Precise/not precise (PNP)
A Brunswikian model that uses judgment error distributions to identify cognitive processes
Bibliographic Data
| ID | 21640948 |
|---|---|
| Authors | Joakim Sundh (0000-0003-2451-6450, Uppsala University, corresponding author), August Collsiöö (0000-0002-6873-7987, Uppsala University), Philip Millroth (0000-0001-7943-508X, Uppsala University), Peter Juslin (0000-0001-9594-2153, Uppsala University) |
| Year | 2021 |
| Volume | 28 |
| Issue | 2 |
| Pages | 351-373 |
| Publication date | 2021-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychonomic Bulletin & Review (JOURNAL) |
| Journal identifiers | ISSN: 1069-9384 • E-ISSN: 1531-5320 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.3758/s13423-020-01805-9 |
| PMID | 32989718 |
| OpenAlex | W3089595907 |
| Language | EN |
| Citations received | 4 |
| References cited | 63 |
In 1956, Brunswik proposed a definition of what he called intuitive and analytic cognitive processes, not in terms of verbally specified properties, but operationally based on the observable error distributions. In the decades since, the diagnostic value of error distributions has generally been overlooked, arguably because of a long tradition to consider the error as exogenous (and irrelevant) to the process. Based on Brunswik’s ideas, we develop the precise/not precise (PNP) model, using a mixture distribution to model the proportion of error-perturbed versus error-free executions of an algorithm, to determine if Brunswik’s claims can be replicated and extended. In Experiment 1, we demonstrate that the PNP model recovers Brunswik’s distinction between perceptual and conceptual tasks. In Experiment 2, we show that also in symbolic tasks that involve no perceptual noise, the PNP model identifies both types of processes based on the error distributions. In Experiment 3, we apply the PNP model to confirm the often-assumed “quasi-rational” nature of the rule-based processes involved in multiple-cue judgment. The results demonstrate that the PNP model reliably identifies the two cognitive processes proposed by Brunswik, and often recovers the parameters of the process more effectively than a standard regression model with homogeneous Gaussian error, suggesting that the standard Gaussian assumption incorrectly specifies the error distribution in many tasks. We discuss the untapped potentials of using error distributions to identify cognitive processes and how the PNP model relates to, and can enlighten, debates on intuition and analysis in dual-systems theories
Cognition · Cognitive psychology · Cognitive science · Intuition · Perception · Child and Animal Learning Development · Cognitive Science and Mapping · Computer Science · Decision-Making and Behavioral Economics · Psychology · Artificial Intelligence
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| Unique citing works | 4 |
|---|---|
| Citations per year | 0,8 |
| Citation span | 2021 - 2025 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 4 |