An Organic Syntactic Complexity Measure for the Chinese Language: The TC-Unit

Autor/in	Yu, Qiaona
Titel	An Organic Syntactic Complexity Measure for the Chinese Language: The TC-Unit
Quelle	In: Applied Linguistics, 42 (2021) 1, S.60-92 (33 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0142-6001
DOI	10.1093/applin/amz064
Schlagwörter	Chinese; Difficulty Level; Syntax; Language Proficiency; Language Tests; Timed Tests; Discriminant Analysis + Suchen Sie Ihr Suchwort? China; Chinesen; Schwierigkeitsgrad; Language skill; Language skills; Sprachkompetenz; Language test; Sprachtest; Diskriminanzanalyse
Abstract	Language complexity reveals the ability to use a wide and varied range of sophisticated structures and vocabulary. Although different languages compose complexity differently, complexity measures such as the T-unit have typically been based on clause subordination, which may underrepresent complexity and threaten the validity of studies. This study argues that an organic complexity measure should avoid the assumption of clause subordination and instead consider the typological features of the target language. Therefore, this study proposes the TC-unit in recognition of the "topic chain" as the underlying unit of Chinese complexity. It further validates TC-unit-based measures by investigating how accurately they predict proficiency group membership. Discriminant analyses of L1 and L2 Chinese speakers' spoken (N = 115) and written (N = 116) output elicited from a designed timed online test, revealed that TC-unit-based measures classified proficiency group membership with high efficiency (61.2-75.7 per cent). Mean length of terminable TC-unit proved the most effective indicator of spoken Chinese syntactic complexity, while mean length of terminable TC-unit and single TC-units per terminable TC-unit in combination proved the most effective for written Chinese syntactic complexity. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01