Monumental Landscapes and the Politics of Place: The First Lenin to Fall
Bibliographic record
Abstract
On August 1, 1990, there was an unprecedented event in the Ukrainian town of Chervonohrad: a crowd gathered at the central square and, for the first time in the USSR, demolished a monument to Lenin. The demolition caused a political scandal and was the first of a chain of Lenin statue topplings all over Soviet Ukraine and beyond. Chervonohrad’s deconstruction is often compared to the array of Lenin statue demolitions that took place during the 2013-14 Ukrainian Revolution. Yet, this historic comparison does not answer the question: why was Chervonohrad, out of all the Soviet political centres and peripheral towns, meant to go down in history in this monumental way?Although the transformation of monumental landscapes has been among the most studied aspects of the post-Soviet condition, it has often been approached unilaterally. The studies of dismantled monuments have explored the largest scale of national and international politics, national imageries, and historic myth. The overwhelming attention paid to major metropolitan areas overshadowed the importance of place politics, local actors, and power relationships within former Soviet republics. As a result, the transformation of Soviet monumental landscapes has been sometimes misread as a top-down geopolitical process over the plain and ghostly backgrounds of post-Soviet metropolitan cityscapes. This article questions the scales and methods used to study monumental deconstruction. While national politics were undoubtedly an integral part of Chervonohrad’s milestone event, this study aims to understand the complex causes that led to the removal of the monument through Chervonohrad’s politics of place, the history of urban displacement and appropriation, and the agents and constellations that made this demolition possible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".