Conference Proceedings

Vasilyeva, N., & Lombrozo, T. (2019). Structural thinking about social categories: Evidence from formal explanations, generics, and generalization. Proceedings of the 41st Annual Conference of the Cognitive Science Society . Montreal, QC: Cognitive Science Society.Abstract
Most theories of kind representation suggest that people posit internal, essence-like factors believed to underlie kind membership and the observable properties of members. Across two studies (N = 234), we show that adults can construe properties of social kinds as products of both internal and structural (stable external) factors. Internalist and structural construals are similar in that both support formal explanations (i.e., “category member has property P due to category membership C”), generic claims (“Cs have P”), and a particular pattern of generalization to individuals when the individuals’ category membership and structural position are preserved. Our findings thus challenge these phenomena as signatures of essentialist thinking. However, once category membership and structural position are unconfounded, different patterns of generalization emerge across internalist and structural construals, as do different judgments concerning category definitions and property mutability. These findings have important implications for reasoning about social kinds.
Mirabile, P., & Lombrozo, T. (2019). Explanatory considerations guide pursuit. Proceedings of the 41st Annual Conference of the Cognitive Science Society . Montreal, QC: Cognitive Science Society.Abstract
Evidence is typically consistent with more than one hypothesis. How do we decide which hypothesis to pursue (e.g., to subject to further consideration and testing)? Research has shown that explanatory considerations play an important role in learning and inference: we tend to seek and favor hypotheses that offer good explanations for the evidence we invoke them to explain. Here we report three studies testing the proposal that explanatory considerations similarly inform decisions concerning pursuit. We find that ratings of explanatory goodness predict pursuit (though to a lesser extent than they predict belief), and that these effects hold after adjusting for subjective probability. These findings contribute to a growing body of work suggesting an important role for explanatory considerations in shaping inquiry.
Liquin, E., & Lombrozo, T. (2019). Inquiry, theory-formation, and the phenomenology of explanation. Proceedings of the 41st Annual Conference of the Cognitive Science Society . Montreal, QC: Cognitive Science Society.Abstract
Explanations not only increase understanding; they are often deeply satisfying. In the present research, we explore how this phenomenological sense of “explanatory satisfaction” relates to the functional role of explanation within the process of inquiry. In two studies, we address the following questions: 1) Does explanatory satisfaction track the epistemic, learning-directed features of explanation? and 2) How does explanatory satisfaction relate to both antecedent and subsequent curiosity? In answering these questions, we uncover novel determinants of explanatory satisfaction and contribute to the broader literature on explanation and inquiry.
Dubey, R., Griffiths, T., & Lombrozo, T. (2019). If it’s important, then I am curious: A value intervention to induce curiosity. Proceedings of the 41st Annual Conference of the Cognitive Science Society . Montreal, QC: Cognitive Science Society.Abstract
Curiosity is considered essential for learning and sustained engagement, yet stimulating curiosity in educational contexts remains a challenge. Can people’s curiosity about a topic be stimulated by evidence that the topic has potential value? In two experiments we show that increasing people’s perceptions about the usefulness of a scientific topic also influences their curiosity and subsequent information search. Our results also show that simply presenting interesting facts is not enough to influence curiosity, and that people are more likely to be curious about a topic if they perceive it to be directly valuable to them. Given the link between curiosity and learning, these results have important implications for science communication and education more broadly.
Gill, M., & Lombrozo, T. (2019). Social consequences of information search: Seeking evidence and explanation signals religious and scientific commitments. Proceedings of the 41st Annual Conference of the Cognitive Science Society . Montreal, QC: Cognitive Science Society.Abstract

Scientific norms value skepticism; many religious traditions value faith. We test the hypothesis that these different attitudes towards inquiry and belief result in different inferences from epistemic behavior: Whereas the pursuit of evidence or explanations is taken as a signal of commitment to science, forgoing further evidence and explanation is taken as a signal of commitment to religion. Two studies (N = 401) support these predictions. We also find that deciding to pursue inquiry is judged more moral and trustworthy, with moderating effects of participant religiosity and scientism. These findings suggest that epistemic behavior can be a social signal, and shed light on the epistemic and social functions of scientific vs. religious belief.

