Costly Exceptions: Deviant Exemplars Reduce Category Compression
- Daniel Silliman, Binghamton University, Binghamton, New York, United States
- Sean Snoddy, Binghamton University, Binghamton, New York, United States
- Matt Wetzel, Psychology, Binghamton University, Binghamton, New York, United States
- Kenneth Kurtz, Binghamton University, Binghamton, New York, United States
AbstractWe investigated whether the presence of exception items can impede effects of category compression (within-category items appearing more similar) in classification learning. We hypothesized that the distinct representations afforded to exceptions may cause the target category to appear less cohesive, thereby reducing the likelihood of compression occurring. Across two experiments, participants engaged in classification learning without exceptions, with an easy exception, or with a difficult exception. Pairwise similarity ratings for all items were collected before and after learning to index compression. Results from Experiment 1 suggest that difficult exceptions can impede compression for the contrast category when situated within its cluster, while results from Experiment 2 suggest that both kinds of exceptions can impair compression of standard items in a target category relative to the No Exception control. We also observed surprising evidence of a novel between-category compression effect that was observed with the category structure developed for these experiments.