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Record W4400604191 · doi:10.1093/mind/fzae034

<i>Ancient Women Philosophers: Recovered Ideas and New Perspectives</i> , edited by Katharine R. O’Reilly and Caterina Pellò

2024· article· en· W4400604191 on OpenAlexaffabout
Marguerite Deslauriers

Bibliographic record

VenueMind · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicClassical Philosophy and Thought
Canadian institutionsMcGill University
Fundersnot available
KeywordsArtPsychologyArt historyPhilosophy

Abstract

fetched live from OpenAlex

This is a wonderful book: exciting, thoughtful, and provocative. It is a collection of articles on ancient women, mostly Greek and Roman, engaged in philosophy. As a volume it addresses both the challenges of recovering the ideas of ancient women, and the methods that might allow us to do so. Most importantly, perhaps, it also suggests new ways to think about ancient philosophy, and new approaches we might take to it. It convinced me that I have been wrong (more on that below), and at the same time gave me hope. The editors aim to ‘retrieve and re-evaluate’ the ideas of women philosophers from antiquity, which have remained largely ‘unrecorded and untaught’ (p. 1). The women in question belonged to different philosophical schools (Hippocratic, Platonic, Epicurean, Cyrenaic, Stoic, and Pythagorean) and different traditions (Greek, Roman, Indian, and Chinese), from the sixth century BCE to the fifth century CE. Many scholars have worked over the last thirty years or so to recover and assess the work of women in the history of philosophy (for recent discussions see Hutton and Hagengruber 2019, and Shapiro and Detlefsen 2023). Because, however, there is scant direct evidence of the philosophical views of ancient women, little of that research has focused on antiquity until recently (see Brill and McKeen 2024, and Pellò 2022). The process of recovery of neglected figures is often characterized as ‘re-writing the canon’ but many questions remain about just what the aims of that project might be, and what should motivate it. The editors of this volume, Katharine R. O’Reilly and Caterina Pellò, address those questions only briefly in their Introduction, but the collection provokes reflection on them, and suggests possible answers.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0020.007
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0320.011

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.

Opus teacher head0.027
GPT teacher head0.226
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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