Midterm 2 (NEW PROGRESS) Flashcards
What are examples of typicality effects?
- We name typical category members before atypical ones
- We are faster to put typical members into categories than atypical ones
- Typical exemplars show larger priming effects than atypical ones
- Infants learn typical category members first
- When producing sentences, we list typical category members before atypical ones
Describe the exemplar theory of categorization
- Rather than storing an abstract prototype in memory to which items can be compared, exemplar theory proposes that we store actual examples of items we have encountered in the past
- Ex: your knowledge of the bird category contains a set of birds that you have seen before
- Categorization occurs by comparing new items to the ones you have in memory and looking for similarity between their features
- If a new item has many similar features with the category members you have in memory and not a lot of features in common with members of other categories, it is placed into the first category
How does the exemplar theory of categorization explain the typicality effects?
- This theory can explain typicality effects because typical items are similar to many other category members so it will be easy (and fast) to retrieve those members from memory
- Atypical members will be harder to retrieve because they are less common
- Ex: on the one hand, an apple is similar to other fruits but dissimilar to vegetables, so it is considered a typical fruit. This means it will be processed quickly because we can think of many other similar fruits. On the other hand, a squash is similar to some fruits, but also similar to some vegetables. This makes it an atypical member of the fruit category and more difficult to identify as a fruit because there are fewer similar examples
How does exemplar theory explain context effects?
- Because it assumes that categorization depends on personal experience
- Ex: a robin is a typical bird in North America because it is similar to many birds that one would encounter there. Similarly, a rainbow lorikeet is a typical bird in Australia because is it similar to many birds that are seen there
Describe Dopkins and Gleason’s (1997) study on the exemplar theory before they introduced the ambiguous exemplars
- They had participants learn to categorize rectangles on a computer screen into 2 different categories
- Participants were not given any rules to help them learn how to sort the rectangles, they were simply told whether they had classified each rectangle correctly
- What participants didn’t know was that the rectangles could be categorized by considering both their length and the position they appeared on the screen -> one type of rectangle was usually wide and near the top of the screen (category 1); the other type of rectangle was narrow and near the bottom of the screen (category 2)
- After many trials, participants were able to accurately categorize the rectangles
- This finding was expected because it has been known for a long time that we are very good at categorization even when we aren’t told how to do it
Describe Dopkins and Gleason’s (1997) study on the exemplar theory when they introduced the ambiguous exemplars
- Participants then had to categorize new, ambiguous exemplars which could theoretically belong to either category (they were medium length in the middle of the screen) and were designed in such a way that prototype theory and exemplar theory made different predictions about how they would be categorized
- The new rectangles were similar to the average, or prototypical, rectangle from category 2, but they were more similar to some of the previously seen individual exemplars from the category 1, meaning that the prototype approach would predict that participants would categorize the new rectangles into category 2, whereas, the exemplar theory would predict that participants would categorize the new rectangles into category 1
- The results showed that participants tended to categorize the new rectangles into the wide and high group (category 1) most often
- They based their categorization on similarity to previously seen exemplars rather than similarity to a prototype
What do the prototype theory and exemplar theory fail to account for?
- Both theories claim that the fact that people provide consistent typicality ratings to items indicates that category boundaries are fuzzy and not rule-based. However, Armstrong, Gleitman, and Gleitman (1983) showed that participants could give consistent typicality ratings to well-defined categories, indicating that perhaps the typicality ratings of other categories, such as birds and fruit, were merely an artifact of the experimental method used and not indicative of fuzzy category borders
- According to these views, we categorize items by comparing the similarity between a new item and either a prototype or many exemplars in memory. However, they don’t specify how we decide which features to compare. This concept of implicit ideas about category membership is not explained by either prototype or exemplar theory, but is addressed by knowledge-based views of categorization
Describe Armstrong, Gleitman, and Gleitman (1983) study on typicality ratings
- They had participants give typicality ratings to naturally occurring categories, such as birds and fruit, but also to categories that have well-defined category membership rules (ex: odd numbers)
- They found that their participants agreed with the idea that numbers are either odd or even and that there really isn’t such a thing as a “more odd” number, (i.e., they conform to rules). However, they still gave odd numbers typicality ratings when asked to do so and participants’ typicality ratings were consistent with each other
Ex: participants agreed that 3 is a more typical odd number than is 447 - Conclusion: If participants could give consistent typicality ratings to well-defined categories, perhaps the typicality ratings of other categories, such as birds and fruit, were merely an artifact of the experimental method used and not indicative of fuzzy category borders
What did Murphy and Medin (1985) point out about categorization?
