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Record W2944388281 · doi:10.1163/26659077-00802006

Food, Emotion and the Empowerment of Women in Contemporary Fiction by Women Writers

2005· article· en· W2944388281 on OpenAlexaff
Surapeepan Chatraporn

Bibliographic record

VenueManusya Journal of Humanities · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSustenanceSoulTheme (computing)EmpowermentFeelingAestheticsCreativityExpression (computer science)PsychologyPower (physics)SociologyGender studiesSocial psychologyArtPolitical science

Abstract

fetched live from OpenAlex

This paper aims to explore the connection between food and emotions and analyze how food empowers the women who cook and serve it. In the selected fictional bestsellers, which were made into successful films, food plays a vital role. Food functions as the title, the main theme, the dominant imagery, and distinctive figures of speech. Food has a direct impact on the emotions and behavior of those who consume the food prepared by these female cooks. Their food provides physical nourishment as well as emotional and spiritual sustenance. Food is used as a vehicle to communicate feelings, and an outlet for female creativity and artistic expression. The female cooks, who appear initially weak and inferior in status, grow to be influential and indispensable. Having derived their power from food, these female cooks eventually assume the roles of artistic chefs and, more importantly, saviors of body and soul.

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 score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.008
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.026
GPT teacher head0.205
Teacher spread0.179 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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