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Record W7115931018 · doi:10.5206/fpq/2025.4.18657

Early Modern Feminists on Wooing as a Gendered Epistemic Harm

2025· article· en· W7115931018 on OpenAlexaffvenue

Bibliographic record

VenueFeminist Philosophy Quarterly · 2025
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsMcMaster University
FundersUniversität Paderborn
KeywordsAgency (philosophy)HarmCoercion (linguistics)Power (physics)Relation (database)Autonomy

Abstract

fetched live from OpenAlex

In this article I explore how three early modern European feminists—Marie de Gournay, Margaret Cavendish, and Mary Astell—discuss wooing in surprisingly similar ways. Independently and without the benefit of a personal or intellectual relationship, all three highlight how wooing is characterized by deception, insincere flattery, and occasional coercion to secure consent to marriage; they problematize how wooing tricks women into consenting to their own subordination. This is a feminist social epistemological project: Gournay, Cavendish, and Astell recognize wooing as a gendered socio-epistemic harm, for wooing undermines women’s abilities to exercise their epistemic agency over making what was often the single most consequential choice in their lives—who to accept as husband. I argue that for Gournay, Cavendish, and Astell, wooing not only is a gendered socio-epistemic harm but also manifests an epistemic injustice, hermeneutical obscuring, which was deployed by wooers in service of maintaining patriarchal power hierarchies. For Gournay, Cavendish, and Astell, the social practice of wooing manifests patriarchal control via a kind of gendered epistemic tyranny. Successful wooing frustrates epistemic capacities, entrenches gender hierarchies, and traps women in the epistemically and politically subordinating relation of marriage.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.066
Scholarly communication0.0060.009
Open science0.0010.006
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.340
Teacher spread0.301 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2025
Admission routes2
Has abstractyes

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