"Attribute-framing bias" reflects people's tendency to evaluate objects framed positively more favorably than the same objects framed negatively. Although biased by the framing valence, evaluations are nevertheless calibrated to the magnitude of the target attribute. In three experiments that manipulated magnitudes in different ways, we…

Attribute-framing bias reflects people's tendency to evaluate positively framed objects more favorably than the same objects framed negatively. Most theoretical accounts of this bias emphasized the role of positive- and negative-framing valence in the message, disregarding the quantitative information that typically accompanies it. To examine the…

In our everyday life, we often need to anticipate the potential occurrence of events and their consequences. In this context, the way we represent contingencies can determine our ability to adapt to the environment. However, it is not clear how agents encode and organize available knowledge about the future to react to possible states of the…

Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…

Interacting with a system is key to uncovering its causal structure. A computational framework for interventional causal learning has been developed over the last decade, but how real causal learners might achieve or approximate the computations entailed by this framework is still poorly understood. Here we describe an interactive computer task in…

The present set of 7 experiments systematically examined the effectiveness of adding causal explanations to simple refutations in reducing or eliminating the impact of outdated information on subsequent comprehension. The addition of a single causal-explanation sentence to a refutation was sufficient to eliminate any measurable disruption in…