landscape in both countries. During the early decades of the twentieth century, the governments of both Canada and the US repeatedly worked together to ensure that the race-based barriers each erected against Japanese immigration and the acknowledgment of Indigenous rights reinforced those of the other.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.053 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".