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Chapter 9

Chapter 9.docx

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Department
Psychology
Course
PSYC 2650
Professor
Anneke Olthof
Semester
Winter

Description
Chapter 9 - Concepts and Generic Knowledge Family Resemblance:  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. Applefruit), “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 Exemplars  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 primedfaster memory searchpattern of what more readily available in
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