Task 2 - Concepts and Categorization Flashcards
Concept
Mental representation of an object, event, or pattern that includes the knowledge deemed relevant to it.
e.g. dog: animal, four legs, tail, reputation, etc.
Category
Class of similar things (objects or entities) sharing either an essential core or some similarity in perceptual biological or functional properties
- things in category have common denominator
- organize our knowledge base
Similarity-based category theories
Classical View
Prototype View
Exemplar View
-> categorization based on similarity of instance to an abstract specification or one or more exemplars,
-> focus on superficial, perceptual information about a particular object
Explanation-based category theories
Schemata view
Knowledge-Based View
-> classification based on meaningful relationships among instances and categories
-> focus on deeper knowledge derived info about object
Prototype View
- no necessary-and-sufficient feature list
- objects are compared to prototype (more similar, higher prototypicality)
- > there are core representations but no rigid boundaries
- > basic, subordinate, superordinate levels of categories
Pros and cons of Prototype view
Pros: explains typicality perception, explains difficulty of strict definitions for objects and why some classifications are easy and others hard
Cons:
-doesn’t explain limits of conceptual boundaries and doesn’t explain how typicality varies with changing contexts
Classical View
Classification based on all examples of instances of a concept sharing features
- > every member of category must have certain feature(s)
- all members within category are equal
Cons of Classical View
Cons
- different members of categories are judged as varying in fitting (some are more typical than others)
- some concepts don’t have clearly defined boundaries
Exemplar View
Concepts include representations of at least some actual instances
- > new instances are compared to previously stored instances
- > typical instances more likely to be stored
Exemplars
Previously stored instances of a member of a category
Pros & Cons of the Exemplar View
Pros:
explains inability to state necessary and defining features + difficulty of categorizing atyptical instances
Cons:
too unconstrained, doesn’t explain which instances will be exemplars
Schemata View
Concepts as schemata
- > frameworks of knowledge
- > hierarchically organized: sub-/superschemata
- doesn’t define clear boundaries, not empirically testable
Knowledge-Based View
Objects and events are classified by people using their knowledge of how the concept is organized to justify classification and explain it (not just comparing features or physical aspects)
Concept Attainment Strategies
- Simultaneous scanning
- Successive scanning
- Conservative focusing
Simultaneous scanning
- figuring out hypothesis to which each object is relevant and consider maximum number of hypotheses by choosing optimat object at each point
- heavy demands on working memory
- > testing number of ideas at the same time
Successive scanning
- less demading for working memory
- one hypothesis tested at a time
- tested until enough evidence gathered to form concept
Conservative Focusing
- involves finding object illustrating a concept than choosing other objects varying from it on only one aspect
- efficient and easy, though efficiency depends on task conditions
Prototype
idealized representation of some class of object or events -> includes all features typical of the concept (prototypicality)
Nonanalytic concept formation
- implicit learning
- requires people paying attention to individual examples, storing information and representations about them in memory
- classification: comparing new instances to representations
Scripts
Successions of action tailored to specific situations (e.g. ordering at a restaurant)
Nominal-kind concepts
Concepts with clear definitions
-> information about necessary and sufficient features as part of the concept definiton
Natural-kind concepts
Things naturally occurring in some environment (e.g. a tiger)
-> may include more information about definitional or essential features (e.g. molecular structure)
Artifact concepts
Things constructed to serve some function or to accomplish a task
-> may highlight information about object’s purpose or function
Essentialism
Idea that objects, people, or events have a certain essence or underlying nature,
racism: essentialism where race is the essence and certain characteristics are assumed for a certain race
Cognitive Economy
By dividing information into classes, the amount of information we need to learn, perceive, remember, and recognize is decreased
Basic Level Categories
Entry point: first contact between object perception and semantic information
- > shifts downwards (more specific) as expertise grows
- > tradeoff between width of coverage and predictive value
Concept formation
Abstraction of feature set
Concept learning
Applying a concept and getting feedback
Category components
- theoretical class of objects
- mental representations
- classification system
Category types
Natural categories
Formal categories
Functional Categories
Ad hoc categories (not stable mental representations)
