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Record W2292773372 · doi:10.1111/1468-2346.12551

Queering women, peace and security

2016· article· en· W2292773372 on OpenAlexfundno aff
Jamie J. Hagen

Bibliographic record

VenueInternational Affairs · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsPolitical scienceSecurity studiesSecurity councilInternational securityHuman securityInternational relationsGender studiesPublic administrationSociologyMedia studiesLawPolitics

Abstract

fetched live from OpenAlex

The aim of the eight Women, Peace and Security (WPS) United Nations Security Council resolutions, beginning with UNSCR 1325 in 2000, is to involve women in peacebuilding, reconstruction and gender mainstreaming efforts for gendered equality in international peace and security work. However, the resolutions make no mention of masculinity, femininity or the LGBTQ (lesbian, gay, bisexual, transgender and queer) population. Throughout the WPS architecture the terms ‘gender’ and ‘women’ are often used interchangeably. As a result, sexual and gender-based violence (SGBV) tracking and monitoring fail to account for individuals who fall outside a heteronormative construction of who qualifies as ‘women’. Those vulnerable to insecurity and violence because of their sexual orientation or gender identity remain largely neglected by the international peace and security community. Feminist security studies and emerging queer theory in international relations provide a framework to incorporate a gender perspective in WPS work that moves beyond a narrow, binary understanding of gender to begin to capture violence targeted at the LGBTQ population, particularly in efforts to address SGBV in conflict-related environments. The article also explores the ways in which a queer security analysis reveals the part heteronormativity and cisprivilege play in sustaining the current gap in analysis of gendered violence.

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)0.004
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.034
Scholarly communication0.0080.006
Open science0.0000.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.278
Teacher spread0.263 · 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

Citations194
Published2016
Admission routes1
Has abstractyes

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