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Record W2086067136 · doi:10.1080/15240657.2014.911054

Discarded Histories and Queer Affects in Anne Carson’s<i>Autobiography of Red</i>

2014· article· en· W2086067136 on OpenAlexaff
Dina Georgis

Bibliographic record

VenueStudies in Gender and Sexuality · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQueerBiographyMonsterContext (archaeology)SubjectivityWitnessMythologyLiteratureIdentity (music)VampireHistoryArtArt historySociologyAestheticsPhilosophyGender studies

Abstract

fetched live from OpenAlex

This article takes up Anne Carson’s Autobiography of Red (1998) as an allegory for the discarded history of queerness. The novel in verse rewrites the Greek myth of Herakles (Hercules) and the red-winged monster Geryon as a queer love story. In Carson’s rendition, Herakles is not a colonizer who murders Geryon to seize his red cattle but a lover who steals and breaks his fragile heart. Born hybrid in a modern-day context, Geryon struggles with narrating his life in words and instead takes pictures.By asking us to pay attention to history’s queer affective traces, Carson invites us to think about how bodies become discarded social monsters and how monsters must learn to live in their bodies. She turns our attention to the traumas and their affects that render the activities of subjectivity unpredictable and undecipherable. In Autobiography of Red, “queer” is not simply sexual orientation but the abject perversions of difference, not easily nameable. Without the familiar registers of identity, we are invited to witness and to be touched by Geryon’s life through his photo-autobiography, which captures the affect of experience, otherwise lost to the foreclosures of time.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.064
GPT teacher head0.284
Teacher spread0.219 · 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 designObservational
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

Citations4
Published2014
Admission routes1
Has abstractyes

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