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ERIC Number: EJ1404235
Record Type: Journal
Publication Date: 2023
Pages: 21
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0163-853X
EISSN: EISSN-1532-6950
Eye-Tracking Evidence from Attachment Structures Favors a Serial Model of Discourse-Sentence Interactivity
Jack Dempsey; Anna Tsiola; Kiel Christianson
Discourse Processes: A Multidisciplinary Journal, v60 n9 p613-633 2023
Many psycholinguistic studies examine how people parse sentences in isolation; however, years of work in discourse processing have shown that sentence-level interpretations are influenced at some stage by discourse-level information. Evidence over the past 20 years remains mixed as to the temporal dynamics of such top-down interactions. In particular, dynamic accounts where readers use the discourse model to generate expectations for certain grammatical structures before and during parsing differ from serial accounts where an algorithmic first-pass processing mechanism precedes integration of sentence material into the discourse model. To test between these two theories, the current study investigates eye-movement behaviors when reading temporarily ambiguous attachment structures following discourses with biases either matching, mismatching, or neutral with respect to the attachment resolution. No evidence was found suggesting readers systematically use discourse information to generate structural expectations, in line with serial accounts of processing at the sentence-discourse interface. Scanpath analyses further highlight the confirmatory nature of rereading when participants encounter discourse continuations that do not fit with prior contexts.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Illinois
Grant or Contract Numbers: N/A
Data File: URL: https://osf.io/gfjn6/