The description of the Russian language by the French writers of the second half of the eighteenth century
Bibliographic record
Abstract
La thèse est consacrée à l'étude de la contribution des auteurs français peu connus d'ouvrages de grammaire russe (Charpentier, Maudru) et de grammaire française (De Laval, Boujot, Gautier) à l'usage des russophones, dans la description de la langue russe et le développement de la science linguistique en Russie. Les résultats de la recherche concourent à combler une lacune dans l'histoire des études slaves en France et romanes en Russie, à faire reconnaître les auteurs des ouvrages analysés en tant que témoins et acteurs de la grammatisation du russe rénové ainsi qu'à valoriser leurs témoignages, l'originalité de leurs interprétations des données linguistiques et des phénomènes grammaticaux de la langue russe de l'époque.
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.
How this classification was reachedexpand
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 | 0.002 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".