Children posit hidden causes to explain causal variability


Most models of causal reasoning estimate the strength of a causal relation using a function of the proportion of successes and failures: the number of trials on which the cause produced the effect, divided by the total number of trials. Alternatively, people may represent failures as due to a hidden inhibitor that has a specific location and extent in time. We model these possibilities, and empirically test a case on which the two models make opposite predictions. We find that children as young as four years old generate responses inconsistent with proportional models, but consistent with an inhibitor-based model. Incorporating a recency component does not help proportional models fit the data.

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