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Record W2883654859 · doi:10.1386/smt.12.2.141_1

‘Is it like a beat without a melody?’: Rap and revolution in Hamilton

2018· article· en· W2883654859 on OpenAlexaff
Jeffrey Severs

Bibliographic record

VenueStudies in Musical Theatre · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLyricsMusicalJazzArtRhymeLiteraturePassionsPoliticsPerformance artArt historyPoetryLaw

Abstract

fetched live from OpenAlex

Abstract Hamilton (2015) celebrates rap as the discursively dense, incandescent language of American revolution, democracy and individuality, but the musical also, in its tragic course, portrays rap’s limits, especially when post-revolutionary problems of governance and family life arise. In giving these dual fates to the show’s central musical language, creator Lin-Manuel Miranda draws on the history of hip hop in general and gangsta rap in particular, offering an implicit critique of vengeful violence through allusions to the allegedly linked murders of Tupac Shakur and Notorious B.I.G. In its close readings of lyrics, this essay focuses on Alexander and Philip Hamilton and John Laurens and draws connections between these characters’ development and Miranda’s use of abolitionist and revolutionary history. The essay also explores the show’s many allegorical attempts to link positions on the political spectrum with different styles of music, from pop and jazz to the increasingly intricate rhyme schemes of hip hop.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0120.016
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.095
GPT teacher head0.315
Teacher spread0.220 · 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 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

Citations11
Published2018
Admission routes1
Has abstractyes

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