Exam 7: Knowing

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An advantage of feature list theories of semantic memory over semantic network models is that feature list theories provide a more fine-grained and flexible representation of conceptual knowledge. In feature list theories, concepts are understood as a collection of features, with each feature representing a property or characteristic of the concept. This allows for a more detailed description of concepts, as each one can be broken down into its constituent features.

One of the key benefits of this approach is that it can account for the typicality effect, which is the observation that certain instances of a concept are judged to be more typical or representative than others. For example, when asked to think of a bird, people are more likely to think of a robin or a sparrow than a penguin. Feature list theories explain this by suggesting that more typical instances have more features in common with the overall feature list for that category.

Additionally, feature list theories can easily accommodate variations and exceptions within a category. Since concepts are not defined by necessary and sufficient conditions, but rather by a list of features that can vary in importance and presence, it is easier to explain how atypical members can still be recognized as part of a category. For instance, even though a penguin lacks many of the features that are common to the category "bird" (such as the ability to fly), it still possesses enough bird-like features to be classified as a bird.

In contrast, semantic network models represent concepts as nodes in a network, with relationships between them depicted as links. While this approach is useful for understanding how concepts are related to one another and can illustrate hierarchical structures and category membership, it may not capture the nuances of individual concept features as effectively as feature list theories. Semantic network models might struggle with explaining typicality effects and the inclusion of atypical category members without additional mechanisms or rules.

In summary, feature list theories offer a more nuanced and flexible approach to representing the details of individual concepts, making it easier to explain phenomena like typicality effects and the categorization of atypical instances.