Where Is Home? The Current State of Chinese Migration Studies
Bibliographic record
Abstract
Gregor Benton and Hong Liu. "Dear China: Emigrant Letters and Remittances, 1820-1980." Oakland, CA: University of California Press, 2018. 288 pp. \n \nElaine Lynn-Ee Ho. "Citizens in Motion: Emigration, Immigration, and Re-migration across China's Borders." Redwood City, CA: Stanford University Press, 2018. 184 pp. \n \nWang Gungwu. "Home Is Not Here." Singapore: National University of Singapore Press, 2018. 216 pp. \n \nThe field of Chinese migration studies is thriving, as demonstrated by three recent publications by highly accomplished senior scholars, including pioneering historian Wang Gungwu, sociologist Elaine Lynn-Ee Ho, and historians Gregor Benton and Hong Liu. Together, this trio of books significantly develops the fields of migration and Chinese overseas studies, and each articulates key aspects of these interlocking fields in a distinctive way. Ho’s short monograph draws on ethnographic studies of contemporary Chinese immigrants in Canada, Singapore, and returnees to China to frame conceptual terms that enable scholars to acknowledge, categorize, and analyze complex layers of migrant experiences. These migrants participate in multiple diasporas and encounter varied practices of ethnic inclusion, exclusion, and institutional and ideological conceptions of citizenship. Benton and Liu provide a sweeping survey of qiaopi (remittance letters) as tensile, nongovernmental systems through which Chinese migration networks and societies circulated the finances that motivated so much of their mobility. These authors take a three-pronged approach, which makes available in English an overview of the extensive Chinese-language scholarship on qiaopi, descriptions of extant archival holdings of the documents, and authoritative analysis of the implications of this subfield. Wang’s volume takes an entirely different approach as a memoir depicting the first two decades of the life of the scholar who established the field of Chinese overseas studies.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.023 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".