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Record W3137649894 · doi:10.32920/cd.v5i2.1414

The Queen of Hearts: Exploring the process of creating queer art and its use in dietetic research and practice

2021· article· en· W3137649894 on OpenAlexaffvenue
Phillip Joy, James Iain Neith

Bibliographic record

VenueJournal of Critical Dietetics · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsQueerSet (abstract data type)PsychologyAestheticsSociologyVisual artsGender studiesArtComputer science

Abstract

fetched live from OpenAlex

Body image issues for gay men can shape their overall health and wellbeing. The intent of this article is to explore the personal and creative process in translating research findings to art. The article first presents a brief overview of the research that explored how social and cultural norms constitute the beliefs, values, and practices of gay men concerning their eating, body image, and health. The research findings are translated through an art piece that is disruptive to the dominant ways of knowing about the body ideals set before gay men. An art piece that is, therefore, by definition queer art. The findings, and hence, the art are interpreted through the classic tale of Alice in Wonderland - a poststructural piece of literature. The article describes the considerations and processes used to create the art, including the central character, the colors, and the the symbolism of its various components. Implications of queer art to dietetic practice are discussed.

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)0.044
metaresearch head score (Gemma)0.035
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: none
Teacher disagreement score0.044
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0300.120
Scholarly communication0.0250.014
Open science0.0020.015
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.175
GPT teacher head0.387
Teacher spread0.212 · 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
Published2021
Admission routes2
Has abstractyes

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