La música popular como arena de negociación en la literatura cubana posrevolucionaria
Bibliographic record
Abstract
RESUMEN Partiendo de una definición política de música popular, es decir, como una expresión cultural que no es ajena a conflictos de poder e intereses entre diversos grupos, este artículo examina la forma en la que se trata la música popular en Ella cantaba boleros de Cabrera Infante. De manera específica indaga si en este texto se muestra a la música popular como una arena en negociación constante, en donde diversos grupos sociales siempre están tratando de atribuirle su propio significado para que su particular “visión del mundo” domine sobre las demás; o si por el contrario, se asume que la música popular es un símbolo de identidad colectiva que diluye desigualdades, diferencias y que cobija a toda una colectividad bajo un mismo símbolo de identidad nacional. ABSTRACT Taking as a central point of analysis a political understanding of popular music; that is to say, as an arena of struggle among various groups, this article explores how popular music is approached in Ella cantaba boleros by Cabrera Infante. Specifically, this article explores if the text shows that popular music is an arena of constant negotiation; that is, as a cultural space that several groups use as a means to make their own views of the world appear as natural, or on the contrary, if it portrays popular music as a symbol of national identity that embraces everyone, and dissolves inequalities and differences.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".