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Candida, Food Discipline and the Dietary Taming of Uncertainty

2013· article· en· W2010654700 on OpenAlexaff
Alissa Overend

Bibliographic record

VenueFood Culture & Society · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsMacEwan University
Fundersnot available
KeywordsDietingAmbiguityDisciplineCertaintyNarrativeSociology of health and illnessSocial psychologyPsychologySociologyHealth careMedicineEpistemologySocial sciencePolitical science

Abstract

fetched live from OpenAlex

Discourses of nutritional health are strongly associated with illness, and have recently been linked to the prevalence and management of chronic undefined disorders. Using the case of Candida—a yeast-related disorder of vague symptomatology—I explore the role of food in the narratives of twenty-four people living with Candida. As Candida remains a speculative illness within the boundaries of biomedical science, it is relevant to critically explore the often-focal role of food in the management of this condition, and to consider the range of personal, social and cultural motivations at work in its dietary regulation. Taking up Foucault's theory of docility, I trace the ways in which dietary practices can be understood as normalizing the Candidad-body by helping to create a sense of certainty and control in the persistent face of illness ambiguity. In drawing on Foucault's later work, I move beyond illness dieting as solely a disciplinary regime and explore the ways in which dietary regime can also be conceptualized as a practice in the care of the self, fostering a heightened, often-changing sense of self. While Candida dieting practices will never fully operate separate from the pervasive discourses of nutritional science, they can offer productive possibilities in the regulation and maintenance of an illness not fully recognized by biomedical science.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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