Seeing clearly: Frame Semantic, Psycholinguistic, and Cross ...

CHAPTER 1. INTRODUCTION 9
is not classical, but fuzzy 3 , and the items rated as better examples are members to a greater
degree.
Lako (1987:77-90) gives an extended series of examples of how prototype e ects
can arise with regard to even classical categories and exemplars that are indisputably mem-
bers of them. For example, one type of prototype is the \Ideal"; the Ideal husband is \a
good provider, faithful, strong, respected, attractive" (p. 87). Of a group of men all of
whom are legally married and live with their wives, some may be judged better examples
of husbands than others depending on their similarity to the Ideal husband, but all of them
are 100% members of the category \husband".
The other error (Prototype = Representation) involves the assumption that the
mental representation of the category is simply the best example, or prototype, i.e. that a
single exemplar is what de nes the category. Degree of category membership would then
be determined by degree of similarity to the prototype. The Ideal husband example also
disproves this error; it would be perfectly possible to have an Aristotelian de nition of the
category \husband" in terms of necessary and su cient conditions (as for example is needed
in law to refer to the rights and responsibilities of a husband vis-a-vis his wife), and still
to record prototype e ects when people are asked to rate individuals as better or worse
examples (for more discussion see Medin 1989).
Thus prototype e ects do not in themselves prove anything about the structure
of categories, as Rosch and other psychologists have been at pains to point out. Of course,
there are categories with fuzzy boundaries and graded membership, such as the set of tall
people, and they will inevitably show prototype e ects. But the measurement of prototype
e ects is not the royal road to understanding human categorization. Barsalou (1983) found
that even categories de ned in such away that the subject had never conceived of them as
a category before (e.g. things that might fallonyour head, things to take on a picnic) also
display prototype e ects, even though they are not pre-existing and do not have names.
One of the strongest experimental proofs of the E ects = Structure error was the study by
Armstrong et al. (1983) which showed that the same subjects would claim to believe the
opinion that a particular category was crisply de ned (the categories used in the experiment
were male, female, odd, and even), and still give better/worse example judgements on a
3 Fuzzy is used here as a technical term, rst used by Zadeh (1965), which describes a category whose
membership function can have values intermediate between true and false, i.e. that individuals can be
members of a category to some degree. Classical categories, which do not allow partial membership, can
also be described as crisp, the opposite of fuzzy.