On the adequacy of current empirical evaluations of formal models of categorization
Bibliographic Data
| ID | 4424017 |
|---|---|
| Authors | A J Wills (0000-0003-4803-0367), Emmanuel M Pothos (0000-0003-1919-387X) |
| Year | 2012 |
| Volume | 138 |
| Issue | 1 |
| Pages | 102-125 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Psychological Bulletin (JOURNAL) |
| Journal identifiers | ISSN: 0033-2909 • E-ISSN: 1939-1455 |
| Publisher | American Psychological Association (APA) (PUBLISHER) |
| DOI | 10.1037/a0025715 |
| PMID | 22061692 |
| OpenAlex | W2129038834 |
| Language | EN |
| Citations received | 12 |
Categorization is one of the fundamental building blocks of cognition, and the study of categorization is notable for the extent to which formal modeling has been a central and influential component of research. However, the field has seen a proliferation of noncomplementary models with little consensus on the relative adequacy of these accounts. Progress in assessing the relative adequacy of formal categorization models has, to date, been limited because (a) formal model comparisons are narrow in the number of models and phenomena considered and (b) models do not often clearly define their explanatory scope. Progress is further hampered by the practice of fitting models with arbitrarily variable parameters to each data set independently. Reviewing examples of good practice in the literature, we conclude that model comparisons are most fruitful when relative adequacy is assessed by comparing well-defined models on the basis of the number and proportion of irreversible, ordinal, penetrable successes (principles of minimal flexibility, breadth, good-enough precision, maximal simplicity, and psychological focus
Categorical variable · Categorization · Cognition · Cognitive psychology · Econometrics · Epistemology · Flexibility (engineering · Machine learning · Scope (computer science · Set (abstract data type · Simplicity · Statistics · Categorization, perception, and language · Child and Animal Learning Development · Cognitive Science and Mapping · Computer Science · Mathematics · Psychology · Artificial Intelligence
The Bayesian evaluation of categorization models
Benchmarks for models of short-term and working memory
On the adequacy of Bayesian evaluations of categorization models
Addressing the theory crisis in psychology
Is Man the Measure of All Things? A Social Cognitive Account of Androcentrism
Attention and associative learning in humans
Disentangling Perceptual and Process-Related Sources of Behavioral Variability in Categorization
How Computational Modeling Can Force Theory Building in Psychological Science
Reconciling category exceptions through representational shifts
Featural relations in concept learning and generalization
Effects of categorical and numerical feedback on category learning
Transfer of a novel discriminative function across functional stimulus class members in rats
| Unique citing works | 12 |
|---|---|
| Citations per year | 0,86 |
| Citation span | 2012 - 2025 (14) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 9 |