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Record W2968309498 · doi:10.1163/18763324-04603006

Kharkiv: The Past Lives On

2019· article· en· W2968309498 on OpenAlexaff
Volodymyr Kravchenko

Bibliographic record

VenueThe Soviet and Post-Soviet Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUkrainianGeopoliticsAnnexationNationalismContext (archaeology)Political sciencePoliticsState (computer science)RhetoricPopulationPolitical economyModernization theorySociologyLawHistory

Abstract

fetched live from OpenAlex

Why was Kharkiv assigned the role of an alternative political capital of Ukraine during the Euromaidan revolution of 2014? Why did this plan fail? In this article the author tries to answer these questions by exploring Kharkiv’s role and place in the regional context of ongoing Ukrainian nation-state building in the historical perspective, focusing on the period after the dissolution of the Soviet Union. Issues of regional geopolitics on the Ukrainian-Russian border as well as the changing symbolic landscape of the city are explored. The proactive role of the central authorities as well as specific local traditions and identity played their roles in keeping Kharkiv on the sidelines of the “hybrid war” that engulfed the Donbas. The modernization matrix that promoted Kharkiv’s growth from a provincial town into a regional leader prevailed over the rhetoric of Russian nationalism employed by Putin’s regime during the annexation of the Crimea. At the same time, social apathy and national ambivalence, so typical of a borderland zone, also prevented the local population from falling into political extremes. Kharkiv’s cultural space continues to be a battlefield of competing discourses, each of which has been projected into the past and the future.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.018
GPT teacher head0.342
Teacher spread0.324 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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