En busca de otros cuerpos, contagios e influencias. Notas sobre Letras arrebatadas, de Germán Labrador-Méndez
Bibliographic record
Abstract
Letras arrebatadas: Poesia y quimica en la transici6n espaiiola (Madrid: Editorial Devenir, 2009), de German Labrador-Mendez, es un riguroso estudio sabre una heterogenea secci6n de la poesia espafiola que se relacion6 con las drogas -principalmente la heroina-a partir de las afios 70.«Drogas, poesia y transici6n» seria un subtitulo mas pop pero menos acertado, pues la quimica de la que habla el critico sobrepasa las substancias.El tema es alucinante par su originalidad y la osadia de meterse en la farmacia de la poesia, y ademas porque Labrador-Mendez se arma de una bateria critica que equidista de la ingenua admiraci6n por las drogas, coma tambien de sumojigata y devastadora postura prohibicionista.Es un libro consistente pero tambien es muchos libros: todos muy bien escritos, investigados y pensados.Por eso las 500 paginas del trabajo que intercala relatos, recortes, historias y poemas, se disfrutan y se desean mas.Labrador-Mendez trabaja diferentes discursos y aproximaciones, y opera en las recovecos de las archivos, los bares, las librerias delibros nuevos y viejos, en conversaciones, entrevistas o bibliotecas, saca informaci6n y pega en el libro clips de epoca, album de fotos, y documentos de su paso por catacumbas, manicomios, y los desafiantes acometidos de las lecturas que sugiere.Toda para pensar la poesia drogada: territorio indisciplinado.Labrador-Mendez reflexiona sin las redes de seguridad de una disciplina o metodo: se crea y manta su propio salvataje conceptual.Su trabajo toma el riesgo de relucir mas
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".