Presentation of the Patterson Prize / Présentation du prix Patterson
Bibliographic record
Abstract
Presentation of the Patterson Prize / Présentation du prix PattersonWe have the distinctive pleasure to announce that Esther Demoulin's incisive and innovative article "'Qui gagne perd': Simone de Beauvoir et le couple littéraire" ("'The Winner Loses': Simone de Beauvoir and the Literary Couple") is the recipient of the second annual Patterson Prize / prix Patterson competition.This award was established by the International Simone de Beauvoir Society in 2020 to recognize outstanding work in Beauvoir studies that extends Simone de Beauvoir's legacy both by making an original contribution to the field and enacting modes of thinking and expression characteristic of Beauvoir's oeuvre.The Patterson Prize / prix Patterson is named in honor of Yolanda Astarita Patterson, founder and first president of the International Simone de Beauvoir Society, author of numerous publications that opened the field of Beauvoir studies in the 1990s and 2000s, and editor in chief of Simone de Beauvoir Studies for thirty years.1With the publication of each Patterson Prize / prix Patterson article, we pay homage to Yolanda and her vision of building a robust international community of researchers, teachers, and activists who are inspired, challenged, and brought together by Simone de Beauvoir's writings.Demoulin's article stands out because it not only offers fresh ways to think about the significance of Beauvoir's relationship with Jean-Paul Sartre but also attends to Beauvoir's evolving sense of her own relationship to the literary canons and trends of the twentieth century." 'Qui gagne perd': Simone de Beauvoir et le couple littéraire" considers what it means to be a woman writer across historical shifts in the purpose, audience, and practice of literature, as well as the practical strategies that Beauvoir used to navigate these changes.Demoulin understands the idea of the "literary couple" as a relationship between two writers who share lived experiences, a library, a place in the public eye, and a mode of reading each other's writing that is woven into everyday life. 1 For a detailed discussion of Yolanda Astarita Patterson's unparalleled contributions to Beauvoir studies and the history of the Patterson Prize / prix Patterson, see the editors' introduction that accompanies the inaugural presentation of the award.Jennifer McWeeny and
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.104 | 0.027 |
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".