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Record W2055831162 · doi:10.1080/14427591.2011.586326

Occupational Meanings of Food Preparation for Goan Canadian Women

2011· article· en· W2055831162 on OpenAlexaffabout
Brenda L. Beagan, Andrea D’Sylva

Bibliographic record

VenueJournal of Occupational Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEthnic groupHomelandDiasporaPortugueseSociologyContext (archaeology)Gender studiesGeographyAnthropologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Food-related occupations connect people with bodies, traditions, rituals, community, family, and caring. Food holds sensate memories and may vividly evoke the past. For those who live in a diaspora, sharing an ethnic heritage yet displaced from a homeland, food may comprise a major means of cultural transmission. This qualitative study explores the meanings of food and food-related occupations for 13 Goan women in Toronto, Canada. Catholic Goans, an ethnic group borne of Portuguese colonization of an area in what is now Western India, have few unique markers of ethnic distinction from other Indians. In this context, Goan cuisine becomes a powerful boundary marker, and food-related occupations carry a particular salience in cultural maintenance. Skill in culinary occupations may then be experienced as a form of power or ‘currency’ for women, because they are able to produce a highly significant symbol of culture.

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)0.001
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0290.013
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.064
GPT teacher head0.284
Teacher spread0.220 · 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

Citations24
Published2011
Admission routes2
Has abstractyes

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