Chapter 7: Concepts & Categorization Flashcards
Concepts
Mental representation of some object, event, or pattern that has stored in it much of the knowledge typically thought relevant to that object, event, pattern
Categorization
Process by which things are placed into groups called categories
Category
Class or group of similar things (objects or entities)
Functions of Categorization
Understand individual cases you have not seen before and make inferences about them
Reduces complexity of environment
Requires less learning/memorization
Guide to appropriate action
Theoretical Descriptions of Concepts
Classical view
Prototype view
Exemplar view
Schemata view
Knowledge-based view
The Classical View
Category membership determined by a set of defining (necessary and sufficient) properties
Individually Necessary
Each example must have the feature if it is to be regarded as a member of the concept
E.g. ‘has three sides’ is necessary for concept of triangle
Collectively Sufficient
Anything with each feature in the set is automatically an instance of the concept
E.g. the set of features ‘has three sides’ and ‘closed geometric figure’ is sufficient to specify a triangle (anything that has both is a triangle)
Implications of Classical View
Assumes that concepts mentally represent lists of features/characteristics (not representations of specific examples)
Assumes that membership in a category is clear cut (all in or all out)
Implies that all members within a category are created equal (no such thing as better or worse triangle)
Weaknesses of Classical View
Participants are often inconsistent when judging items to be in certain categories
No defining features for many natural-kind categories (e.g. games, we have olympic games, ball games, card games, etc)
Typicality (graded membership)
The Prototype View
Prototypes of concepts include features or aspects that are characteristic (typical) of members of category
Denies existence of necessary and sufficient feature lists
Prototypes
Idealized representations of some class of objects or events
Abstraction that includes all characteristic features of a category (rather than necessary or sufficient levels)
May or may not be an actual instance of the category
Formed by averaging the category members we have encountered in the past
Members within a category differ in terms of prototypicality
Family Resemblance Structure of Concepts
Structure in which each member has a number of features, sharing different features with different members
Few if any features are shared by every single member of the category
More features a member possesses, the more typical it is
Typical examples classified fastest
Basic Categorization Levels
Basic levels include members that are maximally similar to each other (e.g. guitars)
Superordinate levels (e.g. musical instruments) of categories contain members that are dissimilar in several respects (e.g. pianos and guitars)
Subordinate levels are specific (e.g. classical guitar, folk guitar)
Pros of Prototype Theory
Explains why certain members of category are seen as more typical
Explains why people have hard time providing strict definitions of concepts
Problems With Prototype Theory
Variable categories for some things (e.g. games)
Fails to capture people’s knowledge about the limits of conceptual boundaries
Typicality of an instance depends to some extent on context (typicality is not fixed)
The Exemplar View
Concepts include representations of at least some actual individual instances
Assumes that people categorize new instances by comparing them to representations of actual instances
Pros of Exemplar View
Explains people’s inability to state necessary and defining features (because there are none to be stated )
Explains why people have difficulty categorizing unclear and atypical instances
Explains why people are faster to process info about typical instances
Problems With Exemplar View
Fails to specify which instances will be exemplars
Does not explain how different exemplars are called to mind at time of categorization
Difficulty accommodating data from large and complex categories
Does not specify which exemplars will be used for categorization
Requires that we store lots of exemplars (unconstrained)
The Schemata View
Concepts are schemata
Schemata can embed themselves in one another hierarchically (schemas have subschemata or superschemata)
Pros of Schematic View
Schemata involve both abstractions across instances (prototype view) and info about actual instances (exemplar view)
Problems With Schematic View
Does not specify clear boundaries among individual schemata
Not sufficiently delineated to be empirically testable
The Knowledge-Based View
Person uses their knowledge of how the concept is organized to justify classification and to explain why certain instances happen to go in same category
Person classifying objects and events doesn’t just compare features or physical aspects to features or aspects of stored representations
Category becomes coherent only when you know the purpose of the category (e.g. things to save from fire)
Similarities Between Schemata, Prototype, & Exemplar Views
Schemata and prototypes store information that is abstracted across instances
Schemata and exemplars store info about actual instances
