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Record W2964722446 · doi:10.24908/iqurcp.13387

The Political Representation of Women in the Soviet Union Compared to Modern-day Democratic Russia

2019· article· en· W2964722446 on OpenAlexaffvenue
Bohdan Tyvodar

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsQueen's University
Fundersnot available
KeywordsPoliticsDemocracyRepresentation (politics)IdeologyPolitical sciencePolitical economyMarxist philosophyIndependence (probability theory)LiberalizationSociologyLaw

Abstract

fetched live from OpenAlex

Over 25 years after Russia’s independence, Russia has established itself as one of the world’s most powerful countries, however, it seems to have forgotten about its women. This study examines why women in the Soviet Union were more represented in political institutions, specifically in the national government, than women in modern-day, democratic Russia. This study is timely and relevant because women’s political representation is an issue to which a lot of attention is devoted in the media and in academic literature. This study investigates and compares women’s involvement in political institutions in the Soviet era compared to the post-Soviet, democratic era, a natural turning point in which we would logically expect growth rather than retraction of women’s political representation. Period one encompasses women’s representation in political institutions of the Soviet Union from 1922-1991, with an emphasis on the Gorbachev era. Meanwhile, period two encompasses women’s representation in political institutions of modern-day Russia, 1991 to today. The research in this study indicates that the Marxist-Leninist ideology of the Soviet Union, the political liberalization started by the Soviet Union in the late 1980s and continued by Russia in the early to mid 1990s, and the rise of conservatism in post-Soviet Russia, are three important factors accounting for the increased gender imbalance in representation in the modern era.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.122
GPT teacher head0.422
Teacher spread0.300 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2019
Admission routes2
Has abstractyes

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