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Record W1988276827 · doi:10.1353/reg.2014.0007

The Reinstated Gubernatorial Elections in Russia: A Return to Open Politics?

2014· article· en· W1988276827 on OpenAlexaff
Joan DeBardeleben, Mikhail Zherebtsov

Bibliographic record

VenueRegion Regional Studies of Russia Eastern Europe and Central Asia · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsCarleton University
Fundersnot available
KeywordsPoliticsPolitical sciencePolitical economyEconomicsLaw

Abstract

fetched live from OpenAlex

Rescission of the direct popular election of Russia’s regional executives was interpreted by many observers as a cardinal indicator of the trend toward authoritarianism in Russia. In the wake of a series of vocal national protests against electoral fraud following the State Duma elections of December 2011, President Dmitrii Medvedev announced the reinstatement of gubernatorial elections, and a federal law was passed in May 2012 implementing this decision; the first gubernatorial elections under the new system took place in five Russian oblasts on 14 October 2012. This paper analyzes the campaigns and outcomes of these elections, as well as media and expert commentary surrounding them, with a goal of exploring whether the reinstitution of a gubernatorial electoral process presents a significant potential for renewed political competition or popular political mobilization at the regional level in Russia. Analysis of these early cases suggests that while these elections offer a real potential for genuine electoral contestation, the political establishment also exhibited the ability to apply a variety of formal and informal mechanisms to assure the desired outcome. Realization of the potential of gubernatorial elections to promote electoral competition would require a greater resolve and unity of opposition parties, including at the subregional level.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.067
GPT teacher head0.355
Teacher spread0.289 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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