Elliott Young.<i>Alien Nation: Chinese Migration in the Americas from the Coolie Era through World War II</i>.
Bibliographic record
Abstract
Elliott Young’s agenda in Alien Nation: Chinese Migration in the Americas from the Coolie Era through World War II is commendably ambitious. He seeks to offer a transnational understanding of one hundred years of Chinese immigration to the Western Hemisphere, especially the U.S., Canada, Mexico, Cuba, and Peru; to illuminate transnational smuggling networks and migration routes; to explain the simultaneous and linked rise of the “illegal alien” and the nation-state; and to give voice to Chinese migrants and the communities they created under incredible pressure across North and South America. The book does not succeed in achieving all these goals, for it ultimately proves more adept at describing government responses to Chinese migration than at exploring the lives of the migrants themselves. However, Young’s study does provide a fascinating new window into the mechanics of immigration control across the Americas. Alien Nation begins in the mid-nineteenth century, when Chinese laborers from the stumbling Qing dynasty began to stream from the ports of Hong Kong and Macao into Cuba, Peru, the U.S., and other parts of the Western Hemisphere. Often reviled as “coolies,” they and the conditions in which they traveled, worked, and contracted their services prompted considerable consternation across the Americas. Officials and other participants in ongoing and increasingly bitter international debates about slavery used the Chinese migrants as examples of both free labor and slavery and fought over the need to reform the “coolie trade.” With the late-nineteenth-century decline of slavery in the Western Hemisphere, the debate shifted somewhat; government authorities in China, the U.S., Britain, Spain, Mexico, Peru, Cuba, and Canada began to argue heatedly about whether Chinese “coolie” labor was in fact a continuation of slavery or a symbol of free labor. Meanwhile, the potent anti-Chinese movement that emerged in the post–Civil War U.S. shaped immigration law there and compelled lawmakers to press other countries to cooperate with America’s exclusionist priorities. By the early twentieth century, Canada and Mexico both complied, particularly because anti-Chinese sentiment was rising within their own nations; still, corruption and long borders also meant continued Chinese immigration into the U.S. from the two countries and from Cuba. Simultaneously, the growth of anti-Chinese sentiment across the Western Hemisphere affected how Chinese migrants throughout the region organized politically and socially in the period between 1900 and the 1930s. The book concludes by linking the plight of the pre–World War II Chinese to current migrant waves.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".