Bibliographic record
Abstract
While food is capable of mediating between different cultures, opening kitchen systems to all sort of inventions, crosses and contaminations, it is also the space for domestication and adaptation. This has become particularly evident in contemporary glocalised foodscapes, where migratory flows, travels and the development of media systems have made the processes of translation across different food cultures increasingly evident and consistent, affecting (much faster than in the past) the existing culinary “traditions” and becoming part of them. The distinction between the global and the local dimension has thus progressively blurred, making established meanings and identities no longer clearly defined, but rather expressed through several and multiple interpretations. It is therefore essential to understand the semiotic processes underlying such interpretations, and the way they contribute to the definition of contemporary food meanings and identities. This paper deals with these crucial questions by focusing on some relevant case studies related to the Peruvian foodsphere, whose recent development and success on a global scale has been promoted precisely by means of an emphasised process of glocalisation operated by local food services and haute-cuisine chefs that have become famous worldwide.
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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 | 0.001 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.001 | 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".