title: Metrics and mappings: a framework for understanding real-world quantitative estimation.
abstract: Estimation is influenced by a variety of processes: application of heuristics, domain-specific reasoning, and intuitive statistical induction, among them. In this article, we propose the metrics and mapping framework to account for how these processes are integrated to generate estimates. This framework identifies 2 types of information as critical: knowledge of distributional properties (metric knowledge) and knowledge of relative status of individual entities within the distribution (mapping knowledge). Heuristics and domain-specific knowledge are both viewed as cues that contribute to mapping knowledge; intuitive statistical induction is viewed as providing cues to metric properties. Results of 4 experiments illustrate the framework's usefulness for integrating these types of information and for predicting when people emphasize heuristics and when they emphasize domain-specific knowledge.
authors.affiliation: Department of Psychology, University of Alberta, Edmonton, Canada.
authors.forename: N R
authors.initials: NR
authors.lastname: Brown
authors.forename: R S
authors.initials: RS
authors.lastname: Siegler
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003210:Concept Formation; D003657:Decision Making; D005260:Female; D006801:Humans; D007721:Knowledge of Results, Psychological; D008297:Male; D008875:Middle Aged; D011156:Population Density; D013690:Television