- That there’s potentially an infinite number of ways that any 2 items could be similar
- Ex: A banana and a television can both be purchased in a store, both are enjoyed by people, both are smaller than a truck, neither of them is purple
- We appear to have an understanding of which features are important for category membership and which are not
- This concept of implicit ideas about category membership is not explained by either prototype or exemplar theory, but is addressed by knowledge-based views of categorization
Describe knowledge-based views of categorization
- This approach assumes we use more than feature similarity to categorize
- Instead, they propose that we rely on our broad knowledge base to explain the reasons for category membership
- Often our ideas about category membership are implicit
- Ex: we know a poodle is a dog because there’s just something “doggy” about it. Even a poodle with three legs that can’t bark is still a dog because it hasn’t lost its “dogginess”
-This type of theory avoids the problem faced by prototype and exemplar theories of explaining which features are important for determining category membership and which are not - According to theory-based approaches, membership isn’t based on features; instead, we use broad theories about essentialism
What did Medin (1989) refer to as psychological essentialism?
- He described this idea that we have implicit theories about the requirements for category membership
- The idea is that all category members possess a fundamental essence that is unique to that category and determines membership
- Ex: Dogs are “doggy,” birds are “birdy,” and fruits are “fruity”
What’s psychological essentialism?
The proposal that categories have a natural underlying true nature that can’t be stated explicitly
What did Murphy and Allopena discover with regards to descriptions of place whose features do and don’t go together?
- They found that participants can learn about the building whose features go together more easily than the second type of building whose features don’t seem to go together
- These results indicate that when we learn about categories, we try to make meaningful connections from our past knowledge to explain the particular combination of features
- According to this view, we rely on categories to teach us about the world, and we use our knowledge about the world to help explain category membership
What’s a consequence of categorization based on psychological essentialism?
- Risk of applying “essential” qualities to social categories in the same way that we do to biological categories
- While it may be reasonable to think all dogs have an essential “doggy” quality, it doesn’t make sense to make the same claims about older adults
- While it’s natural to expect that we put people into categories in the same way that we categorize objects since our brains are designed to categorize the world to help us make sense of it, it’s important to keep in mind that categorizing people that way leads to stereotyping
- There’s a relationship between essentialism and stereotypes
Describe Bastian and Haslam (2006) study on participants’ essentialist beliefs
- They asked participants to complete questionnaires that measured their essentialist beliefs
- The questionnaires measured how much participants believed that people belong to discrete groups (“Everyone is either a certain type of person or they are not”), whether or not qualities are changeable (“Everyone, no matter who they are, can significantly change their basic characteristics”) and whether group membership has a biological cause (“The kind of person someone is can be largely attributed to their genetic inheritance”)
- The results revealed that participants with higher essentialist beliefs were more likely to endorse a variety of stereotypes about different groups of people
Why is it important to not apply essentialism views on people?
- This leads to stereotyping
- While we all categorize people based on our past experiences and knowledge, it’s important to remember that the categories we form about people are shortcuts meant to reduce cognitive load, and not based on essential characteristics of group members
Research about what has been particularly influential in informing psychologists’ understanding of knowledge organization?
Research about human memory and artificial intelligence
What’s a core idea about categories that was first introduced by Rosch et al (1976)?
- He noticed that individual items can belong to multiple levels or hierarchies of categories
- Rosch further suggested that basic level categories are the most cognitively efficient
What are the 3 levels of categories that Rosch named for his idea of the hierarchy of categories?
- Basic level category
- Subordinate category
- Superordinate category
Describe the basic level category
- The level of categorization that people find most natural
- It’s the most cognitively efficient level that is both informative and distinctive
- Level in the hierarchy that seems to most of us to be “just right” -> they provide just the right amount of information about the category to provide useful information (informative), and can be used to distinguish members from members of other categories (distinctive)
- This is the level we typically use to name the category of an item, and it’s also the one that children learn first as they learn to name objects around them
Describe the subordinate category level
- The category level that is below the basic level
- This level is more informative than the basic level but less distinctive
- Informative because they provide a lot of information about the item; however, they are not distinctive because they share many features in common
Describe the superordinate category level
- The category level that is above the basic level
- This level is less informative than the basic level but distinctive
- Ex: animals are quite different from fruits, but knowing something is an animal provides relatively little information compared to knowing that it’s a dog
Rank the different category levels from most broad to most specific
- Superordinate level
- Basic level
- Subordinate level
How can the human mind can be likened to a computer?
Humans are information processors that receive sensory input, use rule-based strategies to manipulate information, and produce a behavioral output, much in the same way as a computer