Category differentiation in object recognition: typicality constraints on the basic category advantage.

By Gregory L. Murphy, H. Brownell. 1985

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A mathematical theory of semantic development in deep neural networks (2018, background): “Indeed, such graded judgements of category membership are both highly reproducible across individuals [8, 9] and moreover correlate with performance on a range of tasks: subjects more quickly verify the category membership of more typical items [10, 11], more frequently recall typical examples of a ”
Similar and Different : The Differentiation of Basic-Level Categories (1997, methodology): “Finally, at least two thirds of our superordinates and basiclevel terms have been used in previous studies examining the basic-level advantage (Murphy & Brownell, 1985; Murphy & Wisniewski, 1989; Rosch et al., 1976; Wisniewskl & Murphy, 1989).”
Learning Transferable Knowledge Through Embedding Spaces (2019, result): “But psychological experiments do not confirm this prediction [10].”
The parallel distributed processing approach to semantic cognition (2003, background): “Once potential confounds 16 are controlled for, however,no such effect is found 17,18 .”
Doing without Concepts (2009, result): “” Similar results are obtained when the stimuli are presented visually, for instance, when subjects are shown a picture or a drawing of the object to be categorized, such as a drawing of a robin (Murphy and Brownell 1985).”