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Record W2273074229 · doi:10.1177/1532708615617640

Authorship and Nostalgia in Contemporary Cowboy Repertoire

2015· article· en· W2273074229 on OpenAlexafffund
Gillian Turnbull

Bibliographic record

VenueCulture Studies &#x2194 Critical Methodologies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsToronto Metropolitan University
FundersYork University
KeywordsRepertoireSentimentalityPeriod (music)LiteratureComposition (language)HistoryArtMusicalAestheticsVisual arts

Abstract

fetched live from OpenAlex

The genre of cowboy music, first developed by working cowboys in the late 19th and early 20th centuries, has been thoroughly documented by early folklorists, and revived by younger performers working as professional songwriters. Through an analysis of the cowboy classics recorded by Ian Tyson, and of six volumes of cowboy songs available in written form, this article proposes that despite the weight of tradition that cowboy repertoire bears, it has been one that favors new composition because it exists as a folk music, a commercial music, and an art music all at once. This article will also consider the significant role of place in Western song; for cowboy singers, the ongoing disappearance of an old West is a source of both despair and inspiration. In this sense, songwriters are not only responsible for creating a picture of a mythic West but also charged with reminding listeners that it should still exist, thereby shaping our knowledge and experience of the region through song. The resurrection of old repertoire is one of the ways cowboy singers can respond to anxiety over the vanishing West. These songs, alongside new compositions that maintain sentimentality for the past, serve a nostalgic function for audiences who long for a lost West but have never experienced it as it is portrayed in art.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.480
GPT teacher head0.429
Teacher spread0.052 · 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 teacher head, not a consensus.

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

Citations2
Published2015
Admission routes2
Has abstractyes

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