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Record W4212928096 · doi:10.1080/21604851.2022.2037309

Feeling ‘Pretty Porky & Pissed Off’: a photo essay on fatness, affect, art, and archives

2022· article· en· W4212928096 on OpenAlexaffabout
Allison Taylor, Allyson Mitchell

Bibliographic record

VenueFat Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsWomen's and Gender Studies et Recherches FéministesYork University
Fundersnot available
KeywordsFeelingScholarshipVisual artsQueerSociologyArchivistNarrativeAestheticsArtMedia studiesPsychologyHistoryLiteratureGender studiesSocial psychology

Abstract

fetched live from OpenAlex

This photo essay is about the process of creating a digital archive dedicated to Pretty Porky and Pissed Off, a Toronto-based fat activist and performance art collective active in the late 1990s and early 2000s. As a leading member of the collective and the project’s principal investigator (Allyson Mitchell) and the project’s researcher archivist (Allison Taylor) we explore the affective potential of the visual archival fat representations produced through Pretty Porky and Pissed Off’s artistic practice. We first provide an overview of the Pretty Porky and Pissed Off archive project. Second, we contextualize our photo essay within queer and fat studies scholarship on affect, archives, and the visual. Third, we present a set of stills from archival video footage of a Pretty Porky and Pissed Off clothing swap in Allyson Mitchell’s art studio. Using these stills, we consider the affectively rich nature of visual archival representations of fatness. We suggest that feelings are a central component of visual archival fat representations; feelings offer important insights about the potential of visual artistic and archival practices to represent, embody, and imagine fatness otherwise.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.517
GPT teacher head0.600
Teacher spread0.083 · 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 designNot applicable
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
Published2022
Admission routes2
Has abstractyes

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