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Deploying Feminism

2022· book· en· W4312232461 on OpenAlex
Stéfanie von Hlatky

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsQueen's University
Fundersnot available
KeywordsFeminismAlliancePolitical scienceService (business)Operational effectivenessSociologyEngineeringPublic relationsLawOperations researchEconomyEconomics

Abstract

fetched live from OpenAlex

Abstract Deploying Feminism tells the story of how the military has been delegated authority to advance gender equality while tackling increasingly complex threats. NATO, the world’s foremost alliance, has embedded these ideas in the planning and execution of its missions. Indeed, Women, Peace and Security norms are being integrated into military processes but not necessarily as intended. Armed forces value one thing above all else: operational effectiveness. They are trained to stay focused on mission objectives and lines of efforts. For troops deployed on NATO missions, this often means seeking out women in their operating area to improve intelligence gathering activities. This helps the mission, surely, but are the women better off? Through military implementation, the focus on gender equality fades, leading to a consistent distortion of Women, Peace and Security norms. Based on fieldwork in Iraq, Kosovo, and the Baltics, this book details why and how these norms are militarized and put at the service of NATO’s operational effectiveness.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.519
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0270.000

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 head0.054
GPT teacher head0.311
Teacher spread0.257 · 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

Quick stats

Citations20
Published2022
Admission routes1
Has abstractyes

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