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Record W2030336077 · doi:10.1017/s0008423908080165

Russia Transformed: Developing Popular Support for a New Regime

2008· article· en· W2030336077 on OpenAlexaff
Andrea Chandler

Bibliographic record

VenueCanadian Journal of Political Science · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicRussia and Soviet political economy
Canadian institutionsCarleton University
Fundersnot available
KeywordsPoliticsPolitical sciencePublic opinionMedia studiesPublic administrationSociologyLibrary scienceLawComputer science

Abstract

fetched live from OpenAlex

Russia Transformed: Developing Popular Support for a New Regime, Richard Rose, William Mishler and Neil Munro, Cambridge and New York: Cambridge University Press, 2006, pp. xii, 226. This monograph analyzes major findings of fourteen years of public opinion research in Russia carried out under the New Russia Barometer survey research project, which Rose and colleagues conducted in conjunction with the Levada Centre in Russia. Rose, Mishler and Munro offer a clearly written, focused discussion that puts complex data into perspective. The work's major contribution is its systematic evaluation of the evolution of Russian citizens' political attitudes from 1992 to 2005. As the authors note in their dedication to the volume, their surveys included over 28,000 people across Russia (the methodology is outlined on pp. 70–75). As such, the book's authority in providing an accurate reflection of citizens' views is indisputable. Much to their credit, the authors render their findings readily understandable to readers who are not expert in survey research design or quantitative methods.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.053
GPT teacher head0.319
Teacher spread0.267 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

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