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
Categorization Involves
Knowledge of how concepts are organized
The purpose of the category
People’s theories about the world
Expectation
Cognitive Economy of Mental Representation
Save on mental resources by limiting amount of info we must store
If treat every object as unique, we would not be using cognitive resources economically
If categorize all objects in one category, it wouldn’t be informative
Categorization must strike a balance between cognitive economy and informative-ness
Similarity Based Conceptual Structure
Classical, prototype, exemplar (some parts of schemata/scripts view)
Approaches in which categorization is assumed to be based on similarity of an instance to some abstract specification of category or store examples
BUT similarity is meaningful only in certain respects (e.g. plum and lawnmower both weigh less than 100kg)
Explanation Based Conceptual Structure
Knowledge based (some of schemata/scripts view)
People seen as basing classifications on meaningful relationships among instances and categories
Concept Attainment Strategies
Simultaneous scanning
Successive scanning
Conservative focusing
Simultaneous Scanning
Use each card to test and rule out multiple hypotheses
Test multiple hypotheses at the same time
Difficult to use and makes heavy demands on working memory
Successive Scanning
Testing one hypothesis at a time
E.g. try to see if concept is black figures, then try next idea
Less efficient than simultaneous, but more cognitively manageable
Conservative Focusing
Finding a card that illustrated the concept, then testing other cards that varied from it in only one aspect
Efficient and easy, but unless cards are laid out in orderly fashion it may be difficult to carry out
Artificial Grammar
Sequences of letters generated by an artificial grammar or random sequences
People learned/recalled/categorized better in artificial grammar condition
Participants couldn’t;t explicitly state underlying grammar rules
Demonstrates non-analytical/unconscious/implicit learning
More complex tasks are sometimes easier accomplished implicitly
Acquiring Concepts in the Brain
Participants had to sort abstract drawings by two fictional painters
Given feedback after each trial
Brain activations limited to frontal and parietal regions in RH
-Early classification mainly involves processing of visual patterns without application of rules
As learning progresses regions in LH become active (parietal and dorsolateral prefrontal)
-Result of formulation and application of abstract rules
Also used basal ganglia for categorization
Psychological Essentialism
People generally act as if objects, people, events have certain essences or underlying natures that make them what they are
Nominal kind
Natural kind
Artifact
Nominal-Kind Concepts
Concepts with clear definitions
Info about necessary and sufficient features, because these exist as part of the concept definition
Natural Kind Concepts
Things naturally occuring in same environment
Info about definitional or essential features
More likely to have a family resemblance structure
Can be equally well explained within a knowledge based approach
Artifact Concepts
Things constructed to serve some function or accomplish some task
Highlight info about object’s purpose or function
Can be adequately described only within the knowledge based approach
