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Alignment and orientation in Kartvelian (South Caucasian)

2017· book-chapter· en· W2957702458 on OpenAlexaff
Kevin Tuite

Bibliographic record

VenueOxford University Press eBooks · 2017
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsErgative caseNominative caseLinguisticsVerbDative caseGeorgianSubject (documents)Orientation (vector space)Computer scienceHistoryMathematicsPhilosophyTransitive relationGeometry

Abstract

fetched live from OpenAlex

Abstract The small Kartvelian family is one of the three endemic language families of the Caucasus. The Kartvelian languages are double marking, with nominal case and two sets of person markers in the verb. Since the 17th century, linguists have attempted to accommodate the complexities of Georgian morphosyntax within the descriptive categories of their time, successively describing the language as nominative, (split) ergative, and active/inactive. In the present chapter, I will argue that its alignment can be most accurately described as split-intransitive, once the considerable number of monovalent dative-subject verbs are brought into consideration. Proto-Kartvelian would have had split-intransitive verb agreement, absolutively aligned verbal plurality marking, and incipient ergative-absolutive case assignment. Also discussed is the morphosyntactic orientation of the Kartvelian languages and dialects, that is, the distribution of morphological and syntactic privileges among the clausal arguments.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.035
GPT teacher head0.212
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2017
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicSyntax, Semantics, Linguistic VariationFrench-language works237,207