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Record W4297341495 · doi:10.1215/02705346-9787056

“All Your Faves Are Problematic”: The Performative Spectatorship of Drunk Feminist Films

2022· article· en· W4297341495 on OpenAlexaboutno aff
Shana MacDonald

Bibliographic record

VenueCamera Obscura Feminism Culture and Media Studies · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerformative utteranceMainstreamNarrativeHollywoodMedia studiesCraftPleasureSociologyMythologyAestheticsVisual artsArtPolitical sciencePsychologyLiteratureArt history

Abstract

fetched live from OpenAlex

Abstract This article looks at the work of the Drunk Feminist Film (DFF) collective from Toronto, Canada. DFF screenings offer interactive in-person and online events that combine watching popular Hollywood films with simultaneous live commentary, audience participation, and hashtag dialogs on Twitter. The article looks specifically at how the multiplatform hybridity of online and embodied participation allows feminist audiences to create collective spectatorial communities. DFF events emphasize paratextual conversation and reimagine how we can relate to movie narratives in the twenty-first century. By looking at a specific screening of The Craft (dir. Andrew Fleming, US, 1996), this article illustrates how DFF indexes the potential of engaging mainstream films while also engaging in feminist conversations about them. Problematic narrative aspects are discussed in real time by a community and are recorded via Twitter, resulting in digitally archived debates about how audiences collaboratively reinvent difficult but popular myths within their favorite films. As a result, the collective decenters mainstream films in favor of paratextual ephemera that negotiate the audience's pleasure in and critique of their favorite films.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.067
GPT teacher head0.266
Teacher spread0.199 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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