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Record W7128812751 · doi:10.1093/hisres/htaf017

Guda, a sinful woman: a multi-scalar portrait of a medieval scribe and illuminator

2025· article· en· W7128812751 on OpenAlexaff
Erik Kwakkel, Peter Vandenabeele, Eva Vermeersch, Sophie Andrade

Bibliographic record

VenueHistorical Research · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsWitnessContext (archaeology)PortraitMultidisciplinary approachZoomMedieval art

Abstract

fetched live from OpenAlex

Abstract This is a multidisciplinary re-evaluation of the Guda Homiliary, a medieval manuscript copied and illuminated by a scribe who identified herself as ‘a sinful woman’. We combine historical and palaeographical detective work with non-destructive Raman micro-spectroscopy to offer a multidisciplinary reassessment of this important witness to the presence of highly skilled female scribes in medieval Europe. We take a multi-scalar approach, beginning with a fresh analysis of the self-portrait initial itself, and then zooming out, first to its context within the broader manuscript, and then into the book’s place within the spiritual and economic landscapes of medieval Germany and beyond.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.013
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.003
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 head0.151
GPT teacher head0.355
Teacher spread0.204 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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