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Record W2102836278 · doi:10.7202/1027690ar

From Practice to Print: Women Crafting Authority at the Margins of Orthodox Medicine

2014· article· en· W2102836278 on OpenAlexvenueno aff
Margaret Carlyle

Bibliographic record

VenueMémoires du livre · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAmateurAgency (philosophy)PublicityNarrativeVariety (cybernetics)Medical practicePublic relationsSociologyLawMedia studiesPolitical scienceMedicineSocial scienceMedical educationArtLiterature

Abstract

fetched live from OpenAlex

This article analyzes how a category of women possessing medical secrets known as “femmes à secrets” entered commercial medicine in mid- to late-xviiith-century Paris. It reads sources including remedy patents and printed publicity with a view to exploring women’s agency in producing and peddling medical products and services within the burgeoning marketplace. It shows how this form of “fringe” practice provided a unique forum where women cultivated their authority outside of learned medicine while also interacting with it. In doing so, the article displaces traditional narratives which position charlatans and quacks as the primary practitioners who colonized the margins of medical practice. Instead, it provides an account of women as examples of the dynamic “fringe” practitioners who strove to prove their genuine authority across a variety of domains. By bringing their practice to print, enterprising women succeeding in staking out their claim to expertise in a growing and increasingly consumerist, legislated, and policed medical milieu, where the boundaries between “expert” and “amateur” knowledge traditions were becoming increasingly blurred.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.977
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0230.061
Scholarly communication0.0090.007
Open science0.0010.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.028
GPT teacher head0.259
Teacher spread0.231 · 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.

Study designQualitative
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

Citations1
Published2014
Admission routes1
Has abstractyes

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