The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Seeing it their way: Evidence for rapid and involuntary computation of what other people see.
Abstract
In a series of three visual perspective-taking experiments, we asked adult participants to judge their own or someone else's visual perspective in situations where both perspectives were either the same or different. We found that participants could not easily ignore what someone else saw when making self-perspective judgments. This was observed even when participants were only required to take their own perspective within the same block of trials (Experiment 2) or even within the entire experiment (Experiment 3), i.e. under conditions which gave participants a clear opportunity to adopt a strategy of ignoring the other person's irrelevant perspective. Under some circumstances, participants were also more efficient at judging the other person's perspective than at judging their own perspective. Collectively, these results suggest that adults make use of rapid and efficient processes to compute what other people can see.
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Cites
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Cited by
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Apperly, I. A., & Butterfill, S. A. (2009) · Psychological Review · doi:10.1037/a0016923 · Cited by 1,261
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Metadata
- Authors
- Samson, D., Apperly, I. A., Braithwaite, J. J., Andrews, B. J., & Bodley Scott, S. E.
- Venue
- Journal of Experimental Psychology: Human Perception and Performance
- Published
- 2010-10
- Volume
- 36
- Issue
- 5
- Pages
- 1255-1266
- ISSN
- 0096-1523 (ISSN-L)
- 1939-1277
- OpenAlex
- W2105741723
- Cited by
- 733
- References
- 32
- FWCI
- 46.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- Samson, D., Apperly, I. A., Braithwaite, J. J., Andrews, B. J., & Bodley Scott, S. E. (2010). Seeing it their way: Evidence for rapid and involuntary computation of what other people see. Journal of Experimental Psychology: Human Perception and Performance. https://doi.org/10.1037/a0018729
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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.