Every day people make judgments and decisions, even when they don’t have the necessary information. Ramadhar Singh studied how people, when making predictions about others, infer the missing information from the facts they do have. In his research, Singh first experimentally demonstrated that Predicted gift size = Generosity x Capability (Income). Based on this evidence, he then identified that inferred value of the missing capability information increases with the given value of generosity information. In contrast, inferred value of the missing generosity information is constant usually around the middle level of generosity in the donor. Singh and his colleagues also demonstrated similar inferences about missing ability and motivation information in prediction of performance. Singh’s work identifying these kinds of asymmetrical inferences has helped social and cross-cultural psychologists understand and investigate how people judge morality and achievement of others even without the needed information.
“In any given moment, we have two options: to step forward into growth or to step back into safety.” These words, attributed to Abraham Maslow, might summarize what motivates individuals who forego the relative security of a traditional career in favor of entrepreneurship, defined as the capacity and willingness to More
The National Science Foundation’s (NSF) Future of Work at the Human-Technology Frontier program has issued a new grant opportunity that supports research seeking to understand the risk, benefits and impact of human-technology interaction on workers and the work environment more broadly. More
Using communal “we” language in organizational codes of conduct can contribute to the perception that dishonesty will go unpunished. More