The Russian language of Odesa: simplification and reduction of grammatical complexity
Bibliographic record
Abstract
The Russian language of Odesa, in southern Ukraine, arose in a specific language contact situation where a large number of migrants from different countries settled in the city and had to learn Russian in a non-native way, giving rise to a new contact variety of Russian. Later on, successive generations of speakers acquired this variety as a native language. This article focuses on the most salient morphosyntactic properties of this variety as it was spoken from around 1850 to 1950, before it fell into disuse: (i) the simplification of grammatical gender, (ii) the partial reduction of case forms, (iii) the levelling of argument marking (toward the genitive case), and (iv) uninflected prepositional subordinative clauses. The authors show that the morphosyntactic traits that characterized this variety were not random or attributable to Odesa citizens’ low command of the Russian language, but that they responded to general processes of language de-complexification, namely reduction and simplification of grammatical complexity. More specifically, the phenomena analyzed in this paper underwent cross-linguistically well-known general principles: economy and transparency, phonologically motivated morphological reassignments, and morphological rearrangements on the basis of existing noun classes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".