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Record W2102160686 · doi:10.4000/ideas.406

Eating à la Criolla : Global and Local Foods in Argentina, Cuba, and Mexico

2012· article· en· W2102160686 on OpenAlexaff
Jeffrey M. Pilcher

Bibliographic record

VenueIdeAs · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
FundersUniversity of CambridgeSecretaría de Educación PúblicaHarvard UniversityYale University
KeywordsPolitical science

Abstract

fetched live from OpenAlex

This essay examines the changing meanings of local and global foods in Argentina, Cuba, and Mexico. Nineteenth-century Latin America is often viewed as a period of liberal ascendancy when imported goods were highly valued, while on the contrary, the twentieth century is seen as a time of populist nationalism that embraced local culture and, at least until the neoliberal era, rejected European and North American imports. Nevertheless, liberals sought to balance their international sophistication with a patriotic affection for the local, while revolutionary middle classes aspired to their own versions of cosmopolitanism. These changing meanings become particularly evident through an examination of the divergent usages of the term “criollo” to refer to local foods. The paper argues that national cuisines emerged throughout Latin America not from the rejection of the global in favor of the local but rather through a blending of the two in a culinary sensibility that combined patriotism and cosmopolitanism in pursuit of social distinction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.240
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2012
Admission routes1
Has abstractyes

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