Bibliographic record
Abstract
Abstract This paper has two goals: to show why Clare Hemmings’ work, Why Stories Matter: The Political Grammar of Feminist Theory (2011), which focuses on the types and consequences of feminist “stories,” should be applied to Simone de Beauvoir; and to argue that Beauvoir’s place in the history of feminist thinking should be revisited. I propose to use some of the critical tools gleaned from Hemmings’ text to think through the place of Simone de Beauvoir in feminist theoretical storytelling. Résumé Cet article a un objectif double : démontrer pourquoi le travail de Clare Hemmings, Why Stories Matter: The Political Grammar of Feminist Theory (2011), qui met l’accent sur les types et les conséquences des « récits » féministes, doit s’appliquer à Simone de Beauvoir, et faire valoir que la place de Beauvoir dans l’histoire de la pensée féministe doit être réexaminée. Je propose d’utiliser certains des outils critiques du texte de Hemmings pour réfléchir à la place de Simone de Beauvoir dans la narration théorique féministe.
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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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.045 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".