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Ch.9 Concepts and Generic Knowledge.docx

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George Cree

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Ch.9: Concepts and Generic Knowledge Chapter 9: Concepts and Generic Knowledge Introduction  One must understand underlying concepts to have knowledge o Ex. Understand concept of money to be able to build onto a story involving checking piggybanks Definitions: What do we know when we know what a dog is?  A concept may be similar to a dictionary definition (what is a dog? -- count its defining features)  Then compare this definition with what we sense  Limitations: o Can't account for abstract concepts such as virtue or knowledge o There can be exceptions to each of the defining features  Ex. Games -- one feature may be it is played by multiple people --> but some solitaire is played alone  Family resemblance o Add probability to the definition so that the definition is not too strict and the content also remains o Wittgenstein proposed "family resemblance"  The degree to which an object resembles its ideal category  There characteristic features of each category --> compare the extent to which these are found in the object Prototypes and Typicality Effects  Prototype theory: specify the "center" (or average) of the category rather than the boundaries o Compare the typical object (a prototype) in the category with the object in the real world o The prototype will vary from person to person  Fuzzy boundaries and graded membership o Each category has a fuzzy boundary -- no clear specification of category membership and nonmembership o Allows for graded membership -- an object can more or less in the category or out of it  Testing the prototype notion o Sentence verification task  Present participants with a succession of sentences and indicate whether each sentence is true or false  Dependent variable: response speed  Results: the response speed varies from item to item within the category  Conclusion: some items in the category resemble the prototype more than other items (more -- faster) o Production task  Name as many items in a given category (ex. Birds)  Birds named first were closer to the prototypical bird  Conclusion: go to bird category and then name all the things that resemble that category o Rating task (typicality studies)  Ask how close is the particular item to the given category's prototype  Participants can judge more or less resemblance of the object to the category o When people think about a category they are in fact thinking about the prototype for that category  Basic-Level Categories o Certain types of category are also preferred (as was the case with prototype) o Basic-level categorization - there is a natural level of categorization (neither too specific nor too general) that we tend to use in our conversation and our reasoning (spontaneous)  Ex. When asked "what is this?", we say "a chair" --> could have been more specific (an office chair) or more general (an item of furniture) o When learning to talk, basic level categorization is acquired earlier than more specific and more general terms o "natural" way to categorize objects Exemplars  Another way of interpreting the typicality effect and the graded membership of categories  Analogies from remembered exemplars o Exemplar based reasoning -- categorization can draw on knowledge about specific category members (encounters with dogs) rather than on more general information about the overall category (features of a dog) o May be supported by memories of the category rather than knowledge of the category itself o Exemplar -- specific remembered instance --> compare object with examplar o Similar to protoype view  There is comparison between a given "standard" o Difference between exemplars and prototype  A prototype -- average representation of entire category  An exemplar -- whatever example comes to mind  Explaining typicality data with an exemplar model o Graded membership (exemplar model explanation)  When classifying an object into a category, recall possible corresponding objects of the category  Try to match them -- more or less (graded membership)  More it resembles the greater the likelihood it will be part of the category  Also, the objects with more encounters in reality will be have quicker response times (more memory and prime memory for easier recall)  Exemplars preserve information about variability o In an average, variability is lost o A set of exemplars preserves information about variability in a category (pizzas can vary in sizes -- a common notion)  A combination of exemplars and prototypes o People in daily life behave according to the given circumstances -- different settings, different perspectives trigger different memories and so bring different exemplars to mind o Prototypes are efficient and economical o Thus, not mutually exclusive but a combination of both prototype and exemplars  The extent to which one relies on prototype or exemplar varies from person to person and from category to category  A bird expert has many exemplars in memory for birds while another person may only have a prototype of bird  The same bird expert may only have a general understanding of cars (a prototype)  Small category -- easier to come up with exemplars  Confusable category -- prototypes are better (distinct category -- exemplars better)  Familiar category-- exemplars The Difficulties with Categorization via Resemblance  Odd Number, Even Number o Show all odd numbers and ask participants to rate them in increasing oddness of the numbers o Participants rated each number differently even when the numbers were clearly equally odd o Thus, not always a relationship between typicality and membership o
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