<i>Alien Nation: Chinese Migration in the Americas from the Coolie Era through World War II</i>. By Elliott Young.
Bibliographic record
Abstract
This is a fruitfully ambitious attempt to understand Chinese migration to important destinations in the United States, Canada, Mexico, Peru, and Cuba in the late nineteenth and early twentieth centuries. Its remarkably extensive scope represents a pathbreaking contribution, as an international perspective helps readers understand the varied experiences of Chinese immigrants in different countries. For example, while the Chinese became victims of nationalistic xenophobia in Mexico, their compatriots’ disproportionate participation in the wars of independence “helped to mitigate the most virulent expressions of racism” in Cuba (p. 13). But this book is not merely a traditional comparative study. Rather, it constitutes a most successful effort to create a coherent transnational framework through which to comprehend Chinese migrations to different destinations in the Americas as interrelated events related to, and shaped by, other historical forces, such as ideas about race, labor systems, and nationalism. Author Elliott Young’s theoretical insights are solidly grounded in extraordinarily rich archival sources in Britain, Canada, Cuba, Mexico, Peru, Spain, and the United States.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".