The auto-verification of social hypotheses: Stereotyping and the power of sample size

In the literature on social hypothesis testing, the co-occurrence of 2 prin ciples is often held responsible for hypothesis confirmation. The first is positive testing (e.g., looking for covert lather than overt aggression whe n testing the stereotype that female aggression is covert), and the second is a cooperative social environment that will often acquiesce and provide p ositive answers (i.e., positive examples for covert female aggression). How ever, it is argued that the co-occurrence of 1-sided questions and confirmi ng answers does not logically verify a hypothesis. A theoretical framework is presented that explains why a constant ratio of confirming to disconfirm ing evidence has more impact when based on a large than on a small sample o f observations. In 2 experiments, a constant affirmation rate led to auto-v erification of the hypothesis that was represented by the larger sample. Th e enhanced significance of large samples is shown to be independent of ster eotypical expectancies and unconfounded with diagnosticity.