The Influence of French on Eighteenth-Century Literary Russian. Semantic and Phraseological Calques
Bibliographic record
Abstract
May Smith. The Influence of French on Eighteenth-Century Literary Russian. Semantic and Phraseological Caiques. Bern/Frankfurt a.M./New York: Peter Lang, 2006. 399 pp. Bibliography. Indices of caiques. $73.95, paper.Its primary title notwithstanding, this book is perhaps most accurately described as a thesaurus of apparent, French-derived semantic and phraseological caiques that author, May Smith, has found used and/or discussed in 18th-century Russian publications (literary works, dictionaries, essays, etc.). By my count, indices at end of book list 130 semantic caiques (pp. 393-394) and 350 phraseological caiques (pp. 395-399). The semantic caiques are itemized (in no obvious order) in Chapter I (pp. 35-162) and are usually accompanied by some commentary or brief discussion as well as relevant excerpts from 18th-century Russian source(s) in which they appear. A number of these sources are direct Russian translations of French literary works, a fact which increases likelihood that many of Russian terms cited by Smith really are caiques. The same procedure is continued in Chapter II (pp. 163-371), where phraseological caiques are itemized. In each instance author provides French source of caique-for example, Russianporazit'Because of relatively large typeface used in this book and brevity of its General (pp. 15-28), Introduction [to] Caiques (pp. 29-34), and General Conclusion (which is actually an afterword, largely rehashing General Introduction, pp. 375-378), reading book from cover to cover is not as timeconsuming as one might imagine in view of its 399 pages. Many pages, moreover, are about one-third blank. In introductions, Smith reviews widespread use of French in 18th-century Europe, both among intellectuals and among nobility and royal houses of many European countries, including Russia. At same time, she reminds readers of great influence that French exerted on development of Russian literary thanks in large part to numerous Russian translations of French works of literature. Here she also provides working definitions of various types of caiques: a semantic caique (also known in English as a 'loan meaning' [this term itself being a loan translation of German Lehnbedeutung or Bedeutungsentlehnung]), we are told, is the borrowing by a word in receiving of one or several meanings of corresponding word in donor language, whose primary meaning is identical to primary meaning of word in receiving language (p. …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".