The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Social Attribution and Explanation
Abstract
Attribution processes appear to be an integral part of human visual perception, as low-level inferences of causality and intentionality appear to be automatic and are supported by specific brain systems. However, higher-order attribution processes use information held in memory or made present at the time of judgment. While attribution processes about social objects are sometimes biased, there is scope for partial correction. This chapter reviews work on the generation, communication, and interpretation of complex explanations, with reference to explanation-based models of text understanding that result in situation models of narratives. It distinguishes between causal connection and causal selection, and suggests that a factor will be discounted if it is not perceived to be connected to the event and backgrounded if it is perceived to be causally connected to that event, but is not selected as relevant to an explanation. The final section focuses on how interpersonal explanation processes constrain causal selection.
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“these explanations are not only known to be incomplete, often omitting crucial parts of the causal chain for a particular event (Lombrozo, 2006;Hilton, 2017)”
From Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting (2023) · cites this paper as Hilton, 2017
Citations
Cites
An Experimental Study of Apparent Behavior
Heider, F., & Simmel, M. (1944) · The American Journal of Psychology · doi:10.2307/1416950 · Cited by 3,340
Social cognition and the brain: A meta-analysis
Van Overwalle, F. (2009) · Human Brain Mapping · doi:10.1002/hbm.20547 · Cited by 1,792
How People Explain Behavior: A New Theoretical Framework
Malle, B. F. (1999) · Personality and Social Psychology Review · doi:10.1207/s15327957pspr0301_2 · Cited by 538
Cited by
Sorted by citations
Explanation in artificial intelligence: Insights from the social sciences
Miller, T. (2019) · Artificial Intelligence · doi:10.1016/j.artint.2018.07.007 · Cited by 5,302
Turpin, M., Michael, J., Perez, E., & Bowman, S. R. (2023) · arXiv · doi:10.48550/arxiv.2305.04388 · Cited by 262
“…human-written explanations, these explanations are not only known to be incomplete, often omitting crucial parts of the causal chain for a particular event (Lombrozo, 2006; Hilton, 2017), but they can also often be unfaithful accounts of individuals’ cognitive processes (Nisbett and Wilson, 1977).”
Background
Metadata
- Authors
- Hilton, D.
- Affiliations
- Université de Toulouse (FR)
- Corresponding author
- Hilton, Denis
- ORCID
- Hilton, Denis
- Venue
- Oxford Handbooks Online
- Publisher
- Oxford University Press
- Published
- 2017-05-10
- OpenAlex
- W2626312928
- Cited by
- 37
- References
- 3
- Citations by year
- 2025: 2 · 2024: 12 · 2023: 7 · 2022: 5 · 2021: 4 · 2020: 2 · 2019: 4 · 2018: 1
- FWCI
- 2.25
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Narrative Theory and Analysis
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- social attribution, explanation, causal relationship, causal selection, situation model, narrative comprehension, text understanding, backgrounding, intentionality, causality
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