    Kon, E., & Lombrozo, T. (2018). Seeking ideal explanations in a non-ideal world. T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Ed.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (1939-1944) . Austin, TX: Cognitive Science Society.Abstract
    Research has found that when children or adults attempt to explain novel observations in the course of learning, they are more likely to discover patterns that support ideal explanations: explanations that are maximally simple and broad. However, not all learning contexts support such explanations. Can explaining facilitate discovery nonetheless? We present a study in which participants were tasked with discovering a rule governing the classification of items, where the items were consistent two non-ideal rules: one correctly classified 66% of cases, the other 83%. We find that when there is no ideal rule to be discovered (i.e., no 100% rule), participants prompted to explain are better than control participants at discovering the best available rule (i.e., the 83% rule). This supports the idea that seeking ideal explanations can be beneficial in a non-ideal world because the pursuit of an ideal explanation can facilitate the discovery of imperfect patterns along the way.
    Liquin, E., Metz, S. E., & Lombrozo, T. (2018). Explanation and its limits: Mystery and the need for explanation in science and religion. T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Ed.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (2065-2070) . Austin, TX: Cognitive Science Society.Abstract
    Both science and religion offer explanations for everyday events, but they differ with respect to their tolerance for mysteries. In the present research, we investigate laypeople's perceptions about the extent to which religious and scientific questions demand an explanation and the extent to which an appeal to mystery can satisfy that demand. In Study 1, we document a large domain difference between science and religion: scientific questions are judged to be more in need of explanation and less appropriately answered by appeal to mystery than religious questions. In Study 2, we demonstrate that these differences are not driven by differing levels of belief in the content of these domains. While the source of these domain differences remains unclear, we propose several hypotheses in the General Discussion.
    Liquin, E., & Lombrozo, T. (2018). Determinants and consequences of the need for explanation. T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Ed.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (696-701) . Austin, TX: Cognitive Science Society.Abstract

    Much of human learning throughout the lifespan is achieved through seeking and generating explanations. However, very little is known about what triggers a learner to seek an explanation. In two studies, we investigate what makes a given event or phenomenon stand in need of explanation. In Study 1, we show that a learner's judgment of "need for explanation" for a given question predicts that learner's likelihood of seeking an answer to this question. In Study 2, we explore several potential predictors of need for explanation. We find that the need for explanation is greater for questions expected to have useful answers that require expert understanding, and that "need for explanation" can be differentiated from general curiosity. 

