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Record W4412161975 · doi:10.1080/18902138.2025.2529078

Performative male vulnerability and right-wing privilege: Vladimir Putin, Jordan Peterson and Rasmus Paludan

2025· article· en· W4412161975 on OpenAlexaboutno aff
Maria Brock, Jenny Carleheden

Bibliographic record

VenueNORMA · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCommunism, Protests, Social Movements
Canadian institutionsnot available
FundersÖstersjöstiftelsen
KeywordsPerformative utterancePrivilege (computing)Vulnerability (computing)SociologyGender studiesPolitical scienceComputer securityLawArtAestheticsComputer science

Abstract

fetched live from OpenAlex

This article examines the strategic function of public displays of vulnerability by three powerful male figures: Russian President Vladimir Putin, Canadian psychologist and conservative social media personality Jordan Peterson, and Swedish and Danish politician and Islamophobe Rasmus Paludan. Each is associated with ideologies that are championing ‘traditional’ masculinity, which means their shows of vulnerability may initially appear at odds with the conservative or right-wing values they promulgate. We examine what is meant to be invoked in the audience by these figures’ strategic borrowing of ‘feminine’ traits in their performances of masculinity.Theoretically, the article is rooted in theories of identification in psychoanalysis and critical theory as they relate to processes of leadership and group identification, as well as treating the masculinist logic of gendered nationalism as underlying contemporary forms of right-wing politics. We find that the three men’s strategic borrowing of vulnerability in fact represents a manipulative component of right-wing Weltanschauung, where its performance can solidify dominance over groups of followers, without extending compassion to those othered by this very ideology.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.317
Teacher spread0.302 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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