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Record W2601444870 · doi:10.3167/hrrh.2017.430105

Pious Women in a “Den of Scorpions”

2017· article· en· W2601444870 on OpenAlexvenueno aff
Amy Livingstone

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsnot available
Fundersnot available
KeywordsQueen (butterfly)EleventhWifeNegotiationPower (physics)PoliticsAncient historyHistoryArtSociologyLawPolitical science

Abstract

fetched live from OpenAlex

• Chroniclers observing the complex politics of medieval Brittany referred to it as a “den of scorpions.” Eleventh- and early twelfth-century Brittany was politically unstable, with comital power under threat from both local lords and ambitious neighbors. The counts of Brittany depended upon their wives to bolster relationships with other regional powers, including the church, and to create alliances. These women brought with them relationships, ties, and associations to many powerful ecclesiastical foundations. This article examines the experiences of Countess Havoise (r. 1008–1034), Countess Bertha of Blois (c. 1020–1100), Countess Bertha (d. 1085), wife of Geoffrey Grenonat, and Countess Constance (r. 1076–1090), who all used ecclesiastical patronage to solidify the power of husbands and sons. This support allowed women to develop relationships with medieval clerics, making them, like Queen Esther, ideally placed to intervene and negotiate when tensions arose between the counts and the church.

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)0.001
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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.020
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.059
GPT teacher head0.290
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.

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
Published2017
Admission routes1
Has abstractyes

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