Song from the discarded: The multisensory shaping of a community corrido in the Oaxaca dump
Bibliographic record
Abstract
This article examines a corrido, a Mexican folk song, crafted through the collaborative songwriting efforts of Los Pepenadores, a formally organized yet often disregarded workers’ union that laboured in the garbage dump of Oaxaca, Mexico. Situating this corrido within the community’s 42-year history of environmental interaction and their multisensory listening and sound-making practices reveals the organic development of their collaborative process. This community’s corrido serves as a testament to their history and a repository for their memories and stories. This article also addresses this corrido’s ongoing importance following the dump’s closure in 2022, as the community negotiates recording and sharing their song to honour and uphold their enduring connections. Drawing from two years of fieldwork, two decades of personal connection and engaging the fields of ethnomusicology, sound studies, discard studies and community music, I propose an interdisciplinary framework to examine how this corrido functions within this community, revealing its roles in self-representation, shared experience and inclusion. I argue that Los Pepenadores’ virtuosic, multisensory environmental engagement and strong communal ties, combined with the corrido genre’s deep cultural roots, produced a distinctive instance of multisensory songwriting. This collaboratively composed corrido stands as a poignant tribute to a proud community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| 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".