Bibliographic record
Abstract
Chapter 2 considers ways in which both Indigenous people and Japanese migrants responded to the shifting legal, cultural and legal landscape that followed the formal incorporation of the north Pacific borderlands by Canada and the United States. At times, members of both groups engaged in complex acts of repositioning that took into account ways in which race-based legal restrictions in Canada and the US structured constraint or opportunity within their own borders. Examples include the Tsimishian who relocated to from Metlakatla, B.C. to New Metlakatla, Alaska in response to the B.C. government’s refusal to recognize Aboriginal title in B.C., only to be caught in the gap between ‘immigrant’ and ‘indigene’ in the United States. Also a telling example is that of Jujiro Wada, a Japanese immigrant with ties to both Alaska and the Yukon, who was forced to redefine himself on each side of the US-Canada border given the differing sets of racial barriers Japanese immigrants confronted in each. While Japanese immigrants shared certain attitudes with their Euro-American and -Canadian neighbors, viewing the land as empty and open to settlement, their encounters with Indigenous people were also shaped by perceptions of indigeneity rooted in Japanese history and culture.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".