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Problems for Judgment and Decision Making
Abstract
▪ Abstract This review examines recent developments during the past 5 years in the field of judgment and decision making, written in the form of a list of 16 research problems. Many of the problems involve natural extensions of traditional, originally rational, theories of decision making. Others are derived from descriptive algebraic modeling approaches or from recent developments in cognitive psychology and cognitive neuroscience. “Wir müssen wissen. Wir werden wissen.” (We must know. We will know.) David Hilbert, Mathematische Probleme ( 1900 )
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Metadata
- Authors
- Hastie, R.
- Venue
- Annual Review of Psychology
- Publisher
- Annual Reviews
- Published
- 2001-02
- Volume
- 52
- Issue
- 1
- Pages
- 653-683
- ISSN
- 0066-4308 (ISSN-L)
- 1545-2085
- OpenAlex
- W2171258393
- Cited by
- 522
- References
- 197
- FWCI
- 4.08
- Type
- journal article
- Language
- en
- Open access
- closed
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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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.