Chapter 9 - Concepts and Generic Knowledge
Need way of identifying concepts that highlights what various members of category have in common (eg. What all dogs have in
common) while simultaneously allowing exceptions to the proposed rule.
We can do so by keeping the context of our definitions but being more flexible to our use of the definitions
For instance; a dog is an animal that probably has fur, 4 legs, and barks
Wittgenstein proposed that members of a category have a family resemblance to each other
Features that common in family, and so, if we consider family members, 2 or even 3 at a time, we can fine shared attributes
May be no features that shared by all dogs/all games, just as there no features that shared by everyone in family
Identify “characteristic features” for each category; features that most category members have
More of these features an object has, the more likely we are to believe it is in the category
Family resemblance is a matter of degree, not all-or-none
Prototypes and Typicality Effects
Definitions set the “boundaries” for a category
If a test case has certain attributes, then it is inside the category
Prototype theory: best way to identify category/characterize concept - specify “center” of category rather than boundaries
o Example: prototype dog= the ideal dog
Therefore, all judgments about dogs are made with reference to this ideal
In some cases, prototype may represent ideal for category: e.g. prototype of diet soda might have 0 calories but still taste great.
Prototype will be an average of various category members have encountered. E.g. average color/size of dogs you have seen
Different people have different prototypes; people may disagree about what the ideal for a category is
Despite this, the prototype serves as an anchor, or benchmark for our conceptual knowledge
When we reason about a concept or use our conceptual knowledge, our reasoning is done with reference to the prototype
Fuzzy Boundaries and Graded Membership
What it means to “know” a concept is simply to have some mental representation of the concept’s prototype
Things that have fewer attributes in common with prototype will probably cause you uncertainty about their identity
Since category is characterized by center (prototype) and not boundaries, no way can say something is inside/outside category
o To be inside or outside, you need a definite boundary to be inside or outside of
Each category has what is called a fuzzy boundary: with no clear specification of category membership and non-membership
Objects closer to the prototype are, in effect, “better” members of the category than objects farther from the prototype
Thus, categories that depend on a prototype have graded membership.
Graded membership: idea that some members of category “better” members and more firmly in category than others
Testing the Prototype Notion
Sentence verification task: presented with series of sentences; indicate (press appropriate button) if sentence is true or false)
In most experiments, we are interested in how quickly participants can do task, in fact, speed depends on several factors.
Response speed depends on the number of “Steps” the participants must traverse to confirm the sentence
Participants also response more quickly to true sentences than for false, and also more quickly for familiar categories.
According to prototype perspective, participants make judgments by comparing thing mentioned to their prototype for category
Similarity between test case and prototype, make decisions quickly. Items more distant from prototype take more time.
Production task: ask people to name as many birds or dogs as they can.
According to prototype view; do production task by locating bird/dog prototype in memory and ask what resembles prototype
Start with the center of the category (prototype) work their way outward
Birds closest to prototype mentioned first, birds farther from the prototype, later on.
First birds mentioned in production task yielded fastest response times in verification task - proximity to the prototype.
Members of category “privileged” on one task (eg. yield fastest response times), privileged on other tasks (eg. Likely mentioned)
Various tasks converge in the sense that each task yields the same answer/ indicates the same category members as special.
Category members mentioned early in production task (robin bird. Applefruit), “privileged” in picture-identification task
Picture-identification task: shown simple pictures (often line drawings), must indicate, as rapidly as possible, what picture
shows - Responses faster if objects are typical of category.
Rating task: participants evaluate item/category with reference to some dimension, expressing response in terms of number. E.g.
asked to evaluate birds for how typical they are within category of birds, using 1 - “very typical” and 7 - “very atypical”
Typicality: The degree to which a particular case (an object, situation, event) is typical for its kind
A Basic-Level Categories
Rosch and others argued that “natural” level of categorization, not specific not general, use in our conversations & reasoning
The special status of this basic-level categorization can be demonstrated in many ways. Basic-level categorization: represented in our language via a single word (ex. chair)
Specific categories: identified via a phrase (lawn chair, kitchen chair, etc)
The importance of basic level categories also shows up in our memory errors
Participants read story, after delay memory tested. If contained specific terms, often (falsely) recalled heard more general
“She noticed that her jeans were stained” remembered as “she noticed that her pants were stained”
Story contained general terms, misremembered more specific (E.g. remembered hearing dogs when actually heard animals)
The errors almost always tend to “revise” the story in the direction of basic-level categorization
Exemplar-based reasoning: reasoning draws on knowledge about specific category members, rather than drawing on more
general information about overall category (a specific remembered instance)
Analogies from remembered exemplars
Categorization draw on knowledge about specific category members rather than more general information about overall category
Example: categorization is supported by memories of a specific chair, rather than remembered knowledge about chairs in general
Exemplar-based approach similar to the prototype view - categorize objects by comparing to mentally represented “standard”
The difference between the views lies in what that standard is
For prototype theory: the standard is the prototype; an average representing the entire category
For exemplar theory: the standard is provided by whatever example of the category comes to mind
Explaining typicality data with an exemplar model
An exemplar-based approach can also explain the graded-membership pattern
Frequently encounter something memory well primedfaster memory searchpattern of what more readily available in