Horses in the Back: Negotiations of Black Identity through Cowboy Symbolism in American Popular Culture
Bibliographic record
Abstract
In 2019 Lil Nas X released a country-trap song called “Old Town Road” that challenges the traditional boundaries of American popular music. This research paper examines the creation, maintenance, and subversion of myths in American popular culture through the lens of the song “Old Town Road.” With Roland Barthes’ work on mythologies as the theoretical framework, this research asks the following question: How does Lil Nas X, a young queer Black man, reshape the popular American iconography of the western cowboy in order to reconstruct mainstream popular culture representations? The research draws upon critical theory from a range of fields, including subculture, postcolonial, and intersectional feminist theory. This study finds that Black Americans have been marginalized by American history through racial stereotypes and strict social boundaries. However, through self-representation in music and style Black creators work to actively rewrite the myths of American identity.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.025 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".