MétaCan
Menu
Back to cohort
Record W3198673254 · doi:10.1080/1060586x.2021.1971927

Mixed signals: what Putin says about gender equality

2021· article· en· W3198673254 on OpenAlexafffund
Janet Elise Johnson, Alexandra Novitskaya, Valerie Sperling, Lisa McIntosh Sundstrom

Bibliographic record

VenuePost-Soviet Affairs · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of British Columbia
FundersNorges ForskningsrådSocial Sciences and Humanities Research Council of CanadaUniversity of British Columbia
KeywordsTraditionalismEliteGender balanceIdeologyPoliticsBalance (ability)Political scienceNormativePolitical economySociologyGender studiesLawPsychology

Abstract

fetched live from OpenAlex

The prevailing wisdom among scholars of gender in Russia is that Vladimir Putin–as Russia’s “strongman” president–has become an agent of traditionalism. Some political scientists, often without a gendered lens, have argued that Putin is not so powerful, compelled to deploy various tactics and ideologies to balance competing interests among elites and retain support from the general public. We systematically analyze Putin’s statements about gender in two decades of his annual speeches (1999–2020) to better understand how Putin rules. Coding Putin’s remarks on a spectrum from promoting to opposing gender equality, we find that there has been no shift toward an explicit traditionalism, but rather, an expansion of the gender-stereotypical/Soviet views that have dominated Putin’s pronouncements all along. We argue that Putin’s diverse remarks across the spectrum of gender (in)equality constitute an important part of his efforts to balance diverse elite interests and enlist mass support.

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)0.007
metaresearch head score (Gemma)0.024
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0110.030
Scholarly communication0.0150.017
Open science0.0010.004
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.086
GPT teacher head0.346
Teacher spread0.260 · 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

Citations34
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuePost-Soviet AffairsSame topicGender Politics and RepresentationFrench-language works237,207