Performing geopolitics of toponymic solidarity: The case of Ukraine
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".