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Record W4414052898 · doi:10.33137/rr.v48i3.45977

Moral Injury and the Implicit or Explicit Language of Sexual Violence during Warfare in Fifteenth-Century Flemish Chronicles

2025· article· en· W4414052898 on OpenAlexvenueno aff
Lisa Demets

Bibliographic record

VenueRenaissance and Reformation · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicReformation and Early Modern Christianity
Canadian institutionsnot available
Fundersnot available
KeywordsFlemishSexual violencePassionMoral injuryPerception

Abstract

fetched live from OpenAlex

In late medieval Flemish chronicles, sexual violence is frequently depicted as a consequence of war. Chroniclers distinguished between rape as a crime of passion and rape by armed coercion, reflecting broader societal perceptions of sexual violence. These accounts often served to demonize enemies, portraying them as morally corrupt, but they also reveal anxieties about leadership failures and moral transgressions within one’s own ranks that led to plundering, harassment, and ravishment. Both Burgundian and urban chroniclers engaged with this discourse: some highlighted ducal anti-rape policies to reinforce Burgundian legitimacy, while others exposed the contradictions between official prohibitions and the realities of war. Additionally, the portrayal of sexual violence intersects with the concept of moral injury, as chroniclers—both explicitly and implicitly—documented the violation of deeply held ideals about just warfare. As such, chroniclers constructed selective memories of sexual violence during warfare and revolts.

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)0.003
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 score0.025
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0120.046
Scholarly communication0.0050.004
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.245
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
Published2025
Admission routes1
Has abstractyes

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