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Record W4413277704 · doi:10.3138/flor-2023-0006

Judith, Éowyn, and the Alloying Effects of Sexualized Violence

2025· article· en· W4413277704 on OpenAlexaffvenue
Gavin M. Foster

Bibliographic record

VenueFlorilegium · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPost-Communist Economic and Political Transition
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCriminologySociologyGender studiesPsychologyArt

Abstract

fetched live from OpenAlex

Critics have argued that J. R. R. Tolkien uses his northern heroic characters to fix the broken heroism of Old English characters. However, I suggest that Tolkien does not pursue the same motivation in constructing his heroines. Rather, women demonstrate a distinct form of “alloyed” northern heroism due to their experiences of marginalization. When we compare the heroic actions of the Old English Judith to Tolkien’s Éowyn, while demonstrating northern heroic qualities, both Judith and Éowyn must additionally contend with threats of gendered, sexualized violence. Judith’s fight against Holofernes is not only a fight against an opposing political power, it is also implicated in struggles against sexual subjugation and the harassment of women. When she fights, she risks permanent social and cultural marginalization, losing her status as a “chaste woman.” The outcome of Éowyn’s fight against the Witch-king is similarly determined by her role as a woman. Her initial social role as cup-bearer shapes how her heroism is read, as does the Witch-king’s threat of sexualized violence and her ultimate return to the private sphere. Together, these elements construct a gendered arc that has no parallel among Tolkien’s male characters.

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)0.002
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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.030
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.281
Teacher spread0.275 · 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 routes2
Has abstractyes

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