Nesta página você pode obter uma análise detalhada de uma palavra ou frase, produzida usando a melhor tecnologia de inteligência artificial até o momento:
Actor–observer asymmetry (also actor–observer bias) is a bias one makes when forming attributions about the behavior of others or themselves depending on whether they are an actor or an observer in a situation. When people judge their own behavior, they are more likely to attribute their actions to the particular situation than to their personality. However, when an observer is explaining the behavior of another person, they are more likely to attribute this behavior to the actors' personality rather than to situational factors.
Sometimes the actor-observer asymmetry is defined as the fundamental attribution error, which is when people tend to focus on the internal, personal characteristic or disposition as the cause of behavior rather than the external factors or situational influences.
This term falls under attribution theory. The specific hypothesis of an actor-observer asymmetry in attribution was originally proposed by Edward Jones and Richard Nisbett, where they said that "actors tend to attribute the causes of their behavior to stimuli inherent in the situation, while observers tend to attribute behavior to stable dispositions of the actor". Supported by initial evidence, the hypothesis was long held as firmly established. However, a meta-analysis of all the published tests of the hypothesis between 1971 and 2004 found that there was no actor-observer asymmetry of the sort that had been previously proposed. Malle interpreted this result not so much as proof that actors and observers explained behavior exactly the same way but as evidence that the original hypothesis was fundamentally flawed in the way it framed people's explanations of behavior as attributions to either stable dispositions or to the situation.
Considerations of actor-observer differences can be found in other disciplines as well, such as philosophy (e.g. privileged access, incorrigibility), management studies, artificial intelligence, semiotics, anthropology, and political science.