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Record W4308024165 · doi:10.1080/14616742.2022.2130806

Unsettling the political: conceptualizing the political in feminist and LGBTI+ activism across Russia, the Scandinavian countries, and Turkey

2022· article· en· W4308024165 on OpenAlexaff
Hülya Arik, Selin Çağatay, Mia Liinason, Olga Sasunkevich

Bibliographic record

VenueInternational Feminist Journal of Politics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersKnut och Alice Wallenbergs Stiftelse
KeywordsPoliticsConceptualizationSociologyScholarshipGender studiesContext (archaeology)LesbianPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article aims to expand the ongoing theoretical debate on the broadened and context-specific notion of politics by offering an empirically nuanced conceptualization of the political based on the study of feminist and lesbian, gay, bisexual, trans, and intersex (LGBTI+) activism in Russia, Turkey, and the Scandinavian countries. We use a multi-scalar transnational approach to foreground connectivities across regions to challenge nation-bound and state-centric perspectives on politics and reveal the various formulations beyond the formal/informal divide. Case studies from feminist and LGBTI+ activists and minority organizations demonstrate context-specific ways of inhabiting or distancing from politics. Drawing on interdisciplinary feminist scholarship and a Gramscian approach to civil society, we challenge the narrow articulation of politics either as antagonism or contestation. In doing so, we highlight the political expressions that do not neatly fit into the expected forms of politics, yet are motivated by a commitment to shaping new ways of living together.

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0080.037
Scholarly communication0.0120.006
Open science0.0010.005
Research integrity0.0020.002
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 head0.036
GPT teacher head0.375
Teacher spread0.339 · 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 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

Citations28
Published2022
Admission routes1
Has abstractyes

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