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Record W4319318192 · doi:10.1080/00291951.2023.2170827

Performing geopolitics of toponymic solidarity: The case of Ukraine

2023· article· en· W4319318192 on OpenAlex
Оleksiy Gnatiuk, Sergei Basik

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNorsk Geografisk Tidsskrift - Norwegian Journal of Geography · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicDiverse Scientific Research in Ukraine
Canadian institutionsConestoga College
Fundersnot available
KeywordsToponymySolidarityGeopoliticsPoliticsPerformativityEtymologySociologyPolitical scienceHistoryLinguisticsLawGender studiesPhilosophyArchaeology

Abstract

fetched live from OpenAlex

The aim of the article is to elucidate the symbolic function of the underexplored geopolitically motivated phenomenon of toponymic solidarity. Based on the critical toponymic approach and the theories of political performativity, the authors examine the toponymic solidarity with Ukraine as a powerful spatial-political technology that emerged globally following the ongoing full-scale Russo-Ukrainian War in 2022. Drawing upon empirical data from media resources, archival materials, and in-situ observations, they unveil the geopolitical role of performative toponymic solidarity as a form of symbolic toponymic gifting both worldwide and in Ukraine. Concomitantly, two collateral spatial processes are revealed, including toponymic gratefulness as a reciprocal co-performance in Ukraine and toponymic retaliation as a counter-performance in Russia. In conclusion, the article advances the political toponymy literature by expanding the performative understanding of space through the lens of geopolitical place naming/renaming practices of toponymic solidarity.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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