Bibliographic record
Abstract
This article juxtaposes the history of Japanese immigrants in Canada—which parallels that of Japanese immigrants to the United States in significant ways—with that of Canada’s Indigenous people, who were also marginalized, to explore larger issues related to the way in which history is deployed in court actions. Although it uses a Canadian case—the 2008 decision of Canada’s Supreme Court in R. v. Kapp (which upheld an exclusive 24-hour communal sales fishery established on behalf of three First Nations)—to frame this discussion, the questions raised are relevant on both sides of the U.S.-Canada border. The article speaks, for example, to ways in which efforts to meet the elements of a given legal test can lead to the distortion of historical evidence, also a danger for U.S. courts. In reviewing the historical arguments made by the Japanese Canadian Fishermen’s Association in R. v. Kapp, which invoked two earlier cases from the 1920s in which Japanese immigrants challenged their exclusion from Canadian fisheries on race-based grounds, the article also provides a summary of that history of exclusion. It highlights the importance of reading immigration and Indigenous histories together in order to develop a more comprehensive understanding of the complex ways in which racialized groups have negotiated racial divides. These negotiations produced a far more intricate set of alignments and divisions among and within various racialized groups than is often recognized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.021 | 0.076 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".