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Record W4286382210 · doi:10.3138/jeunesse.13.1.159

“Laugh! I Thought I Should’ve Died”: British Music Hall Humour and the Subversion of Childhood on The Muppet Show

2021· article· en· W4286382210 on OpenAlexvenueno aff
Liam Maloy

Bibliographic record

VenueJeunesse Young People Texts Cultures · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsSubversionComedyCarnivalesqueMusicalContext (archaeology)Human sexualityInterpretation (philosophy)SociologyNormativeTrope (literature)AestheticsPsychologyLiteratureArtGender studiesHistoryPoliticsPhilosophyLinguisticsEpistemologyLaw

Abstract

fetched live from OpenAlex

Through the abundant use of the bawdy, humorous songs of British music hall, The Muppet Show delivered a potent critique of constructed notions of a protectionist childhood. Paradoxically perhaps, the music hall songs, carnivalesque comedy, and frequent depictions of sex, sexuality, and violence also did much to construct The Muppet Show’s intended “family” audience while simultaneously providing a direct challenge to its normative sanguinuptial (blood and marriage) construction. This intergenerational family audience is crucial to the child’s interpretation of The Muppet Show’s complex and contentious content, subject matter that is rarely included in media made for a solely child audience. While the musical sketches open up an interpretive space for the child to encounter, resist, and subvert the range of fluid identities hinted at onscreen, the process is simultaneously constricted by the musical-visual texts themselves and by The Muppet Show’s family-reception context. As such, this case study reveals the inherent tensions of targeting a family audience through music and television.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.014
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.019
GPT teacher head0.209
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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Same venueJeunesse Young People Texts CulturesSame topicMusic History and CultureFrench-language works237,207