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Private War, Private Suffering, and the Normalizing Power of Law

2013· book-chapter· en· W2479906913 on OpenAlexfundno aff
Bianca Baggiarini

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
FundersYork University
KeywordsArbitrationPower (physics)Sexual violenceContext (archaeology)Political scienceLawLaw and economicsSociologyGeography

Abstract

fetched live from OpenAlex

Abstract Purpose This chapter discusses how private military corporations (PMCs) and their employees have been implicated in discourses and practices of sexual violence. I examine how PMCs have become seemingly permanent fixtures of international relations since the end of the Cold War. Furthermore, the purpose is to contribute to the ongoing conversations about PMCs and gender. To do this, I examine one instance of sexual violence in the context of PMCs. I argue that, since the legal case was forced into private arbitration, this maneuver reflects critical shifts in the normalizing power of law, away from a model of a social contract toward global neoliberal economics. Design/methodology/approach Utilizing postmodern feminist theory alongside a Foucauldian discourse analysis, I explore the case of one PMC contractor who alleged rape by multiple coworkers in Iraq. I examine the limitations of standpoint feminism in relation to theories and representations of sexual violence. Social implications I claim that military outsourcing raises serious concerns for feminists theorizing issues of gender and wartime sexual violence. PMC personnel are unaccountable when they are implicated in cases of sexual violence. Feminist critique is urgent given the various ways PMCs have been implicated in reproducing gender inequality and in sexual violence. Originality/value This chapter advances feminist knowledge about wartime sexual violence in a context where PMCs now play a significant role in the reproduction of practices that normalize sexual violence in public and private militarized spaces, both “at home” and “abroad.”

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.899
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.260
Teacher spread0.233 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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