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Record W2481412741 · doi:10.1075/clu.10.10fel

The flavors of multi-ethnic North American literatures

2013· book-chapter· en· W2481412741 on OpenAlexaboutno aff
Astrid M. Fellner

Bibliographic record

VenueCulture and language use · 2013
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupPsychologyGeographySociologyAnthropology

Abstract

fetched live from OpenAlex

This paper analyzes culinary remembrances by Asian Canadian, Latina, and Caribbean writers, investigating the multivalent meaning of food in literary texts. In ethnic literature, food figures as a powerful symbol of ethnicity, becoming a significant site where identity construction, community building and social critique can take place. Descriptions of culinary practices set in motion thoughts on belonging and national identity, offering affective encounters with the past. Culinary nostalgia, this paper argues, allows ethnic subjects to identify as ethnic via their relationship to food, opening up ways of engaging the politics of identity. Using a language through which to imagine alterity, these narratives provide a space for reflections on the complex interplay of “here” and “there,” of “home” and “away.”

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.009
Science and technology studies0.0230.022
Scholarly communication0.0120.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.231
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2013
Admission routes1
Has abstractyes

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