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Record W324839524 · doi:10.2478/pjes-2014-0017

Gender, Humour and Transgression in Canadian Women’s Theatre

2014· article· en· W324839524 on OpenAlexaboutno aff
Natalie Meisner, Donia Mounsef

Bibliographic record

VenuePrague Journal of English Studies · 2014
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsLaughterFemininityComedyAestheticsIronyAmbivalenceIdeologyMasculinityLiteraturePower (physics)AntipathyGender studiesPsychoanalysisSociologyPsychologyArtPoliticsLaw

Abstract

fetched live from OpenAlex

Abstract Are humour and laughter gender-specific? The simple answer, like most everything that is ideological, is “yes”. Many feminists in recent years have grappled with the question of humour and how it is often the site of much contestation when it comes to women using it as a tool of transgression. This paper probes the seemingly timeless antipathy between humour and representations of femininity through recourse to performance and theories of the body. This article holds the term “woman” up to scrutiny while simultaneously examining the persistence of both critical and philosophical recalcitrance and the way humour continues to function in both gendered and violent ways. How does gender “do” or “undo” humour? Laughter is no simple matter for women, due to the legacy of profoundly polarized and hyper-sexualized historical ambivalence between femininity and laughter. Acknowledging the problematic nature of the category “woman”, and after clearing some terminological distinctions (comedy, humour, irony, satire, and parody), this article investigates humour’s complicated and volatile relationship to gender and the way the laughing body of women on stage presents a fascinating double helix of sexual aggression and power

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.033
GPT teacher head0.335
Teacher spread0.302 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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