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Record W7046344288

Demonstrating Feminist Metic Intelligence Through the Embodied Rhetorical Practices of Julia Child

2018· article· en· W7046344288 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Media Literacy Education · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsMetisRhetorical questionEmbodied cognitionRhetoricCreativity
DOInot available

Abstract

fetched live from OpenAlex

The concept of metis reinserts the body and its intelligences into the ways in which rhetoric is understood, harnessed, and performed. Originating from the wisdom of Greek goddess Metis, the concept of metis is commonly understood as cunning intelligence that is deployed in order to escape an adversary, trick an opponent, or dupe its victim. When metic intelligence is read through the helping acts of Metis and her daughter, goddess Athena, however, an expanded version of its ways of operating begins to emerge. Through her efforts to debunk French cuisine using rule-based approaches meant to empower home chefs in their own kitchens, Julia Child, cookbook author, television educator, and chef, embodies metis with practices that represent feminist metic intelligence. In archival collections that reveal prolific correspondence, manuscript drafts, and television production material, Child deploys rhetorical strategies meant to teach and stimulate physical movements of cooking, and she does so by positioning the rules of cuisine as the gateway to culinary agency. For Child, structured rules allowed a home chef to respond to and recover from mistakes, and the rules also, consequently, fostered creativity and culinary freedom in the kitchen. Child’s own wielding of cunning and embodied intelligence helps us understand how metis is cultivated by a rhetorical body, and, in turn, Child’s metis may allow us to better understand how embodied rhetorics are invented and deployed.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0120.000

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 head0.034
GPT teacher head0.386
Teacher spread0.352 · 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 designOther design
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
Published2018
Admission routes1
Has abstractyes

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