MétaCan
Menu
Back to cohort

Cuisines of Diaspora: Expressions of Iranian Foodways & Culinary Traditions

2022· article· en· W4285127445 on OpenAlexaffabout
Nazmi Kamal, Marian Chung

Bibliographic record

VenueGastronomy and Tourism · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsCapilano University
Fundersnot available
KeywordsFoodwaysDiasporaQualitative researchPopularityEntertainmentDanceStatus quoPromotion (chess)SociologyRepresentation (politics)GeographySocial scienceAnthropologyGender studiesPolitical sciencePsychologyArtSocial psychologyVisual arts

Abstract

fetched live from OpenAlex

The project "Cuisines of Diaspora" was a community-based research inquiry that aimed to expose the status quo of Iranian culinary culture within the decades-strong Iranian diaspora in the North Shore area of Vancouver, BC, Canada. Using a qualitative and interpretive approach with a case study methodology, the research employed multiple tools using semistructured interviews, market observations, photovoice samples, and city archives, as well as other interactions with community members and stakeholders. Nineteen interview responses were obtained alongside a magnitude of data through secondary research findings. The findings suggest a lack of regional Iranian cuisine representation in the North Shore and a thirst for a more diverse offering that reflect the various Iranian provinces. Furthermore, the findings illustrate the growth in dining entertainment options including artistic cultural representations through song, dance, and other art forms. Other findings suggest a strong sense of gastrodiplomacy by the Iranian community, which supports advocacy and promotion of Iranian cuisine. Finally, there is an appetite for more community events that highlight Iranian culture and cuisine and a potential for preserving food culture through community partnerships and sustainable sourcing of food ingredients.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score1.000

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)0.0010.000

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 head0.023
GPT teacher head0.207
Teacher spread0.184 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueGastronomy and TourismSame topicCulinary Culture and TourismFrench-language works237,207