Coherence and correspondence in the psychological analysis of numerical predictions
Numerical predictions are of central interest for both coherence-based approaches to judgment and decisions --- the Heuristic and Biases (HB) program in particular --- and to correspondence-based approaches --- Social Judgment Theory (SJT). In this paper I examine the way these two approaches study...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2009-03-01
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| Series: | Judgment and Decision Making |
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| Online Access: | http://journal.sjdm.org/ccg/ccg.pdf |
| _version_ | 1797766341454725120 |
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| author | Yoav Ganzach |
| author_facet | Yoav Ganzach |
| author_sort | Yoav Ganzach |
| collection | DOAJ |
| description | Numerical predictions are of central interest for both coherence-based approaches to judgment and decisions --- the Heuristic and Biases (HB) program in particular --- and to correspondence-based approaches --- Social Judgment Theory (SJT). In this paper I examine the way these two approaches study numerical predictions by reviewing papers that use Cue Probability Learning (CPL), the central experimental paradigm for studying numerical predictions in the SJT tradition, while attempting to look for heuristics and biases. The theme underlying this review is that both bias-prone heuristics and adaptive heuristics govern subjects' predictions in CPL. When they have little experience to guide them, subjects fall prey to relying on bias-prone natural heuristics, such as representativeness and anchoring and adjustment, which are the only prediction strategies available to them. But, as they acquire experience with the prediction task, these heuristics are abandoned and replaced by ecologically valid heuristics. |
| first_indexed | 2024-03-12T20:23:53Z |
| format | Article |
| id | doaj.art-e0aa517df1384e8b8f25e43f1a4a9f6a |
| institution | Directory Open Access Journal |
| issn | 1930-2975 |
| language | English |
| last_indexed | 2024-03-12T20:23:53Z |
| publishDate | 2009-03-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Judgment and Decision Making |
| spelling | doaj.art-e0aa517df1384e8b8f25e43f1a4a9f6a2023-08-02T00:44:30ZengCambridge University PressJudgment and Decision Making1930-29752009-03-0142175185Coherence and correspondence in the psychological analysis of numerical predictionsYoav GanzachNumerical predictions are of central interest for both coherence-based approaches to judgment and decisions --- the Heuristic and Biases (HB) program in particular --- and to correspondence-based approaches --- Social Judgment Theory (SJT). In this paper I examine the way these two approaches study numerical predictions by reviewing papers that use Cue Probability Learning (CPL), the central experimental paradigm for studying numerical predictions in the SJT tradition, while attempting to look for heuristics and biases. The theme underlying this review is that both bias-prone heuristics and adaptive heuristics govern subjects' predictions in CPL. When they have little experience to guide them, subjects fall prey to relying on bias-prone natural heuristics, such as representativeness and anchoring and adjustment, which are the only prediction strategies available to them. But, as they acquire experience with the prediction task, these heuristics are abandoned and replaced by ecologically valid heuristics.http://journal.sjdm.org/ccg/ccg.pdfnumerical predictionsocial judgment theorycue probabilitylearningheuristics and biases. |
| spellingShingle | Yoav Ganzach Coherence and correspondence in the psychological analysis of numerical predictions Judgment and Decision Making numerical prediction social judgment theory cue probabilitylearning heuristics and biases. |
| title | Coherence and correspondence in the psychological analysis of numerical predictions |
| title_full | Coherence and correspondence in the psychological analysis of numerical predictions |
| title_fullStr | Coherence and correspondence in the psychological analysis of numerical predictions |
| title_full_unstemmed | Coherence and correspondence in the psychological analysis of numerical predictions |
| title_short | Coherence and correspondence in the psychological analysis of numerical predictions |
| title_sort | coherence and correspondence in the psychological analysis of numerical predictions |
| topic | numerical prediction social judgment theory cue probabilitylearning heuristics and biases. |
| url | http://journal.sjdm.org/ccg/ccg.pdf |
| work_keys_str_mv | AT yoavganzach coherenceandcorrespondenceinthepsychologicalanalysisofnumericalpredictions |