Bivalent verb classes across Slavic: areal and genealogical patterns

Abstract The Slavic languages, shaped by a complex history of divergence and contact, offer an ideal setting for investigating how genealogical and areal factors influence valency class systems. These systems, marked by diachronic instability, reflect both internal linguistic developments and external pressures. Drawing on data from BivalTyp, a typological database of bivalent verbs and their coding frames ( https://bivaltyp.info/ ), this study analyzes the argument-coding properties of 130 bivalent predicates (e.g., ‘hit’, ‘know’, ‘be afraid’, ‘look’, ‘resemble’) across 11 Slavic standard varieties: Belarusian, Bulgarian, Croatian, Czech, Macedonian, Polish, Russian, Serbian, Slovak, Slovenian, and Ukrainian. The dataset is annotated for argument-coding devices, such as cases and adpositions, as well as for cognacy relations between verbs and argument-coding devices. These annotations serve as the basis for constructing distance matrices that reveal patterns of similarity and divergence among Slavic languages in various subsystems of argument coding, with syntactic dimensions partially independent of the cognacy relations of the verbs involved. The findings highlight the significant role of areal factors in shaping valency classes in Slavic languages, often surpassing genealogical influences. This is evident in the systematic convergence between Polish and East Slavic languages and in broader areal trends, where Slavic languages exhibit syntactic convergences with neighboring non-Slavic languages.

Authors

Institutions

Publication Details

Journal
Russian Linguistics
Published
2025-10-03
DOI
https://doi.org/10.1007/s11185-025-09322-w
Citations
1
Primary Topic
Linguistics and language evolution
Type
article
Field-Weighted Citation Impact
10.42

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bivalent verb classes across Slavic: areal and genealogical patterns

Sergey Say
1 citations
Russian Linguistics
Linguistics and language evolution
10.42
article

Bivalent verb classes across Slavic: areal and genealogical patterns

Sergey Say
article en
1 citations

Abstract

Abstract The Slavic languages, shaped by a complex history of divergence and contact, offer an ideal setting for investigating how genealogical and areal factors influence valency class systems. These systems, marked by diachronic instability, reflect both internal linguistic developments and external pressures. Drawing on data from BivalTyp, a typological database of bivalent verbs and their coding frames ( https://bivaltyp.info/ ), this study analyzes the argument-coding properties of 130 bivalent predicates (e.g., ‘hit’, ‘know’, ‘be afraid’, ‘look’, ‘resemble’) across 11 Slavic standard varieties: Belarusian, Bulgarian, Croatian, Czech, Macedonian, Polish, Russian, Serbian, Slovak, Slovenian, and Ukrainian. The dataset is annotated for argument-coding devices, such as cases and adpositions, as well as for cognacy relations between verbs and argument-coding devices. These annotations serve as the basis for constructing distance matrices that reveal patterns of similarity and divergence among Slavic languages in various subsystems of argument coding, with syntactic dimensions partially independent of the cognacy relations of the verbs involved. The findings highlight the significant role of areal factors in shaping valency classes in Slavic languages, often surpassing genealogical influences. This is evident in the systematic convergence between Polish and East Slavic languages and in broader areal trends, where Slavic languages exhibit syntactic convergences with neighboring non-Slavic languages.

Russian LinguisticsVol. 49(1)
University of Potsdam (DE)
Deutsche Forschungsgemeinschaft, Universität Potsdam
Openalex Percentile: Top 2%
Linguistics and language evolution
10.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.