The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
The Lexical Constituency Model: Some Implications of Research on Chinese for General Theories of Reading.
Abstract
The authors examine the implications of research on Chinese for theories of reading and propose the lexical constituency model as a general framework for word reading across writing systems. Word identities are defined by 3 interlinked constituents (orthographic, phonological, and semantic). The implemented model simulates the time course of graphic, phonological, and semantic priming effects, including immediate graphic facilitation followed by graphic inhibition with simultaneous phonological facilitation, a pattern unique to the Chinese writing system. Pseudocharacter primes produced only facilitation, supporting the model's assumption that lexical thresholds determine phonological and semantic, but not graphic, effects. More generally, both universal reading processes and writing system constraints exist. Although phonology is universal, its activation process depends on how the writing system structures graphic units.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
DRC: A dual route cascaded model of visual word recognition and reading aloud.
Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001) · Psychological Review · doi:10.1037/0033-295x.108.1.204 · Cited by 4,500
A distributed, developmental model of word recognition and naming.
Seidenberg, M. S., & McClelland, J. L. (1989) · Psychological Review · doi:10.1037/0033-295x.96.4.523 · Cited by 3,909
Understanding normal and impaired word reading: Computational principles in quasi-regular domains.
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1996) · Psychological Review · doi:10.1037/0033-295x.103.1.56 · Cited by 2,698
Models of reading aloud: Dual-route and parallel-distributed-processing approaches.
Coltheart, M., Curtis, B., Atkins, P., & Haller, M. (1993) · Psychological Review · doi:10.1037//0033-295x.100.4.589 · Cited by 1,798
(1978) · Medical Entomology and Zoology · Cited by 1,064
Orthographic processing in visual word recognition: A multiple read-out model.
Grainger, J., & Jacobs, A. M. (1996) · Psychological Review · doi:10.1037/0033-295x.103.3.518 · Cited by 947
Phonology, reading acquisition, and dyslexia: Insights from connectionist models.
Harm, M. W., & Seidenberg, M. S. (1999) · Psychological Review · doi:10.1037/0033-295x.106.3.491 · Cited by 927
A ROWS is a ROSE: Spelling, sound, and reading
van Orden, G. C. (1987) · Memory & Cognition · doi:10.3758/bf03197716 · Cited by 867 · cited 1×
“In their dynamic systems approach, Van Orden and Goldinger (1994) have also proposed this priority of phonology over meaning.”
BackgroundStrategies of Information Processing
D., C. P., & Underwood, G. (1980) · The American Journal of Psychology · doi:10.2307/1422114 · Cited by 857
Strategies of information processing
Hemsley, D. R. (1980) · Behaviour Research and Therapy · doi:10.1016/0005-7967(80)90029-7 · Cited by 830
Cited by
Share, D. L. (2008) · Psychological Bulletin · doi:10.1037/0033-2909.134.4.584 · Cited by 1,022
Wong, A. C.-N., Jobard, G., James, K. H., James, T. W., & Gauthier, I. (2009) · Cognitive Neuropsychology · doi:10.1080/02643290802340972 · Cited by 85
Cross-Language Transfer of Reading Ability: Evidence From Taiwanese Ninth-Grade Adolescents
Chuang, H.-K., Joshi, R. M., & Dixon, L. Q. (2012) · Journal of Literacy Research · doi:10.1177/1086296x11431157 · Cited by 74
Zhou, Z., Graham, S., & Hsiang, T. P. (2023) · Reading and Writing · doi:10.1007/s11145-022-10398-9 · Cited by 1
Metadata
- Authors
- Perfetti, C. A., Liu, Y., & Tan, L. H.
- Venue
- Psychological Review
- Published
- 2005
- Volume
- 112
- Issue
- 1
- Pages
- 43-59
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2100333970
- Cited by
- 508
- References
- 73
- FWCI
- 27.87
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Lexical Constituency Model: Some Implications of Research on Chinese for General Theories of Reading. https://app.cochat.ai/papers/10.1037/0033-295x.112.1.43
- The paper
- Perfetti, C. A., Liu, Y., & Tan, L. H. (2005). The Lexical Constituency Model: Some Implications of Research on Chinese for General Theories of Reading. Psychological Review. https://doi.org/10.1037/0033-295x.112.1.43
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.