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Record W4388523995 · doi:10.1007/s11049-023-09587-0

Semantic agreement in Russian: Gender, declension, and morphological ineffability

2023· article· en· W4388523995 on OpenAlex
Mariia Privizentseva

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNatural Language & Linguistic Theory · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsnot available
FundersUniversité de FribourgAlbert-Ludwigs-Universität FreiburgDeutsche ForschungsgemeinschaftUniversität LeipzigUniversité du Québec à Montréal
KeywordsAgreementReferentLinguisticsArgument (complex analysis)VocabularySyntaxNounSemantics (computer science)Noun phrasePhilosophyComputer sciencePsychologyMedicine

Abstract

fetched live from OpenAlex

Abstract In this paper, I argue that declension classes are not primitives (see Aronoff 1994; Alexiadou 2004; Kramer 2015; i.a.), but are decomposed into simpler features, one of which is gender (Harris 1991; Wiese 2004; Caha 2019). The argument is based on semantic gender agreement in Russian, where a grammatically masculine noun can trigger feminine agreement if its referent is female (Mučnik 1971; Pesetsky 2013). Semantic agreement is grammatical only in those forms where a regular nominal exponent is syncretic with an exponent of a declension class that includes feminine nouns. In other forms, conflicting masculine and feminine gender features lead to ineffability in morphology (cf. Schütze 2003; Asarina 2011; Coon and Keine 2020). Ineffability arises because the Subset Principle (Halle 1997) that holds between features of a vocabulary item and a terminal at the point of Vocabulary Insertion is violated later in the derivation. This is in turn possible if Vocabulary Insertion applying cyclically bottom-up (Bobaljik 2000) is interleaved with Lowering that alters structure below a triggering node (Embick and Noyer 2001). Finally, I show that Russian also has a number of cases where conflicting gender features in a noun phrase do not result in a realization failure (Iomdin 1980). The difference between these patterns is derived in a principled way and follows from the positions where conflicting features are introduced.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.265
Teacher spread0.241 · 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