Discounting and Augmentation of Dispositional and Causal Attributions

Abstract

This article investigates whether and how discounting and augmentation of dispositional and causal attributions differ between each other. In three experiments, the strength of a causal or dispositional attribution to a target actor (or object) was varied by manipulating the number of observations (i.e., sample size) of an alternative actor (or object). The results of Experiments 1 and 2 indicated that a greater sample size of the alternative actor (or object) resulted in greater discounting or augmentation of the target, and that this effect was alike for causal and dispositional attributions. This effect of sample size on discounting and augmentation cannot be explained by current algebraic attribution models, but is consistent with predictions from a connectionist framework. In Experiment 3, the extraction of information was made more difficult, and the effect of sample size on discounting and augmentation remained robust for causal attributions, whereas it disappeared for dispositional attributions. This failure for dispositional attributions was not predicted by any theoretical model. The discussion focuses on some potential explanations for this unexpected finding.