Resumen de Putting names to faces: a review and tests of the models
It is well established that retrieval of names is harder than the retrieval of other identity specific information. This paper offers a review of the more influential accounts put forward as explanations of why names are so difficult to retrieve. A series of five experiments tests a number of these accounts.
Experiments One to Three examine the claims that names are hard to recall because they are typically meaningless (Cohen 1990), or unique (Burton and Bruce 1992; Brédart, Valentine, Calder, and Gassi 1995). Participants are shown photographs of unfamiliar people (Experiments One and Two) or familiar people (Experiment Three) and given three pieces of information about each: a name, a unique piece of information, and a shared piece of information. Learning follows an incidental procedure, and participants are given a surprise recall test. In each experiment shared information is recalled most often, followed by unique information, followed by name. Experiment Four tests both the ¿uniqueness¿ account and an account based on the specificity of the naming response (Brédart 1993). Participants are presented with famous faces and asked to categorise them by semantic group (occupation). Results indicate that less time is needed to perform this task when the group is a subset of a larger semantic category. A final experiment examines the claim that names might take longer to access because they are less often retrieved than other classes of information. Latencies show that participants remain more efficient when categorising faces by their occupation than by their name even when they have received extra practice of naming the faces.
We conclude that the explanation best able to account for the data is that names are stored separately from other semantic information and can only be accessed after other identity specific information has been retrieved. However, we also argue that the demands we make of these explanations make it likely that no single theory will be able to account for all existing data.
