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Record W4244983871 · doi:10.24908/iqurcp.8802

12. Deconstructing Dad: Satire and Hegemonic Masculinity in Mainstream Television

2016· article· en· W4244983871 on OpenAlexvenueno aff
Laura G. Ritenburg

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsHegemonic masculinityMasculinityMainstreamNormativeHegemonyIdentity (music)SociologyPower (physics)Subordination (linguistics)Gender studiesSocial psychologyPsychologyAestheticsArtPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

What’s sarcastic, droll, brightly coloured, watched by millions and enforces a hegemonic masculine identity? No, not a sports centre update. Family Guy and American Dad!, along with other mainstream popular television shows, feeds into extreme notions of masculinity by depicting humorous macho images that emulate physical strength, aggressiveness, willingness to use violence, and the subordination of women to achieve it. Television as a medium plays an influential role when depicting the stereotypes that are present within social systems. In this paper I discuss the relationships between humour and the construction of a normative hegemonic masculine identity, and explore two examples from Family Guy and American Dad!. I argue that through a steady stream of humorous images, a standard is created that constructs a normative hegemonic masculinity that in turn has created a measuring stick of dominant and subordinate masculine identities. The television shows Family Guy and American Dad! use the power of satire to influence the responses of viewers

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.129
GPT teacher head0.401
Teacher spread0.272 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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