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Record W3155718462 · doi:10.24908/iqurcp.9840

Transvestite, Harlot, and Kingly Saints: Portraying Gender Ideals in Middle Byzantine and Anglo-Saxon Hagiography

2018· article· en· W3155718462 on OpenAlexvenueno aff
Colleen Maillet

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsnot available
Fundersnot available
KeywordsVenerationByzantine architectureCultLiteratureChristianityArtHistoryClassicsSociologyReligious studiesAncient historyPhilosophy

Abstract

fetched live from OpenAlex

The purpose of my study is to explore and analyze some didactic elements concerning gender ideals that are found in hagiographies in early medieval Christianity. By studying lives from two traditions that are widely separated in terms of region, Byzantine saints from the East and Anglo-Saxon saints from the West of the Medieval world, I have been able to distinguish elements that are specific to the particular society and reinforced through these stories. Focusing on the portrayal of gender ideals, I have been able tosuggest how the authors have contrived to present, and encourage, specific notions of socially appropriatebehaviors and attitudes. My study, dispelling a popular assumption that saints are mainly celibate martyrs,includes transvestite nuns, repentant harlots, military men, and pious kings. In each case, however, it shows that their veneration, and the creation of the written tradition supporting their cult, is clearly influenced by the desire to provide examples of gendered behavior that the church perceives as appropriate for the society.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.156
GPT teacher head0.328
Teacher spread0.171 · 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 teacher head, not a consensus.

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
Published2018
Admission routes1
Has abstractyes

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