The classical view of categorisation is that category membership is
based on the invariant features we detect in different kinds of stimuli
(where kinds is defined by requiring the same response).
This view was thought to be wrong for a number of reasons. The main
reason centers around the Vanishing Intersections objection. People
cannot say which features they use to define each category and any
attempt to define the features can be denied as examples of the
category exist that do not have that feature. However, The fact that we
are not always conscious of the invariant features does not mean we are
not using them to tell which category stimuli are in. Many other
cognitive phenomena also operate at a subconscious level (e.g. implicit
memory). Also, this criticism confuses the psychologists epistimic
problem "What can we do?" with the philosophers ontic problem "What is
actually there?"
The claim that because we cannot name the features used to define a
category we cannot be using invariant features is made especially of
abstract categories such as "beauty" and "truth" for which it is
especially hard to find features which the stimuli of category members
share. Wittgenstein is cited as an authority on this as he pointed out
no one can define "game" but we all know a game when we see one, hence
membership is based on family resemblences not features. However,
abstract categories can be achieved by combining more concrete stimuli
that have been grounded in invariant features. For example, we could
correctly categorise a zebra even if we had never seen one before if we
had combined the previously grounded categories "horse" and "stripes".
An alternative approach has been to suggest that membership of a
category is due to how close an object resembles a prototype of its
category (e.g. Rosch and Lloyd, 19??). This view is based on
experimental evidence that supposedly opposes a classical position as
well as the philosophical objection already outlined. Rosch and others
found that people find some category members more typical than others
and typical members of a category are learnt and categorised faster
than nontypical members. She inferred that category membership is based
on closeness to prototypes to explain this data. For example,
nontypical members took longer to identify than typical ones due to the
extra processing time required to fit stimuli to prototype.
This approach has not been successful. It has some value when one is
trying to explain continuous categories such as "big" as the family
resemblence of "bigness" has relevance to even the smallest thing.
Everything is big to some extent. However, talk of family resemblance
breaks down when considering noncontinuous categories, for example, is
a game more like "blue" than like "chair"? This question clearly cannot
be answered. Also, a big methodological problem with the evidence
provided to support the prototype view is that in studies of typicality
judgements typicality is not categorisation, in fact, it presupposes
categorisation.
Most importantly, the prototype approach has not led to a model being
built that can categorise and, furthermore, even in theory one could
not be built to categorise as we do. It is not clear, for example,
where the prototypes would come from. In contrast, approaches adopting
the classical view that detection of invariant features in stimuli is
the basis of categorisation have had some success in modelling human
categorisation.
So, the philosophical and experimental objections to the classical view
do not stand up to examination, the alternative approach has not been
useful in modelling human capacities while approaches based on the
classical premise have had some success. The more useful and
satisfactory appoach is therefore one that is based on the classical
view.
And also, obviously it's been said that at the end of the day.... its
dark.
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