Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.025 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".