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Record W3100735647 · doi:10.18146/tmg.588

Queering New Cinema History: Affective Methodologies for Comparative History

2020· article· en· W3100735647 on OpenAlexaff
Jonathan Petrychyn

Bibliographic record

VenueTMG Journal for Media History · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMovie theaterHollywoodEphemeraQueerMainstreamScholarshipAestheticsFilm studiesExhibitionSociologyQueer theoryArtVisual artsMedia studiesGender studiesArt historyPolitical science

Abstract

fetched live from OpenAlex

New Cinema History has tended to focus on developing microhistories of the exhibition, distribution, and reception of theatrical Hollywood and other mainstream cinemas. While such scholarship has been essential for understanding how cinema operates as a sociocultural institution, its focus on the highly public forms of cinemagoing that often followed Hollywood film has left untouched the sometimes furtive and deliberately hidden cinemagoing practices and microhistories of queer audiences, curators, and exhibitors throughout the mid-to-late 20th century. This paper intervenes in this state of affairs and queers New Cinema History. I situate film festival studies and New Cinema History within the same methodological and theoretical terrain and argue that the exclusion of queer film festivals from New Cinema History is a result of both the field’s methodological preference for big data, as well as a structural heteronormativity underlying its methodologies. I further argue that by following affect, ephemera, and anecdotes, New Cinema History can better account for queer and other marginalised cinema practices.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.713
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.395
GPT teacher head0.316
Teacher spread0.079 · 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
GenreReview

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

Citations8
Published2020
Admission routes1
Has abstractyes

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