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Record W1987525672 · doi:10.1177/1468796803003004003

Soviet and Post-Soviet

2003· article· en· W1987525672 on OpenAlexaff
Glenn Goshulak

Bibliographic record

VenueEthnicities · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsYork University
Fundersnot available
KeywordsNationalismSoviet unionPolitical scienceState (computer science)Russian studiesEmpireEconomic historyPolitical economyHistoryLawSociologyPolitics

Abstract

fetched live from OpenAlex

Since the collapse of the Soviet multinational state-empire, nationalism in post-Soviet states has been the subject of an ever-increasing number of studies. Post-Soviet scholars have adopted a wide variety of studies on different aspects of the relationship between nation- and state-building projects. In the midst of this burgeoning interest in post-Soviet nationalism, however, there has been relatively little interest in the Soviet era itself. Recent studies provide a valuable re-assessment of some aspects of the ‘national question’ in the Soviet Union. However, the scope of these studies has been relatively limited, and primarily undertaken as historical research. An example can be found in the works of Ronald Suny and Terry Martin. These two authors have re-opened evaluations of the early Soviet period and the ‘national question’. However, they focus mostly on the Leninist and Stalinist periods of Soviet history (Martin, 2001; Suny and Kennedy, 1999). Most recent studies of the Soviet Union generally do not study the entire Soviet project; and even if they do, very few have attempted to link it to the post-Soviet projects taking place today. With the exception of Ronald Suny and Rogers Brubaker, (Brubaker, 1996; Suny, 1999), there has been relatively little theoretical discussion of the Soviet nationalities model and its importance for understanding nationalism.

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)0.001
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: none
Teacher disagreement score0.955
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.321
Teacher spread0.292 · 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

Citations5
Published2003
Admission routes1
Has abstractyes

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