16 Nov 2017
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Chapter 9 – Concepts and Generic Knowledge
Understanding Concepts
• Ordinary concepts (“shoe” or “tree”) are the building blocks out of which all your
knowledge is created – you depend on your knowledge in many aspects of your day-to-
day functioning
• You need concepts in order to have knowledge, and you need knowledge in order ot
function
Definitions: What is a “Dog”?
• You have knowledge that represents what a dog is for you; but what is that knowledge
o You know something akin to a dictionary definition
▪ “A dog is a creature that (a) has four legs, (b) barks, (c) wags it’s tail.”
▪ Can use the definition as a checklist
• But what about more complex concepts?
o For each clause of the definition, we can easily find an exception that doesn’t
have the relevant characteristic
• Therefore, that even simple terms, terms denoting concepts we use easily and often, resist
being defined
o In each case we can come up with what seems to be a plausible definition, but
then its easy to find exceptions to it
Family Resemblance
• Associate that we’ve seen one dog with four legs so all dogs must have four legs
• Dogs usually are creatures that have fur, four legs, and bark, and a creature without these
features is unlikely to be a dog
o This probabilistic phrasing preserves what’s good about definitions – the fact that
they do name sensible, relevant features, shared by most members of the category
▪ A degree of uncertainty, some number of exceptions to the rule
• Members of a category have a family resemblance to one another
o There are features that are common in the family, and so, if we consider family
members two or three at a time, we can usually find some shared attributes
o There are common features, but the identity of those common features depends on
what “subgroup” of the family you’re considering – hair colour shared for these
family members; eye shape shared by those family members
• Imagining the “ideal” for each family – someone who has all of the family’s features
o In lots of families, it may not exist
o Each member of the family has at least some features in common with this ideal –
and therefore some features in common with other family members
• Ordinary categories (“dog”) work the same way
o There may be no features that are shared by all dogs, but we can identify
“characteristic features” for each category – features that many category members
have.
o The more of these features an object has, the ore likely you are to believe it is in
the category
o Family resemblance is a matter of degree, not all-or-non**
Prototypes and Typicality Effects
• Definitions set the “boundaries” for a category
o If a case has certain attributes, then it’s “inside” the boundaries; if if a test doesn’t
have the defining attributes, then it’s “outside” the boundaries
• Prototype theory – begins with a different tactic: Perhaps the best way to identify a
category is to specify the “center” of the category, rather than the boundaries
o Perhaps the concept of dog is represented in the mind by some depiction of the
“ideal” dog, and all judgements about dogs are made with reference to this ideal
▪ The concept is represented by the appropriate prototype
• In most cases the ideal (the prototype) will be an average of the various category
members you’ve encountered
o Prototype dog – average colour, average size, etc., for all the dogs you have seen
o No matter what the specifics of the prototype, though, you’ll use this “ideal” as
the anchor, the benchmark for your conceptual knowledge – whenever you use
your conceptual knowledge, your reasoning is done with reference to the
prototype
Prototypes and Graded Membership
• Simple task of memorization: deciding whether something is or is not a dog
o To make decision you compare the creature currently before your eyes with the
prototype in your memory
o If there is no similarity between them, the creature standing before you is
probably not in the category; if there’s considerable similarity, you draw the
opposite conclusion
• Membership in a category depends on resemblance to the prototype, and resemblance is a
matter of degree
o As a result, membership in the category is not a simple yes or no decision – it’s a
matter of more or less
o Categories have a graded membership – objects closer tot the prototype are
“better” members of the category than objects further from the prototype
▪ Some dogs are “doggier”
Testing the Prototype Notion
• In a sentence verification task research participants are presented with a succession of
sentences; their job is to indicate whether each sentence is true or false
o According to the prototype perspective, participants choose their response (true vs
false) by comparing the thing mentioned to their prototype for that category
o When there is close similarity between the test case and the prototype,
participants can make their decisions quickly; judgments about items more distant
from the prototype take more time
• Production task – ask people to name as many birds or dogs as they can
o According to prototype view they will do this task by first locating their bird or
dog prototype in memory and their asking themselves what resembles this
prototype
o They’ll start with center of category and work their way outward from there
o Birds close from the prototype mentioned first