      Mehta, H., Dubey, R., & Lombrozo, T. (2018). Your liking is my curiosity: a social popularity intervention to induce curiosity. T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Ed.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (756-761) . Austin, TX: Cognitive Science Society.Abstract
      Our actions and decisions are regularly influenced by the social environment around us. Can social environment be leveraged to induce curiosity and facilitate subsequent learning? Across two experiments, we show that curiosity is contagious: social environment can influence people's curiosity about the answers to scientific questions. Our findings show that people are more likely to become curious about the answers to more popular questions, which in turn influences the information they choose to reveal. Given that curiosity has been linked to better learning, these findings have important implications for education.
      Vasilyeva, N., Ruggeri, A., & Lombrozo, T. (2018). When and how children use explanations to guide generalizations. T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Ed.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (2069-2614) . Austin, TX: Cognitive Science Society.Abstract
      Explanations often highlight inductively rich relationships that support further generalizations: learning that the knife is sharp because it is for cutting, we correspondingly infer that other things for cutting might also be sharp. When do children appreciate that explanations are good guides to generalization? We report a study in which 108 4- to 7-year-old children evaluated mechanistic, functional, and categorical explanations for the properties of objects, and subsequently generalized those properties to novel objects on the basis of shared mechanisms, functions, or category membership. Older children, but not younger children, were significantly more likely to generalize when the explanation they had received matched the subsequent basis for generalization (e.g., generalizing on the basis of a shared mechanism after hearing a mechanistic explanation). These findings shed light on how explanation and generalization become coordinated in development, as well as the role of explanations in young children’s learning.
      Kon, E., & Lombrozo, T. (2017). Explaining guides learners towards perfect patterns, not perfect prediction. G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Ed.), Proceedings of the 39th Annual Conference of the Cognitive Science Society.Abstract
      When learners explain to themselves as they encounter new information, they recruit a suite of processes that influence subsequent learning. One consequence is that learners are more likely to discover exceptionless rules that underlie what they are trying to explain. Here we investigate what it is about exceptionless rules that satisfies the demands of explanation. Are exceptions unwelcome because they lower predictive accuracy, or because they challenge some other explanatory ideal, such as simplicity and breadth? To compare these alternatives, we introduce a causally rich property explanation task in which exceptions to a general rule are either arbitrary or predictable. If predictive accuracy is sufficient to satisfy the demands of explanation, the introduction of a rule plus exception that supports perfect prediction should block the discovery of a more subtle but exceptionless rule. Across two experiments, we find that effects of explanation go beyond attaining perfect prediction.
      Liquin, E. G., & Lombrozo, T. (2017). Explain, explore, exploit: Effects of explanation on information search. G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Ed.), Proceedings of the 39th Annual Conference of the Cognitive Science Society.Abstract
      How does actively seeking explanations for one’s observations affect information search over the course of learning? Generating explanations could plausibly lead learners to take advantage of the information they have already obtained, resulting in less exploration. Alternatively, explaining could lead learners to explore more, especially after encountering evidence that suggests their current beliefs are incorrect. In two experiments using a modified observe or bet task, we investigate these possibilities and find support for the latter: participants who are prompted to explain their observations in the course of learning tend to explore more, especially after encountering evidence that challenges a current belief.
      Vasilyeva, N., Gopnik, A., & Lombrozo, T. (2017). The development of structural thinking about social categories. G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Ed.), Proceedings of the 39th Annual Conference of the Cognitive Science Society.Abstract
      Representations of social categories help us make sense of the social world, supporting predictions and explanations about groups and individuals. Here we explore whether children and adults are able to understanding category-property associations in structural terms, locating an object of explanation within a larger structure and identifying structural constraints that act on elements of the structure. We show that children as young 3-4 years of age show signs of structural thinking, but that this capacity does not fully develop until after 7 years of age. These findings introduce a viable alternative to internalist accounts of social categories, such as psychological essentialism.
       
      Vasilyeva, N., Blanchard, T., & Lombrozo, T. (2016). Stable causal relationships are better causal relationships. D. Grodner, D. Mirman, A. Papafragou, & J. Trueswell (Ed.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society.Abstract
      We report two experiments investigating whether people’s judgments about causal relationships are sensitive to the robustness or stability of such relationships across a wide range of background circumstances. We demonstrate that people prefer stable causal relationships even when overall causal strength is held constant, and show that this effect is unlikely to be driven by a causal generalization’s actual scope of application. This documents a previously unacknowledged factor that shapes people’s causal reasoning.
      Wilkenfeld, D., Asselin, J., & Lombrozo, T. (2016). Are symptom clusters explanatory? A study in mental disorders and non-causal explanation. D. Grodner, D. Mirman, A. Papafragou, & J. Trueswell (Ed.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society.Abstract
      Three experiments investigate whether and why people accept explanations for symptoms that appeal to mental disorders, such as: “She experiences delusions because she has schizophrenia.” Such explanations are potentially puzzling, as mental disorder diagnoses are made on the basis of symptoms rather than causes. Do laypeople nonetheless conceptualize mental disorder classifications in causal terms? Or is this an instance of non-causal explanation? Experiment 1 shows that such explanations are found explanatory. Experiment 2 presents participants with novel disorders that are stipulated to involve or not involve an underlying cause across symptoms and people. Disorder classifications are found more explanatory when a causal basis is stipulated, or when participants infer that one is present (even after it’s denied in the text). Finally, Experiment 3 finds that merely having a principled, but non-causal, basis for defining symptom clusters is insufficient to reach the explanatory potential of categories with a stipulated common cause.

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