Lecture 3 - Concepts and Categories Flashcards
(37 cards)
Define Concept and Category.
A concept can be defined as a mentally possessed idea or notion, whereas a category refers to a set of entities that are grouped together.
E.g. democracy as a concept and then countries that are considered democratic - this is a concept and then categorisation respectively.
Define categorisation.
Categorisation is the ability to form equivalence classes of discriminable entities.
What are some of the challenges to the Classical View of Categorisation?
What are the three theories of how we learn categories discussed in the lecture?
What are the limitations of the Prototype Theory?
Prototype theories cannot explain how we learn non-linearly separable categories.
What is the alternative to the Prototype Model that we discussed that can explain how we learn non-linearly separable categories?
Exemplar Theory.
Why do we form categories, and why is it so important for how we manage the world we perceive?
Being able to categorise things is an evolutionarily beneficial ability that we have developed. It allows us to perceive the complex world in more simplified and manageable way. It also allows us to transfer knowledge about one member of a category to another - e.g. knowing that some snakes are poisonous means that we tend to be cautious around most snakes in case they too are poisonous.
Why does the meaning of a concept change based on the user of the concept?
The meaning of a concept changes depending on who it is using the concept. This is because the goals someone has for using that concept change. E.g. Someone might say that stress on the body is what can lead to chronic health conditions, whereas another might use stress as a pivotal driver of change. The concept of stress is taking on different meaning based on the goal or aim of the user for using that concept.
What happens to generalisation as similarity decreases?
Our willingness to generalise between entities decreases as the similarity between entities decreases. So, for example if we know that robins have a certain behavioural characteristic we would likely being ok saying that a blue wren also has this behavioural feature as these two birds are quite similar, whereas we would probably be less likely to say that flamingoes have this behavioural pattern, due to them being quite different to robins.
What did the World Color Survey find about how we categorise colours?
They found that even though we are able to discriminate around 10,000 colours, 100 different languages had around 10-11 words for the main colours.
In the study done by Eleanor Rosch in 1978 she wanted to understand the structure of categorisation. She looked at the structure of categorisation as having a hierarchy of three main levels - Superordinate, Basic, Subordinate. What did she find about the number of words people used in the three levels?
As you go from superordinate to basic to subordinate the number of words that people used in these categories increased - this seems pretty intuitive.
Eleanor Rosch published a paper in 1978 with a number of experiments illustrating the amount of information we get from the superordinate level of categorisation.
True or false?
False. The experiments were illustrating the large amount of information and importance of the basic level of categorisation.
When does the Classical View of Categorisation date back to?
Ancient Greece.
What is the Classical View of Categorisation?
Members of a category belong to the category based on the fact that they meet the definition of a member of that category. All members are equal members of that category as the all meet the same definition.
Bruner, Goodnow & Austin (1956) did a study to understand the Classical View of Categorisation. They did experiments looking at how participants learned category membership based on arbitrary rules.
They found that there were two types of strategies people used to learn the rules for membership to an arbitrary category.
What were these two types of strategies and what was the difference between the two?
The two types of strategies were Scanning strategies and Focusing strategies.
Scanning Strategies were when participants tried out different hypotheses for what the category membership might be each time they were presented with new members/non-members of the category, i.e. they were “scanning” members to see whether they fit the hypothesis.
Focusing Strategies on the other hand involved focusing on the features/attributes that change or do not change to determine what defined category membership - participants that did this would vary one feature at a time in each choice based on what features changed/stayed the same for the previous item and whether that was considered a member or not.
What is the Classical View Theory of Categorisation?
The Classical View Theory of Categorisation posits that people use rule-based hypotheses to figure and apply categorisation membership. There is a definition that of membership and any entity that fits that definition belongs, just as much as anything else, in that category.
What are some Challenges to the Classical View of Categorisation?
The Classical View of Categorisation sees all members as equally belonging to the category, but people have challenged this view as it appears that we also categorise based on if members partially fit the definition and there are more “typical” members or prototypes of the category.
What did Rosch find in regards to how often a member of a category had one of the attributes listed by participants when they were asked to list attributes of the category members?
Rosch (1978) found that the most most frequent attributes listed more a category tended to only apply to one member of the category. This proposed a challenge the The Classical View Theory of Categorisation. Furthermore, she found that on average only one attribute listed out of all of them belonged to all members of the category.
Rosch (1978) also got participants to rate members of the category as typical or not for that category. e.g. a chair is a more “typical” member of furniture, whereas fish tank (also in the category of furniture), but is “not typical”.
How does this finding challenge the Classical View Theory of Categorisation?
The Classical View sees members of a category as equal members and as all fitting a definition that permits the entity to that category. Rosch’s findings suggest otherwise. She finds that there are typical and atypical members and that members rarely share many of the attributes that people use to define the category.
What is the importance or implication of the typicality of members of a category?
Knowing the typicality of a category is important. It has been shown that people are able to identify entities as members of a group if they are typical members of that group (very intuitive, but still interesting). Also, knowing the typicality of a category means that we know something about what is important for membership to this category.
In regards to categorisation studies, what does induction refer to?
It refers to generalising information from the particular to the general. An example being, if we know all horses get tricket’s diseases and we know all cats get tricket’s disease are we willing to say all mammals get tricket’s disease?
Osheron et al. (1990) did a number of experiments to highlight the importance of typicality of categories to how we learn and generalise across members of a category.
What were some of their main findings?
They found that willingness to generalise information across members of a category is affected by the typicality of the members the information pertains to and the typicality of the members the information is potentially being generalised to.
What is the Prototype Model of Categorization?
The Prototype Model of Categorization assumes that categorization decisions are made based on how similar an object is to the prototype/ideal member of that category.
What was the experiment we looked at in the lecture that wanted to explore the Prototype Theory of Categorization? What were the main findings?
Hint: the arbitrary artificially generated dot constellations were the category members used.
We looked at an experiment that used artificially generated dot constellations that were had a prototype that the rest of the members were generated from. The generated members were of low or high similarity to the prototype. The participants were trained on the category by showing them members of the category that were not the prototype, but the low or high similarity to the prototype. After they had been trained they were shown the prototype or other low/high similarity members of the category. Even though they had never seen the prototype before they were more likely to say that the prototype was a member of the category than the low/high similarity members even when they had seen these members during training.
The researchers concluded that this was evidence in support of the Prototype Model of Categorization. Their theory being that participants, during training, would extract an average from the members they saw and this average would resemble (at least more than other non-prototype members) the prototype hence they would be more willing to say it was a member of the category.
