Probabilistic mental models: a Brunswikian theory of confidence.
By Gerd Gigerenzer, Ulrich Hoffrage, Heinz Kleinbölting. 1991
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Gerd Gigerenzer
- Robin M. Hogarth
- Peter M. Todd
- Ralph Hertwig
- A. Glöckner
- Daniel G. Goldstein
- K. Stanovich
- T. Betsch
Citations in the corpus
- Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, neutral): “…Erlich, 1996; Friedman, forbus, and Sherin, 2018; Friedman and Nissenbaum, 1996; Gary and Wood, 2011; Gentner and Stevens, 1983; Gigerenzer, 1993; Gigerenzer, Hoffrage, and Kleinbölting, 1991; Halasz, and Moran, 1983; Hegarty, 2004; Hegarty, Just, and Morrison, 1987; Heller, 1994; Hilton, 1986,…”
- The recognition heuristic: A decade of research (2011, methodology): “With certain knowledge about the criterion, no inference may be needed—one might simply make deductions using a local mental model (see Gigerenzer et al., 1991, Figure 2).”
- Reasoning the fast and frugal way: models of bounded rationality. (1996, methodology): “…from the framework of PMM theory have been successful in integrating various striking phenomena in inference from memory and predicting novel phenomena, such as the confidence-frequency effect (Gigerenzer et al., 1991) and the less-is-more effect (Goldstein, 1994; Goldstein & Gigerenzer, 1996).”
- The Effect of Incentive Contracts on Learning and Performance (2000, background): “…and Plott (1979), Grether (1980), Thaler (1986), Tversky and Kahneman (1986), Dawes (1988), Wright and Anderson (1989), Awasthi and Pratt (1990), Gigerenzer et al. (1991), Henry and Sniezek (1993), Salvemini et al. (1993), Wright et al. (1993), Henry (1994), Pelham and Neter (1995), Byram…”
- Overconfidence in investment decisions: An experimental approach (2005, background): “…strategies (e.g., Koriat et al. 1980), by motivational factors (e.g., Langer 1975), by imperfections in learning (e.g., Erev et al. 1994, Ferrell 1994), and, for instance, by the experimenters’ tendency to choose harder-than-normal questions (e.g., Gigerenzer et al. 1991, Juslin 1993, 1994).”