The Economic Practices of Chinese Immigrant Entrepreneurs: The Cases of Paris, Brussels, and Montreal
Bibliographic record
Abstract
This article explores the economic ties established by ethnic Chinese immigrant entrepreneurs. It is based on a qualitative analysis of sixty interviews. The interviewees are Chinese individuals from various countries (People's Republic of China, Taiwan, Vietnam, Laos, Cambodia, Thailand, Indonesia, and Madagascar) who have established themselves in the cities of Paris, Brussels, and Montreal. The empirical data presented here indicate that this phenomenon is complex and context-dependent, and that the practices of economic exchanges between businesses are diverse. The paper examines the ethnic aspects of these practices, based on the characteristics of the business owner and the city, as well as their evolution over time. The research stresses the importance of the generational factor in business practices and the increasing role of international trade, particularly toward China. As a corollary, local exchanges between immigrant Chinese companies are weakening. Far from the stereotype of immutability that has sometimes been attributed to them, the Chinese immigrant entrepreneurs demonstrate adaptation to local, national, and transnational contexts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".