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Record W3006237469 · doi:10.7202/1066750ar

Speaking in Pictures: Reading, Memory and Interpretation in Francesco da Barberino’s Advice to Women in his Reggimento e costumi di donna

2020· article· fr· W3006237469 on OpenAlexafffundvenue
Catherine Harding

Bibliographic record

VenueRACAR Revue d art canadienne · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical and Literary Analyses
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Victoria
KeywordsHumanitiesInvocationArtPhilosophyTheology

Abstract

fetched live from OpenAlex

Cet article étudie les différentes façons dont la lecture, la visualisation et l’interprétation travaillent de pair dans la tradition manuscrite de Reggimento e costumi di donna, un précis de bonne conduite rédigé par Francesco da Barberino à l’intention des femmes. Le public de la fin du Moyen-Âge était capable de naviguer entre des images verbales et visuelles du bon et du mauvais comportement selon une expérience corporelle de la lecture, alors que les lecteurs éprouvaient leur adhésion aux objectifs moraux prônés par la pensée chrétienne. Ce texte pouvait s’adresser à des hommes, des femmes et des enfants se trouvant dans un contexte familial. Le livre se termine par l’invocation d’un splendide joyau qui fonctionne comme un puissant procédé mnémotechnique destiné à aider le lecteur à se souvenir du texte et à activer le message dans son esprit.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.016
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.004
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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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
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

Citations2
Published2020
Admission routes3
Has abstractyes

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Same venueRACAR Revue d art canadienneSame topicHistorical and Literary AnalysesFrench-language works237,207