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Record W4386584026 · doi:10.18357/tar141202321371

"We are very proud and very tempted and determined to make this food"

2023· article· en· W4386584026 on OpenAlexaffvenue
Saraf Nawar Rodyna

Bibliographic record

VenueThe Arbutus Review · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFoodwaysCultural identityIdentity (music)SociologyImmigrationFeelingSocial psychologyPsychologyAestheticsPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Food plays a critical role in an individual’s maintenance of cultural identity and social connection. The process of preparing, sharing, and consuming cultural food (i.e., cultural foodways) serves to connect immigrants to their families, communities, and cultures—especially when experiencing a new way of living in an unfamiliar environment. Limited access to cultural food resources can contribute to feelings of isolation or a loss of culture; therefore, continual engagement in cultural food practices is crucial for migrants to maintain their identity and well-being. This study explores the relationship between cultural foodways, identity maintenance, and well-being among immigrant Muslim women. Through semi-structured interviews conducted with two immigrant Muslim women and through personal self-reflection, the intersections between gender, religion, and culture reveal the complexity of immigrant lives in relation to food. Participants describe their experiences navigating cultural food accessibility and identify how cultural food practices, especially the sharing of cultural food, affirm their cultural identity and contribute to their well-being. By engaging in cultural foodways, the participants situate their identities in the present, connect to their cultural histories, and imagine opportunities for the continued transfer of food knowledge.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

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

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 head0.047
GPT teacher head0.253
Teacher spread0.207 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2023
Admission routes2
Has abstractyes

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