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The dilution effect: Nondiagnostic information weakens the implications of diagnostic information
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“When individuals make judgments, the dilution effect occurs when people fail to use diagnostic information in the presence of nondiagnostic information (Nisbett et al., 1981).”
From Setting the future of digital and social media marketing research: Perspectives and research propositions (2021) · cites this paper as Nisbett et al., 1981
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“This may (temporarily) ‘‘dilute’’ (see Nisbett, Zukier, & Lemley, 1981 ) the existing stereotype (e.g., ‘‘not only women but also some men are dependent’’) and/or activate a specific subtype (e.g., ‘‘most men are not dependent, but some men are’’; see Hewstone, 1994).”
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“These inputs therefore form the most appropriate and normative information to be used in the judgment task [44, 51].”
Background
Metadata
- Authors
- Nisbett, R. E., Zukier, H., & Lemley, R. E.
- Affiliations
- University of Michigan (US)
- The New School (US)
- Corresponding author
- Nisbett, Richard E.
- Venue
- Cognitive Psychology
- Publisher
- Elsevier BV
- Published
- 1981-04
- Volume
- 13
- Issue
- 2
- Pages
- 248-277
- ISSN
- 0010-0285 (ISSN-L)
- OpenAlex
- W2171421397
- Cited by
- 605
- References
- 16
- Citations by year
- 2026: 9 · 2025: 11 · 2024: 17 · 2023: 13 · 2022: 11 · 2021: 20 · 2020: 48 · 2019: 19 · 2018: 23 · 2017: 16 · 2016: 20 · 2015: 20 · 2014: 17 · 2013: 19 · 2012: 14
- FWCI
- 26.90
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- Cognitive Psychology (publishedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- dilution effect, diagnostic information, prediction, similarity judgments, stereotypes, individuating information
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 ›
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