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Record W3205163757 · doi:10.47611/jsr.v10i3.1341

Can the Neoliberal Subject Condemn [Him]self?: Locating Masculinity at FOX News in Bombshell

2021· article· en· W3205163757 on OpenAlexaff
Hui Wong, Brent Strang

Bibliographic record

VenueJournal of Student Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMasculinityEgalitarianismFraming (construction)Gender studiesSociologyNews mediaMainstreamMoralityMedia studiesPolitical sciencePoliticsLawHistory

Abstract

fetched live from OpenAlex

Director Jay Roach’s 2019 film Bombshell draws on a series of real-life sexual allegations against FOX News founder Roger Ailes, depicting the climate in the newsroom and portraying a number of FOX personalities. As a film marketed for mass audiences, it is crucial to question the extent to which the film successfully serves to critique sexism in the FOX News newsroom. The purpose of this paper is thus to examine the portrayal of masculinity and sexism and FOX News in Bombshell. To explore the dynamic of this newsroom, this paper centers on interrogating Bombshell against the notion of a “feminist film”. I first attempt to analyze and locate gendered dynamics within Bombshell, then reflect on portrayed gendered dynamics with reference to the history of FOX News and the way competing masculinities work in the news organization. The FOX News newsroom is unique in the ways varying dynamics of gender manifest within its locale: in front of the camera, a kind of neoconservative “traditionalist” morality and gender order; behind the camera, an “amoral” gender dynamic that aligns with neoliberal free-market principles. I then explore how a gender order is upheld in contradiction, often by the very subjects who are subjected under a masculine-dominant gender order. I question the possibility of any future of gender egalitarianism at FOX News, and conclude by arguing that Bombshell misses the mark in interrogating a gender order, instead problematically framing sexism as chiefly upheld by individuals.

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)0.007
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.197
GPT teacher head0.465
Teacher spread0.268 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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