The coincidence effect in similarity and choice

Abstract

Medin, Goldstone, and Markman (1995) recently described a series of parallel effects in similarity and choice. They suggested that similarity and choice are related in a nontrivial way such that choice may entail a similarity judgment to an explicit or constructed ideal. In this paper, the correspondences between similarity and choice were investigated with respect to a phenomenon in similarity known as the coincidence effect. In coincidence (pronounced "coincide-ence"), two items that match on one dimension but have a large difference on another dimension receive a higher similarity rating than do two items that have only modest differences on both dimensions. We conducted five experiments in order to examine commonalities between similarity and choice processes with respect to coincidence. Four types of tasks were given: similarity ratings, desirability ratings, forced choice similarities (which of two items is most similar to a target), and forced choice preferences (which of two items one would prefer, given a target). We found a main effect for ratings as opposed to forced choices, with ratings showing greater coincidence effects than did choices. Similarity measures tended to produce more coincidence than did preference measures. The overall pattern of results suggests the presence of dimensional weighting processes sensitive to task characteristics and operating somewhat differently for similarity and decision making.

The roles of shared vs. distinctive conceptual features in lexical access

“…Past research has shown that similarity ratings tend to weight shared features as more important, with two items (e.g., horse and zebra ) matching on one dimension (e.g., equine animal ) yet differing considerably on another (e.g., stripes ) tending to receive a higher similarity rating than two items that differ modestly (e.g., horse and donkey ; Medin et al, 1995; Kaplan and Medin, 1997). As we noted in the Introduction to this paper, an examination of the close distractor-target pairings in Mahon et al's (2007) Experiment 5 revealed the majority involved distinguishing features (e.g., HORSE- zebra ) according to feature production norms.…”

“…These stimuli were selected based on semantic similarity ratings from an independent sample of participants. Past research has shown that similarity ratings tend to emphasize the importance of shared features while de-emphasizing distinguishing features (e.g., Medin et al, 1995; Kaplan and Medin, 1997). For example, the coincidence effect refers to the finding that two items (e.g., horse and zebra ) that are semantically close due to feature overlap (e.g., equine animal, has legs, has a tail, etc .)…”

Evidence for the coincidence effect in environmental judgments: Why isn't it easy to correctly identify environmentally friendly food products?

“…The data for all tasks used in the experiments were analyzed using Kaplan and Medin's (1997) ideal-based method. 2 According to this method, right angle corners are considered as references (e.g., Stimuli a and e in Figure 2).…”

The roles of conceptual feature overlap and distinctiveness during lexical access in spoken word production

“…Past research has shown that similarity ratings tend to weight shared features as more important, with two items (e.g., horse and zebra) matching on one dimension (e.g., equine animal) yet differing considerably on another (e.g., stripes) tending to receive a higher similarity rating than two items that differ modestly (e.g., horse and donkey; Kaplan & Medin, 1997;Medin, et al, 1995).…”

“…Past research has shown that similarity ratings tend to emphasize the importance of shared features while de-emphasizing distinguishing features (e.g. Kaplan & Medin, 1997;Medin, Goldstone, & Markman, 1995). For example, the coincidence effect refers to the finding that two items (e.g., horse and zebra) that are semantically close due to feature overlap (e.g., equine animal, has legs, has a tail, etc) yet differ due to a distinguishing feature (e.g., has stripes) will tend to receive a higher similarity rating than do two items that share a similar number of semantic features yet only differ modestly (e.g., horse and donkey).…”