Art Resistance against Russia’s “Non-Invasion” of Ukraine
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.
Bibliographic record
Abstract
When Russia invaded Ukraine in 2014, the Russian media ran what I propose to call a simulation of “non-invasion”—a spectacle aimed to distance Russia from the war. This essay explores activist art resistance against this simulation. Specifically, I discuss three art projects that were staged during the first, most violent year of the Russian-Ukrainian conflict: Mariia (Maria) Kulikovs'ka’s performance at “Manifesta 10” in St. Petersburg, Serhii Zakharov’s guerrilla installations on the streets of occupied Donetsk, and Izolyatsia’s #onvacation occupation of the Russian pavilion at the 56th Venice Biennale. These art projects, I argue, not only attacked the simulation from the outside as independent entities, but, by penetrating the simulation on site and online, they disrupted it from within. I offer three reasons to support this claim. First, these art projects superimposed images of the invasion over the physical sites where the “non-invasion” simulation dwelt and, in this way, not only made the war visible but also produced “a glitch in the matrix” effect—a conflict within the simulation visual regime that was inconsistent with its concealment function. Second, they “hailed” (in Louis Althusser’s terms) actants of the simulation as subjects of Putin’s regime, provoking suppressive reactions that proved Russia’s participation in the war—which the simulation, thus, failed to downplay. And third, with carefully orchestrated strategies of online outreach to the public, these art projects attached themselves to the media dimension of the simulation, making the simulation’s media proliferation work against itself.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it