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Record W2165192679 · doi:10.5539/ach.v5n2p115

Eating, Starving and the Body: The Presentation of Self

2013· article· en· W2165192679 on OpenAlexvenueno aff
Roya Nikandam

Bibliographic record

VenueAsian Culture and History · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
Fundersnot available
KeywordsAlienationEating disordersSubject (documents)SociologyPsychoanalysisConsumption (sociology)PsychologySelfGender studiesSocial psychologyAestheticsSocial scienceLawArtPolitical scienceClinical psychology

Abstract

fetched live from OpenAlex

This study examines the subtle and complex importance of food and eating in contemporary female fiction. It reveals how the chief concern with food, its consumption and the body are central to the work of writer like Margaret Atwood. Two novels in particular, Cat’s Eye (1988) and Alias Grace (1996) will be considered as they feature female protagonists who experience intense conflicts concerning their bodies, conflicts that result in or are a response to violence. This violence takes the form of eating disorders. They highlight this form of bodily violence which supports their on going critique of dualistic thinking. In their fictions, Atwood shows the artificial bifurcation of human existence into body and self which tends to result in self-alienation or the splitting of the subject. This writer draws on feminist and sociological theory to engage with a diverse range of issues, including eating disorders as a form of self-violence or mutilation, to demonstrate the direct relationship of food and eating or not-eating with gender and cultural politics to manifest the role of using food in assumed association of the womanly body which leads to splitting of the subject.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.301

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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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