<i>“Chrez vsyu noch' i den' byl velikoi dozhd' (through the whole night and day there was a great rain)”</i> : on the history of a temporal use of the preposition <i>chrez (‘through’)</i>
Bibliographic record
Abstract
The article is devoted to the history of the use of the preposition чрез in combination with the names of time intervals (night, day, morning, evening, with the names of seasons and the words year and time) in the accusative case, which indicate that some event took place during the whole of the named time interval. This construction is found in Old Slavonic; in Old Russian writing it is actively used in historical narrative. In the last quarter of the 17th century, as a result of the increase in translations from Polish, the preposition чрез received semantic development under the influence of the preposition przez; at the same time, the construction чрез A1 in the meaning “throughout A1” also became somewhat widespread. At the turn of the 17th and 18th centuries, the use of this construction is characteristic of authors from the close entourage of Peter the Great. In one of the first codifications of the Russian language, V. A. Adodurov’s essay “The First Foundations of the Russian Language” (1729–1731), this construction was described as “dissonant”. By the beginning of the 19th century, the frequency of use of the construction falls, as the first place is taken by the construction чрез/через with the name of the time interval in the role of A1, denoting “after A1”. At the same time, the construction was used until the beginning of the 19th century, and sporadically even later. This use of the preposition through has not been the subject of linguists’ research so far.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".