Bibliographic record
Abstract
Escuadra hacia la muerte (1953),. la obra m?s famosa de Alfonso Sastre, ha sido considerada como una obra revolucionaria, existencialista, tr?gica, absurda, pol? tica y aleg?rica. A la vez, es una obra liminal, escrita entre el primer per?odo de este autor, el de sus obras propiamente subversivas, y el subsiguiente, el de sus tra gedias complejas. En este segundo per?odo (1953-1964) Sastre escribe obras experi mentales de cierto realismo social. Escuadra hacia la .muerte responde tambi?n a preocupaciones del momento, como lo fue la Guerra Fr?a y el temor europeo por una posible Tercera Guerra Mundial. Estructuralmente, Escuadra hacia la muer te sigue pautas brechtianas en lo que podr?a llamarse un drama social, aunque aqu? en sentido antropol?gico. En efecto, se puede notar, a lo largo de las dos par tes y los doce cuadros de la obra, una estructura quintuple donde se evidencia: 1) la separaci?n de ciertos individuos de su medio ambiente natural; 2) su incorpo raci?n en un espacio liminair) el momento de transici?n ocurrido despu?s de un aut?ntico sacrificio humano; 4) la separaci?n de los ne?fitos de este espacio l? mite; y 5) la reincorporaci?n de ciertos individuos dentro de una sociedad hipot? ticamente mejor. Escuadra hacia la muerte es una obra compleja y optimista en que se imagina un mundo mejor posible
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 | 0.003 | 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 | 0.011 | 0.021 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".