De l’auto ségrégation à l’effacement du particularisme communautaire : le cas des Cantonais de Manille. (Philippines)
Bibliographic record
Abstract
Résumé: La communauté chinoise aux Philippines est évaluée entre 800 000 et un million d’individus. La moitié de ce groupe réside dans la région de Manille, la capitale du pays. Plus de 90% des Chinois ont leurs racines dans la province littorale du Fujian, les autres sont originaires de la région de Guanzhou (Canton). Arrivés plus tardivement aux Philippines, les Cantonais ont développé des formes d’intégration spécifiques tant au niveau spatial, professionnel et associatif ; lesquelles sont aussi une réponse au flux migratoire réduit puis à son extinction. L’émigration vers l’Amérique du nord pour les Cantonais a constitué une solution pour pallier sa faible intégration économique dans la capitale philippine. La communauté cantonaise de Manille représente un cas d’étude original à l’heure où les flux de populations chinoises sont de plus en plus importants dans le monde. Mots clés :Chinois, Cantonais, Manille, Philippines, Canada, marquage visuel, repli communautaire Abstract:The Chinese community settled in the Philippines members are between 800 000 to one million. Half of it stays in Manila and its region. More than 90 % of the Chinese has their roots in the coastal province of Fujian, the others are from Guangzhou area (Canton). Cantonese migrated lately to the Philippines and developed proper integration ways, spatially, professionally, mostly through a tight association network. Those associations correspond to a light migration wave and to its nowadays extinction. Migrate to North America for a Cantonese person is an opportunity to avoid a lack of economical integration in the capital city of the Philippines. The Manila Cantonese community represents an original case study at a time of massive waves of Chinese populations around the world. Key Words:Chinese, Cantonese, Manila, Philippines, Canada, visual aspects, community fold (self withdrawal)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".