Abstract
In this paper, we give a brief overview of current, cognitive-psychological theories, which provide an account for how people explain facts: causal model theories (the predominant type of dependence theory) and mechanistic theories. These theories differ in (i) what they assume people to explain and (ii) how they assume people to provide an explanation. In consequence, they require different types of knowledge in order to explain. We work out predictions from the theoretical accounts for the questions people may ask to fill in gaps in knowledge. Two empirical studies are presented looking at the questions people ask in order to get or give an explanation. The first observational study explored the causal questions people ask on the internet, including questions asking for an explanation. We also analyzed the facts that people want to have explained and found that people inquire about tokens and types of events as well as tokens and types of causal relations. The second experimental study directly investigated which information people ask for in order to provide an explanation. Several scenarios describing tokens and types of events were presented to participants. As a second factor, we manipulated whether the facts were familiar to participants or not. Questions were analyzed and coded with respect to the information inquired about. We found that both factors affected the types of questions participants asked. Surprisingly, participants asked only few questions about actual causation or about information, which would have allowed them to infer actual causation, when a token event had to be explained. Overall the findings neither fully supported causal model nor mechanistic theories. Hence, they are in contrast to many other studies, in which participants were provided with relevant information upfront and just asked for an explanation or judgment. We conclude that more empirical and theoretical work is needed to reconcile the findings from these two lines of research into causal explanations.
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Notes
- 1.
It is important to mention that there are also dispositional theories of causal cognition (e.g., force dynamics, Wolff 2007). Due to length considerations we do not discuss them here.
- 2.
- 3.
Note that these questions can provide important information for causal attribution. Information about the time course of events can rule out certain causes as actual causes like in the Billy and Suzy case, and information about causal power or strength can also help to establish actual causation.
- 4.
Three participants which were assigned to the token condition failed to respond to the unfamiliar token events. Therefore the degrees of freedom were smaller for this comparison.
- 5.
Note that this difference would not be statistically significant when controlling for the number of analyses conducted (controlling for the number of analyses avoids an inflation of the risk for an alpha error in statistical analyses). All other statistically significant results would still be significant.
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Hagmayer, Y., Engelmann, N. (2020). Asking Questions to Provide a Causal Explanation – Do People Search for the Information Required by Cognitive Psychological Theories?. In: Bar-Asher Siegal, E., Boneh, N. (eds) Perspectives on Causation. Jerusalem Studies in Philosophy and History of Science. Springer, Cham. https://doi.org/10.1007/978-3-030-34308-8_4
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