O Chá Gordo Macaense: Análise histórica das narrativas sobre a sua origem
Bibliographic record
Abstract
There are many similarities between the Macanese Chá Gordo and European and Oriental banquets. European banquets that many associate with the ancient Greeks and Romans, Italian antipasto whose origin is attributed to Marco Polo who brought it from China, Portuguese acepipes linked to the Arabic Az-zibib and the Chinese Yam chá are according to some, are the basis for the designation Chá Gordo and the dishes that make up this special meal in Macanese cuisine. The eating habits and customs of the Japanese Christians who sought safe haven in Macau in the aftermath of Shogun Tokugawa’s expulsion Edit of 1614 greatly influenced the Macanese cuisine. The more recent reflections associate Chá Gordo which is served in the afternoon, with the traditional English High Tea. The variety of dishes of the Chá Gordo is given as the reason why it was developed in the nineteenth and twentieth century in the homes of affluent Macanese families. Most if not all of these narratives are speculative, probably based on oral tradition. In this paper we will explore a different line of thought taking account of historical facts from maritime history characterized by tragedy, resilience and religious devotion that over time became features of Macanese identity and the basis of the origin and custom of the Macanese Chá Gordo. Keywords: Chá Gordo; Macanese; Japanese food and eating habits; Macanese gastronomy; Identity
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".