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Anthony Blunt and Nicolas Poussin: A Queer Approach

2011· dissertation· en· W17864172 on OpenAlexfundno aff
Luke Andrew Nicholson

Bibliographic record

VenueAnnals of Surgery · 2011
Typedissertation
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaConcordia University
KeywordsQueerArtScholarshipPaintingBluntArt historyQueer theoryLiteratureSociologyGender studiesLawPolitical science

Abstract

fetched live from OpenAlex

The art historian Anthony Blunt (1907-1983), a homosexual and famously a Soviet spy, was a leading authority on the French painter Nicolas Poussin (1594-1665). In recent years, several scholars have noticed strange affinities between these two figures, affinities that relate to their ideas, to a common interest in secrecy and in covert knowledge, as well as to less definite attitudes that these scholars have had difficulty pinning down. This thesis proposes that these strange affinities may be explained by means of Queer Theory, which has afforded art historical scholarship a language and sets of concepts that allow the more difficult aspects of Blunt’s relationship to Poussin to be carefully anatomized. I argue that Blunt may have found in Poussin’s complex and ambiguous pictorial worlds both an inspiration for and a reflection of his multiple, contradictory identities and commitments. Meanwhile, I investigate what properties in Poussin’s art make possible this relationship, exploring how a kernel of homoerotic sensibility, entering Poussin’s oeuvre from the Arcadian pastoral tradition grows and diversifies to depict what I call queer bodies and to construct what I call queer spaces. Blunt’s art historical account of Poussin, the most influential account of the painter in the twentieth century, turns out to be but one facet of a deep and mutually-constitutive encounter between artist and art historian.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.593
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.285
GPT teacher head0.297
Teacher spread0.012 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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