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Gender, power and international (mis)recognition: Russia’s quest for epistemic agency through the ‘civilisational’ crusade against the rights of sexual and gender minorities

2023· article· en· W4388210348 on OpenAlexaff
Tanya Narozhna

Bibliographic record

VenueGlobal Discourse · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsHuman rightsAgency (philosophy)Gender studiesSociologyRealmScholarshipPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

This article explores Russia’s quest for agential equality with the US through the lens of the gendered dynamics of international (mis)recognition. It draws on the constructivist scholarship that emphasises Moscow’s unfulfilled desire for parity with, and perceived misrecognition by, the West as one of the principal drivers of post-Soviet Russian foreign policy. However, the article moves beyond these analyses by bringing to the fore the centrality of gender in the Kremlin’s pursuit of recognition. It argues that Russia’s ‘civilisational’ crusade against universal human rights, especially the rights of sexual and gender minorities, should be understood as part of the broader struggle for recognition on Russia’s terms. Since misrecognition is associated with curtailed agency and lower status, it invokes associations with femininity, which Russian elites and society generally view as a humiliating act of emasculation. Moscow’s crusade against the rights of sexual and gender minorities has been explicitly predicated on gendered meanings, discourses and policies. This crusade has been intended as a bold, remasculinising campaign that would enable Russia to assert its epistemic agency in the realm of universal human rights and establish epistemic parity with the West. Importantly, Moscow’s struggle against perceived Western misrecognition comes at a cost to sexual and gender minorities in Russia: it amounts to structural, social and physical violence against these minorities, rendering them profoundly insecure.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.021
Scholarly communication0.0090.003
Open science0.0000.005
Research integrity0.0020.003
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 head0.092
GPT teacher head0.382
Teacher spread0.290 · 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.

Study designQualitative
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

Citations3
Published2023
Admission routes1
Has abstractyes

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