MétaCan
Menu
← Back to cohort
Record W4254387463 · doi:10.32920/ryerson.14647632

What Not To Wear At The Opera: Outfitting Sociability at the Met

2021· preprint· en· W4254387463 on OpenAlexaff
Kate Marland

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsToronto Metropolitan UniversityMcGill University
FundersGeorge Washington University
KeywordsOperaEliteClass (philosophy)MusicalPower (physics)Cultural capitalVisual artsCohesion (chemistry)Metropolitan areaSociologyAestheticsArtHistoryPolitical scienceSocial scienceLawComputer sciencePolitics

Abstract

fetched live from OpenAlex

This research project proposes that fashion performs a critical role in the perpetuation of class hierarchies in American opera audiences. Dress is used by opera patrons as a mode of expressing their economic, social, and cultural capital, thereby affirming their status within society. The Metropolitan Opera house, opened in New York City in 1883, was built intentionally to create a space for the New York elite class to socialize, incorporating architectural features that reflected the power dynamics of New York society, effectively prioritizing sociability over musical integrity. This study is supported by analysis of early Vogue magazine articles that directly contributed to the formation of the opera as a pursuit for the upper-class; as well as a critical investigation of photographs drawn from the Met archive revealing the ways in which fashion at the Met performs economic and social power.. Ultimately, this project uses dress to examine the embedded class hierarchies that sustain an elite, exclusive audience for opera in America; indeed, the study shows that the combination of opera and fashion created class cohesion through mutually acknowledged cultural literacy in New York City.

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: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.008
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.104
GPT teacher head0.358
Teacher spread0.253 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicCultural Industries and Urban Development→French-language works237,207→