Change and Continuity in the Urban Semiosphere of Post-Soviet Kharkiv
Bibliographic record
Abstract
The paper studies change and continuity in the urban semiosphere of Kharkiv in the post-Maidan period, focusing on themes such as the interplay of languages, street art, toponyms, and the significance of political, ideological, commercial, and artistic discourses in the urban space. The urban vernacular of Kharkiv is examined via the concept of the palimpsest that helps to expose the process of acceptance or rejection of the past, and to assess how things are remembered and forgotten through the tropes of the old narrative that were scrapped and replaced with new ones. The analysis of the linguistic landscape in this study focuses on a broader, more inclusive set of components that are part of public spaces, such as street graffiti metaphors and reactions to the text on graffiti. Thus, а multimodal approach is essential to provide deeper meanings and interpretations of public spaces. To examine the complex linguistic landscape, I bring together a representative collection of public signage that mirrors the dynamics of different historical, linguistic, and ideological factors that shape the contemporary Ukrainian identity, along with the too obvious and simultaneous presence within it of markers of the collective identity from the Soviet period. The juxtaposition of overlapping narratives provides a means to discuss the city’s community-building efforts. My paper introduces a few familiar cases of how post-Soviet urban dwellers have shaped social spaces.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| 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".