Pratique du commerce et rapports dâethnicité en situation dâimmigration : le cas des Chinois de Paris, Bruxelles et Montréal
Bibliographic record
Abstract
Chinese immigrants are known to have been extensively involved in ethnic commerce and have been studied by many authors in several diasporic poles. \nBased on Barth and Juteau’s theories of ethnicity, on multi-factor theories of ethnic commerce, such as Waldinger's interactive model, as well as social capital theories initiated by Bourdieu, this dissertation develops a comparative analysis of the phenomenon of ethnic commerce in the cities of Paris, Brussels and Montreal.\nThe analysis includes an historical overview and a field study, based on sixty interviews held in the three cities. The latter bore on migratory and entrepreneurial trajectories as well as on the interviewees' perception of intra- and inter-group relationships. \nThe results of this analysis show the need for a multi-factor model to comprehend this phenomenon in its full complexity and that the social player instrumentalises cultural elements for trade purposes and as part of their ethnic strategy. Another conclusion is the importance of a contextual and comparative perspective. In other words, it is necessary to approach ethnicity and its manifestations within the frameworks of constructivism, interactionism and conflictualism, with, in an actionalist perspective, ethnic commerce as an attempt of social players to take their own destiny into their own hands, within a sometimes unfavourable structure, by using their own resources, including ethnic ones.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".