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Record W3169972124 · doi:10.3138/utq.90.1.02

Popular Music and the Modernist Dystopia: <i>Brave New World</i> and <i>Nineteen Eighty-Four</i>

2021· article· en· W3169972124 on OpenAlexaffvenue
Alex MacDonald

Bibliographic record

VenueUniversity of Toronto Quarterly · 2021
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsCampion CollegeUniversity of Regina
Fundersnot available
KeywordsDystopiaPopular musicLiteratureMusicalModernism (music)Popular cultureArtAestheticsHistory

Abstract

fetched live from OpenAlex

This essay explores musical references in Brave New World and Nineteen Eighty-Four, including music imagery and allusions to popular songs of the 1920s and 1940s. Huxley used the popular music of the Brave New World as an indicator of its emotional shallowness, represented by such immortal songs as “Hug Me Till You Drug Me, Honey.” Brave New World’s scorn for popular music, and for popular culture in general, situates Huxley’s famous dystopia as a high Modernist work. In Orwell’s case, implicit references to World War II hits such as “We’ll Meet Again” and “I’ll Be Seeing You” reflect ironically upon the relationship of Winston and Julia and their terrible situation at the end of the novel. His treatment of the musical thrush and the singing Prole laundrywoman plays a more hopeful note, and a positive attitude to popular songs and popular culture situates Nineteen Eighty-Four on the cusp of Post-Modernism. With respect to the critical discourse about hope and despair in these dystopian texts, the essay suggests that signs of hopefulness in Brave New World are very slight, although they do exist. The music of Nineteen Eighty-Four, and some other factors, lend support to the view that Orwell’s novel is not so despairing as it is sometimes made out to be.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.023
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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
GenreOther

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
Published2021
Admission routes2
Has abstractyes

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Same venueUniversity of Toronto QuarterlySame topicLanguage, Metaphor, and CognitionFrench-language works237,207