Judith Butler (2024). Who’s Afraid of Gender? Toronto: Knopf Canada, 320 pp.
Bibliographic record
Abstract
Son pocos los libros que logran convertirse en un éxito de masas y, al mismo tiempo, en una importante contribución teórica para un campo académico. Aún más escasos son aquellos que, además, proponen un diagnóstico global necesario, aunque no por ello menos angustiante y doloroso. Who’s Afraid of Gender?, de Judith Butler, forma parte de este selecto grupo. Sin duda, esto es sorprendente, pues hasta hace poco era difícil imaginar que un libro sobre teoría de género alcanzara tal nivel de popularidady suscitara, al mismo tiempo, tan intensas pasiones. Sin embargo, esta obra, la más clara y didáctica escrita por Butler, estaba destinada a convertirse en un testimonio del zeitgeist contemporáneo, pues en ella se analizan muchas de las tensiones y contradicciones de la compleja épocaque atravesamos.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".