Bibliographic record
Abstract
This is the story of my coming to read Le Deuxième Sexe in the rather unusual way that I do.I was raised, as it were, in the Philosophy Department at Harvard University as part of the last generation working seriously under the tutelage of Stanley Cavell. Though Cavell’s tastes in philosophy were strikingly wide-ranging, crisscrossing the divide between analytic and continental philosophy, not to mention genres and mediums, there were limits to his tastes, as there of course are in every person’s case. He was interested in Heidegger, but not in European phenomenology more generally. (The one thing I recall him saying about Sartre was this offhand remark, perhaps something he had heard or read before, during a seminar: “Sartre thinks it’s very important that no one can die my death for me. Well, no one can take my bath for me, either.”) He was interested in the great film actresses of Hollywood’s golden period—Katharine Hepburn, Barbara Stanwyck, Irene Dunne, Bette Davis, Ingrid Bergman—and even thought of them as, in their own way, philosophers on screen; but he was not as interested, at least publicly, in women writers. He did engage with feminist thinkers in his own writing about film, but he was concerned in those moments mostly to worry about what he experienced as a certain theoretical rigidity in feminist film theory and what he saw as its failing to allow the objects of it criticism breathing room and to give his own way of thinking, which he saw as very much sympathetic to women’s concerns, a chance.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.030 | 0.007 |
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".