Creative Work of Cultic Poets of Runet as a Subcultural Phenomenon
Bibliographic record
Abstract
The article is devoted to the verbal creative work of a cult Runet author Vera Polozkova. The article is based on the material of her early lyrics, presented in the first published book “Nepoemanie” (2008). The poems by Polozkova are considered in the context of youth subculture traditions. We identified such key components of the poet’s worldview typical of modern youth subcultures as non-conformism, elitism, the overall searching orientation of her creative work (information and communication technologies, the need for finding like-minded people, love and faith in God), in regards to poetics the main features are extreme expression (metaphorization), urbanism (poetization of urban space), as well as an appeal to the genres of youth creative work, slang, ICT vocabulary and obscene language. The author of the article makes a conclusion that the bright expression of some typical characteristics of youth culture by Vera Polozkova makes her a popular poet and performer both on Runet and outside it (live performances). At the same time subcultural issues and poetics do not limit the variety of the writer’s lyric themes and poetic means. Her early works continue wonderful traditions of Russian literature, heritage of Marina Tzvetaeva, Vladimir Mayakovsky, Joseph Brodsky and others. The article also identifies and focuses on the essential features of the electronic (digital) literature and the possibility of considering it as a space in which a number of subcultural associations/communities exist.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".