“Hurry! Be smart! Buy Trump’s fine art!” Transforming winged phrases from Soviet films into headings in Russian newspapers
Bibliographic record
Abstract
This paper examines the transformational features and usage of “winged phrases” – in this case quotations from Soviet films that have become catchphrases in spoken and written Russian – in the headings of articles from three Russian newspapers. Data were selected between 2017 and 2018 from Komsomol′skaia pravda (Moscow edition), Izvestiia, and Literaturnaia gazeta. First, the authors identify the transformational features of these phrases; second, they analyze the nature of their usage, drawing on Mikhail Bakhtin’s theory of dialogism. The study reveals two new types of transformations (grammatically associative and lexical) that have not been identified in previous literature. It also demonstrates how the prism of dialogism affords new insights into the socio-historical and multi-voiced richness of winged phrases, extending our understanding of the complex plasticity of the structural and heteroglossic features of these phrases over time.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".