‘Why’ questions are semantically ambiguous. A question like “Why is the sky blue?” can be rephrased as either a ‘how’ (“How did the sky get its blue color?”) or a ‘purpose’ question (“What is the purpose of the sky being blue?”). This semantic ambiguity allows us to seek many kinds of information with the same ‘why’ question. As a result, ‘why’ questions have often been used to investigate people’s explanation preferences. From such work, we know that people will often prefer teleological over mechanistic explanations—a tendency that has been linked to many broader theories of human cognition. But are ‘why’ questions pragmatically ambiguous? You may, for instance, have a specific expectation about what “Why is the sky blue?” was really meaning to ask. Here, we show that (a) people have clear, domain-specific expectations about what specific questions are implied by ambiguous ‘why’ questions; (b) people have clear preferences for certain kinds of questions over others; and (c) there is a direct link between implicit questions and explanation preferences. Thus not only is “why” pragmatically unambiguous, but these specific expectations may shape known explanation preferences. To test this view, we finally show that people endorse teleological answers even when they are explicitly non-explanatory. In other words, people may sometimes prefer teleological answers because they interpret ‘why’ questions as ‘purpose’ questions (rather than as ‘how’ questions) and teleological explanations may simply better address these questions. We discuss how understanding ‘why’ may reshape our understanding of people’s explanation preferences and their consequences.
Parallel research programs across decades have developed contrasting accounts of people’s explanation preferences. One perspective emphasizes adults’ and children’s preferences for teleological explanations (i.e., explanations referring to something’s purpose), even in direct contrast with mechanistic (or causal) explanations. The other perspective highlights contexts where people instead seek out mechanistic knowledge and judge it to be particularly valuable. These characterizations of people’s explanation preferences support fundamentally different theories of people’s intrinsic worldviews: People may either be irrational and prone to unscientific explanation, or relatively sophisticated investigators of the world around them. How can these teleo-centric and mech-centric views of explanation preferences be reconciled? Here, we demonstrate that mechanistic explanations are comprised of two significant subtypes of explanation. Etiological mechanisms address how things came to be, whereas constitutive mechanisms address how they currently work. In Experiments 1 and 2, we find that people prefer constitutive mechanisms to etiological mechanisms. In Experiments 3, 4a, and 4b, we also find that constitutive and etiological mechanisms are judged differently against teleological explanations. In general, constitutive mechanisms perform better against teleological explanations than etiological mechanisms. Thus, people’s preferences depend on the type of mechanism involved; they may prefer teleology to one kind of mechanism but not to the other. We discuss implications for the larger debate on explanation preferences.
What is the format of spatial representation? In mathematics, we often conceive of two primary ways of representing two-dimensional space, Cartesian coordinates, which capture horizontal and vertical relations, and polar coordinates, which captures angle and distance relations. Do either of these two coordinate systems play a representational role in the human mind? Six experiments utilizing a simple ‘visual matching’ paradigm show that (1) representational format is recoverable from the errors observers make in simple spatial tasks; (2) human-made errors spontaneously favor a polar coordinate system of representation; and (3) observers are capable of using other coordinate systems when acting in highly structured spaces (e.g., grids). We discuss these findings in relation to classic work on dimension independence, as well as work on spatial representation at other spatial scales.
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