A Piecemeal Processing Strategy Model for Causal-Based Categorization

AbstractOver the last 20 years, causal-model theory has produced much knowledge about causal-based categorization. However, persistent violations of the normative causal-model theory are prevalent. In particular, violations to the Markov condition have been repeatedly found. These violations have received different explanations. Here, we develop a model that starts from generally accepted cognitive phenomena (e.g., processing limitations, the relevance of inference in cognitive processing) and assumes that people are not fully causal nor fully associative when performing causal-based categorization, offering an explanation for Markov violations.

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