The DOI matches its OpenAlex record; 2 of the 2 references it cites were found in a registry or an index.
Prototypicality, distinctiveness, and intercorrelation: Analyses of the semantic attributes of living and nonliving concepts
Open accessAbstract
Many cognitive psychological, computational, and neuropsychological approaches to the organisation of semantic memory have incorporated the idea that concepts are, at least partly, represented in terms of their fine-grained features. We asked 20 normal volunteers to provide properties of 64 concrete items, drawn from living and nonliving categories, by completing simple sentence stems (e.g., an owl is __, has __, can__). At a later date, the same participants rated the same concepts for prototypicality and familiarity. The features generated were classified as to type of knowledge (sensory, functional, or encyclopaedic), and also quantified with regard to both dominance (the number of participants specifying that property for that concept) and distinctiveness (the proportion of exemplars within a conceptual category of which that feature was considered characteristic). The results demonstrate that rated prototypicality is related to both the familiarity of the concept and its distance from the average of the exemplars within the same category (the category centroid). The feature database was also used to replicate, resolve, and extend a variety of previous observations on the structure of semantic representations. Specifically, the results of our analyses (1) resolve two conflicting claims regarding the relative ratio of sensory to other kinds of attributes in living vs. nonliving concepts; (2) offer new information regarding the types of features-across different domains-that distinguish concepts from their category coordinates; and (3) corroborate some previous claims of higher intercorrelations between features of living things than those of artefacts.
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
From Neuropsychology to Mental Structure
Shallice, T. (1988) · doi:10.1017/cbo9780511526817 · Cited by 4,072
Concepts, Kinds, and Cognitive Development
Keil, F. C. (1989) · doi:10.7551/mitpress/2065.001.0001 · Cited by 1,886
Cited by
Where do you know what you know? The representation of semantic knowledge in the human brain
Patterson, K., Nestor, P. J., & Rogers, T. T. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2277 · Cited by 2,706
Self-citationThe neural and computational bases of semantic cognition
Ralph, M. A. L., Jefferies, E., Patterson, K., & Rogers, T. T. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.150 · Cited by 1,864
Self-citationRogers, T. T., Lambon Ralph, M. A., Garrard, P., Bozeat, S., McClelland, J. L., Hodges, J. R., & Patterson, K. (2004) · Psychological Review · doi:10.1037/0033-295x.111.1.205 · Cited by 948
Self-citationNon-verbal semantic impairment in semantic dementia
Bozeat, S., Lambon Ralph, M. A., Patterson, K., Garrard, P., & Hodges, J. R. (2000) · Neuropsychologia · doi:10.1016/s0028-3932(00)00034-8 · Cited by 884
Self-citationDistributional Memory: A General Framework for Corpus-Based Semantics
Baroni, M., & Lenci, A. (2010) · Computational Linguistics · doi:10.1162/coli_a_00016 · Cited by 659
Metadata
- Authors
- Garrard, P., Ralph, M. A. L., Hodges, J. R., & Patterson, K. E.
- Venue
- Cognitive Neuropsychology
- Publisher
- Taylor & Francis
- Published
- 2001-03-01
- Volume
- 18
- Issue
- 2
- Pages
- 125-174
- ISSN
- 0264-3294 (ISSN-L)
- OpenAlex
- W2141305710
- Cited by
- 298
- References
- 2
- FWCI
- 18.59
- Type
- journal article
- Language
- en
- Open access
- green
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: Prototypicality, distinctiveness, and intercorrelation: Analyses of the semantic attributes of living and nonliving concepts. https://app.cochat.ai/papers/10.1080/02643290042000053
- The paper
- Garrard, P., Ralph, M. A. L., Hodges, J. R., & Patterson, K. E. (2001). Prototypicality, distinctiveness, and intercorrelation: Analyses of the semantic attributes of living and nonliving concepts. Cognitive Neuropsychology. https://doi.org/10.1080/02643290042000053
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.