Folk Festivals, Community Development, and the Sugar Industry Crisis in Tucumán, Argentina, 1966–1973
Bibliographic record
Abstract
Abstract In the late 1960s, the sugar-growing province of Tucumán, Argentina, was undergoing the deepest economic crisis of its history. In 1966, eleven large sugar mills closed by order of the national government, then ruled by military dictator Juan Carlos Onganía. The mills closure left a quarter of the province’s labor force unemployed, which, in turns, prompted a massive rural exodus and a permanent state of social unrest. Paradoxically, at the same time, the suddenly impoverished region was experiencing a boom of folk music festivals organized by small cities and rural towns, including those severely hit by the sugar industry crisis. This essay explores the context of the folk festival phenomenon, analyzing the role of town notables and local civic organizations in responding to the crisis brought about by the closure of the mills. The festivals were, in fact, part of a wider effort of local towns to develop their infrastructure and social services. By organizing festivals and fostering community development, local notables acted as a counterweight to the activism of the working class, generating spaces of consent that aided the military government’s plans to reorder the provincial economy.
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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 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".