Current Trends in Caucasian, East European and Inner Asian Linguistics
Bibliographic record
Abstract
This volume is a collection of seventeen papers, on languages of all three indigenous Caucasian families as well as other languages spoken in the territory of the former Soviet Union. Several papers are concerned with diachronic questions, either within individual families, or at deeper time depths. Some authors utilize their field data to address problems of general linguistic interest, such as reflexivization. A number of papers look at the evidence for contact-induced change in multilingual areas. Some of the most exciting contributions to the collection represent significant advances in the reconstruction of the prehistory of such understudied language families as Northeast Caucasian, Tungusic and the baffling isolate Ket. This book will be of interest not only to specialists in the indigenous languages of the former USSR, but also to historical and synchronic linguists seeking to familiarize themselves with the fascinating, typologically diverse languages from the interior of the Eurasian continent. Dee Ann Holisky is Professor of English and Linguistics, and Associate Dean for Academic Programs of the College of Arts & Sciences at George Mason University. She is the author of Aspect and Georgian Medial Verbs (Caravan Books, 1981) and of numerous articles on Georgian and Kartvelian linguistics. Kevin Tuite is Professor of Anthropology at the Université de Montréal. Among his books are An Anthology of Georgian Folk Poetry (Fairleigh Dickinson University Press, 1994) and Ethnolinguistics and Anthropological Theory (co-edited with Christine Jourdan; Montréal: Éditions Fides, 2003).
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Edited linguistics volume on Caucasian, East European, and Inner Asian languages; the object is language structure and history.
This collected volume concerns historical and synchronic linguistics, not research itself.
Linguistics collection on Caucasian and Inner Asian languages; domain scholarship, not metaresearch.
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 | 0.012 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".