Bibliographic record
Abstract
Este art?culo examina dos comentes en la reacci?n cr?tica y popular a Julio Cort?zar y su novela Rayuela, una que percibe en su estructura un precursor al hipertexto y la posmodernidad y otra que mantiene que la novela y su tem?tica no supera la ?poca en que se escribi?. Para evaluar las dos interpretaciones, este art?culo explora las implicaciones del Rayuel-O-Matic, la m?quina para leer Rayuela que se describe en La vuelta al d?a en ochenta mundos e inspiraci?n para una versi?n Internet de Rayuela. Este trabajo propone que la m?quina contribu ye a la conceptualizaci?n de un lector ciborg de la novela que se opone a la tem?tica anti-cibern?tica de /?7 misma. Utilizando la teor?a del ciborg y el poshu mano de autoras como Donna Haraway y N. Katherine Hayles, el art?culo su giere que Rayuela es una obra que simult?neamente construye y rechaza las ideas y estructuras ciborgianas y poshumanas que formar?an despu?s aspectos funda mentales del hipertexto y la posmodernidad. Se arguye aqu? que k tensi?n entre la estructura hipertextual de la novela y su tem?tica anti-cibern?tica sugiere una visi?n de aqu?lla situada en la frontera entre la modernidad y la posmodernidad, entre el sujeto humano y el sujeto poshumano. A la luz del Rayuel-O-Matic, las dos reacciones recientes a Rayuela producen juntas una visi?n de las contra dicciones y paradojas de Cort?zar y su obra.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".