(De)constructing Argentine Women: Gender, Nation, and Identity in ‘Alfonsina y el mar’
Bibliographic record
Abstract
Abstract This article examines gender, nation, and identity in the popular song of folk roots ‘Alfonsina y el mar’. Written by Félix Luna and Ariel Ramírez, the song is based on the suicide of feminist poet Alfonsina Storni and achieved worldwide popularity through Mercedes Sosa's 1969 rendition on the album Mujeres argentinas. Using Butler's theory of gender performance, Cusick's proposals for a feminist music theory, and Plesch's concept of dysphoric topics in Argentine nationalist music, this article deconstructs the song's poetic, musical, and visual discourses to critique its underlying cultural signification. It concludes that by infantilizing, romanticizing, and nationalizing Storni's public figure, her legacy was adapted to the patriarchal expectations of decorum and historical narrative about nation pervasive in Argentina in the late 1960s. Storni's white European urban background was adapted to more ‘authentic’ Argentine values through Sosa's performance and public image.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".