Bibliographic record
Abstract
This work traces several generations of Chinese “brokers,” ethnic leaders who acted as intermediaries between the Chinese and Anglo worlds of Canada. At the time, most Chinese could not vote and many were illegal immigrants, so brokers played informal but necessary roles as representatives to the larger society. Brokers’ work reveals the changing boundaries between Chinese and Anglo worlds and how tensions among Chinese shaped them. By reinserting Chinese back into mainstream politics, this book alters common understandings of how legally “alien” groups helped create modern immigrant nations. Over several generations, brokers deeply embedded Chinese immigrants in the larger Canadian, U.S., and Chinese politics of their time. On the nineteenth-century Western frontier, Chinese businessmen competed with each other to represent their community. By the early 1920s, a new generation of brokers based in social movements challenged traditional brokers, shifting the power dynamic within the Chinese community. During the Second World War, social movements helped reconfigure both brokerage and race relations. Based on new Chinese language evidence, this book recounts history from the “middle,” a view that is neither bottom up nor top down. Through brokerage, Chinese wielded considerable influence, navigating a period of anti-Asian sentiment and exclusion throughout society. Consequently, Chinese immigrants became significant players in race relations, influencing policies that affected all Canadians and Americans.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".