Sounds of War: Popular Music in the United States during the Vietnam War.
Bibliographic record
Abstract
The Vietnam War was the first conflict in the United States in which a large part of the population expressed its opposition to the conflict since the beginning. This massive reaction against the war, as well as the position supporting it, were reflected in the music of the period. Some of these songs hit the Top 100 chart lists and they were played in the country and on the battlefield itself. The aim of this study is to analyze a selection of songs composed by American and Canadian musicians and released between 1965 and 1970. This analysis will be focused in the themes used, as well as the different linguistic elements that can be found. This would allow us to see the differences and the shared characteristics between the songs in both sides. \nKeywords: Vietnam, war, music, protest, USA, Canada \nLa guerra de Vietnam fue el primer conflicto armado en Estados Unidos al que gran parte de la población se opuso desde el primer momento. Esta masiva reacción contra la guerra, así como la postura a favor de ésta, fueron reflejadas en la música del momento. Algunas de estas canciones llegaron a ser número uno en las tablas de éxitos y a ser reproducidas tanto en el país como en el campo de batalla. En este trabajo se analizará una selección de canciones populares entre los años 1965 y 1970 compuestas por cantantes estadounidenses y canadienses. Este análisis se centrará en la elección de temas en las canciones, así como en los diferentes elementos lingüísticos. Esto nos permitirá ver las diferencias y características en común entre las canciones de ambos bandos. \nPalabras clave: guerra, Vietnam, música, protesta, Estados Unidos, Canadá
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".