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Record W2026593364 · doi:10.1386/eta.4.3.315_1

The art of embodiment: auto-ethnographic portraits of two women's surgical traumas

2008· article· en· W2026593364 on OpenAlexaff
Cynthia M. Morawski, Stephanie Irwin

Bibliographic record

VenueInternational Journal of Education through Art · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsExpression (computer science)Intrapersonal communicationEthnographyPortraitFace (sociological concept)Visual artsAestheticsMeaning (existential)Palette (painting)ConsciousnessArtBiographyExperiential learningPsychologySociologyLiteraturePedagogySocial psychologyInterpersonal communicationAnthropologyPsychotherapistComputer scienceSocial science

Abstract

fetched live from OpenAlex

Two educational researchers heed the responsibility to face their own traumatic pasts in working with women's experiential texts in the present. Using the notion of individual as both artist and image illustrated in the art of body biography, they come together to embody their own intrapersonal stories of gynaecological and obstetrical traumas as auto-ethnographic texts. Using a palette of photographs, found objects, ink, fabric and more, they portray their past on the present canvas of life-size paper placed across the office floor. Pin pricks on the abdomen. The next slice and stitch. Laproscopic cameras. The leg that lurched and twitched. With each expression of meaning, they delve into multiple layers of consciousness, connecting their recurring past to intrapersonal possibilities of women's education in the present. The art of embodiment plays a leading role.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.015
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0150.020
Scholarly communication0.0070.007
Open science0.0020.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.307
Teacher spread0.275 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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