Russian reduplicative surface-syntactic relations in the perspective of general syntax
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
The paper considers lexical reduplications in Russian in the perspective of general syntax. The goal is to define and fully characterize special Russian surface-syntactic relations [SSyntRels], that is, the reduplicative SSyntRels, which appear exclusively in syntactic idioms formed by lexical reduplications. The syntactic operation REDUPL is defined, and several reduplicative SSyntRels are introduced. A deductive calculus thereof is proposed, based on three parameters concerning the correlations between the reduplicate and the reduplicand: the reduplicate is anteposed/postposed (with respect to the reduplicand); is in contact/is not in contact (with the reduplicand); represents an exact/inexact copy (of the reduplicand); eight reduplicative SSynt-Rels are theoretically possible. The notion of syntactic idiom (a non-compositional multilexemic expression having a non-segmental signifier) is formulated and illustrated: e.g., the sentence Mne Y prazdnik X ne v prazdnik Lʹ(X) lit. ‘To me the feast is not into a feast’ = ‘I cannot enjoy the feast’, which implements the syntactic idiom [X to.Y] ˹be not into Lʹ(X)˺ ‘X cannot be enjoyed by Y’. Six reduplicative SSyntRels of Russian and one of English are described. These SSyntRels are conceived as a fragment of a general inventory of SSyntRels in the world languages.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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