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Country Music as Cultural Practice

2017· book· en· W2730230669 on OpenAlexaboutno aff
Clifford R. Murphy

Bibliographic record

VenueOxford University Press eBooks · 2017
Typebook
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPopular musicVernacularMusic historyMusic GeographyEthnographyCountryMusic educationNarrativeArgument (complex analysis)StorytellingFolk musicLiteratureHistorySociologyArtVisual artsAnthropologyMusical

Abstract

fetched live from OpenAlex

This chapter argues that country music should be examined first and foremost as social practice—as a driver of community expression and social capital through music, words, and dance. While country music functions in a multitude of ways, from narrative storytelling to commercial product and points in between, the commercial sphere of country music has been exhaustively examined. Scholarly inquiry into country music, rooted in the folk revival of the mid-twentieth century and significantly influenced by collectors (and collections) of commercial country music, has maintained a southern, commercial focus for much of the past half-century. As such, scholarly and popular understanding of what, where, and who country music springs from has ignored significant regional vernacular forms and uses of country music. Ethnographic inquiry has made it possible to tell the story country music culture and traditions. Murphy illustrates his argument with examples from New England, the Mid-Atlantic, and Atlantic Canada.

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 score0.013
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.018
Scholarly communication0.0090.005
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.042
GPT teacher head0.216
Teacher spread0.174 · 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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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