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Record W4411737370 · doi:10.3390/arts14040071

Producing Feminist Discourses in the Debris of Destruction: Maria Kulikovska’s Response to War in Let Me Say: It’s Not Forgotten

2025· article· en· W4411737370 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueArts · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEastern European Communism and Reforms
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsDebrisArtHistoryGender studiesHumanitiesPolitical scienceArt historyAestheticsSociologyGeographyMeteorology

Abstract

fetched live from OpenAlex

The Ukrainian–Crimean artist Maria Kulikovska’s artistic practice has addressed war in Ukraine since the Annexation of Crimea and outbreak of war in the Donbas regions of Ukraine in 2014. In 2019 she created the video-performance Let Me Say: It Will Not Be Forgotten that responds to the ways artworks and women’s bodies are targeted by derisive retaliation and physical attacks during periods of political instability. Informed by explorations of feminism in post-Soviet countries, theories of prosthetic memory, and destruction art of the 1960s, I argue that Kulikovska does not let the destruction of her artwork silence her, but, rather, she uses destruction as a strategy to take control of oppressive forces. In their place, I argue that Let Me Say: It’s Not Forgotten demonstrates subjective and complex ways of building resilient feminist presents and futures that overcome oppressive violence and testify to continual perseverance.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.322
Teacher spread0.294 · 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