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Formation and Evolvement of the Russian Avant-Garde during 1910–1930. Ideas of the Russian Textile Avant-Garde

2022· article· en· W4312472259 on OpenAlexaboutno aff
Tatiana E. Patina, Olga V. Kovaleva

Bibliographic record

VenueVestnik slavianskikh kul’tur [Bulletin of Slavic Cultures] · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Politics, and Modernism
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsAvant gardeTextilePaintingQuarter (Canadian coin)ClothingArt historyAestheticsArtSociologyHistoryPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

The paper presents an analytical review of the studied and processed information on the fundamental role of the education of artists in the system of the avant-garde institutes and art schools in the first quarter of the twentieth century. The study explores the main theoretical aspects related tothe development and formation of the Russian textile avant-garde. For a deeper and more objective understanding of the development of innovative ideas in the art of post-revolutionary Russia in the 20th century it focused on the activities of the main ideologists of the Russian avant-garde in the art of painting: M. F. Larionov, N. S. Goncharova, K. S. Malevich, and V. V. Kandinsky. In the textile art there were studied the activities of V. F. Stepanova, L. S. Popova, and O. V. Rozanova, as well as other personalities who influenced the formation of avant-garde schools. The authors provide an insight into how the ideas of the avant-garde were kept in the ideas of suprematism, constructivism and propaganda textile. The paper allowed conclusion that the study and research of the ideas of the Russian avant-garde opens up fresh opportunities for thedevelopment of modern Russian design.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.219
Teacher spread0.204 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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