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Record W4393303912 · doi:10.26443/firr.v14i2.171

Language, Power, and the Media in the Portrayal of Wartime Sexual Violence

2024· article· en· W4393303912 on OpenAlexvenueno aff
Morgana Angeli

Bibliographic record

VenueFlux International Relations Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsPower (physics)Sexual violenceCriminologyPsychologyComputer securityPolitical scienceComputer sciencePhysics

Abstract

fetched live from OpenAlex

Sexual violence has increasingly been recognised – and framed – as a war crime. This essay seeks to unpack the normative and epistemological elements of this discourse. The literature is dominated by peacetime studies of gender and language which fail to analyse elements of shock and labels in the construction of the actors at play. This paper seeks to understand how language, power and media work together to infantilize women and create an implicit dichotomy of victims and survivors. Drawing on critical feminist and post-structural theories, it is argued that media agents play a significant role in shaping perception and defining policy on wartime rape, through language patterns and themes. It is concluded that the language employed by news articles contributes to the gendered socialization of wartime rape. The argument is illustrated by a critical discourse analysis (CDA) of two news channels, Al Jazeera and Fox News, which seeks to identify the common discursive themes and demonstrates that the rhetoric employed is self-perpetuating and is conducive to gendered assumptions and shortcomings.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.346
Teacher spread0.325 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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