Toward a theory of automatic information processing in reading
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Speed in word reading is a factor in assessment of reading and has consistently documented its relation with comprehension.
“Speed in word reading again is a factor in assessment of reading and has long been of interest to researchers [100] and over the years consistently documented its relation with comprehension [101].”
From Curriculum-Based Measurement: A Brief History of Nearly Everything from the 1970s to the Present (2013) · cites this paper as [101]
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References 47 · Cited by 3,841
- Authors
- LaBerge, D., & Samuels, S. J.
- Affiliations
- University of Minnesota (US)
- Corresponding author
- LaBerge, David
- Venue
- Cognitive Psychology
- Publisher
- Elsevier BV
- Published
- 1974-04
- Volume
- 6
- Issue
- 2
- Pages
- 293-323
- ISSN
- 0010-0285 (ISSN-L)
- OpenAlex
- W2045597501
- Cited by
- 3,841
- References
- 47
- Citations by year
- 2026: 87 · 2025: 90 · 2024: 112 · 2023: 88 · 2022: 110 · 2021: 127 · 2020: 131 · 2019: 160 · 2018: 117 · 2017: 121 · 2016: 121 · 2015: 147 · 2014: 146 · 2013: 127 · 2012: 131
- FWCI
- 41.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognitive Psychology (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Keywords
- reading, automaticity, information processing model, visual processing, phonological processing, episodic memory, semantic understanding, perceptual learning, associative learning, attention, reading development
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.
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