The Motivational Processes of Sense-Making

Wojtowicz, Zachary; Chater, Nick; Loewenstein, George

doi:10.1017/9781009026949.002

Cited by 16 publications

(6 citation statements)

References 90 publications

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“…Behavioral science provides a powerful i-frame analysis of why people are so vulnerable to misinformation – and should be taken to imply that protecting against these vulnerabilities requires s-level interventions. People are excessively credulous (Gilbert, Tafarodi, & Malone, 1993), strongly underestimate the power of conflicts of interests (Dana & Loewenstein, 2003), and are influenced by the many nonepistemic benefits of new information: Reducing cognitive dissonance, shoring up personal beliefs systems, creating or cementing identification with “like-minded” others, providing ammunition in hypothetical or real debates, and many more (Chater & Loewenstein, 2016; Wojtowicz, Chater, & Loewenstein, 2022).…”

Section: Case Studies: How I-frame Behavioral Public Policy Went Wrongmentioning

confidence: 99%

The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray

Chater¹,

Loewenstein²

2022

Behav Brain Sci

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An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: to adopt what we call the “i-frame,” rather than the “s-frame.” The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contributed to public policy is by employing their skills to develop and implement value-creating system-level change.

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Section: Case Studies: How I-frame Behavioral Public Policy Went Wrongmentioning

confidence: 99%

The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray

Chater¹,

Loewenstein²

2022

Behav Brain Sci

Self Cite

234

140

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“…Fourth, the idea that our generic causal claims about the social world reflect our cognitive budgets has roots in the literature on the psychology of categorization, e.g., Rosch (1978). Given the close connection between compression and more general cognitive processes like sensemaking and understanding (Kirfel et al, 2021;Marzen & DeDeo, 2017;Pacer & Lombrozo, 2017;Wilkenfeld, 2019;Wojtowicz et al, 2021), it is likely the case that even if the granularity of our causal claims about the social world is determined largely by our agential interests, the particular compressed social categories that we use in these explanations can be taken as evidence for how agents make sense of their social world more broadly. Thus, our results here suggest a more general connection between decision theory, representation, and sense-making in human cognition.…”

Section: Discussionmentioning

confidence: 99%

Tell Me Your (Cognitive) Budget and I'll Tell You What You Value

Kinney,

Lombrozo

2024

Preprint

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Consider the following two (hypothetical) generic causal claims: “Living in a neighborhood with many families with children increases purchases of bicycles” and “living in an affluent neighborhood with many families with children increases purchases of bicycles.” These claims not only differ in what they suggest about how bicycle ownership is distributed across different neighborhoods (i.e., “the data”), but also have the potential to communicate something about the speakers’ values: namely, the prominence they accord to affluence in representing and making decisions about the social world. Here, we examine the relationship between the level of granularity with which a cause is described in a generic causal claim (e.g., neighborhood vs. affluent neighborhood) and the value of the information contained in the causal model that generates that claim. We argue that listeners who know any two of the following can make reliable inferences about the third: 1) the level of granularity at which a speaker makes a generic causal claim, 2) the speaker’s values, and 3) the data available to the speaker. We present results of four experiments (N=1,323) in the domain of social categories that provide evidence in keeping with these predictions.

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“…Behavioral science provides a powerful i-frame analysis of why people are so vulnerable to misinformation---and should be taken to imply that protecting against these vulnerabilities requires s-level interventions. People are excessively credulous (Gilbert, Tafarodi & Malone, 1993), strongly underestimate the power of conflicts of interests (Dana & Loewenstein, 2003), and are influenced by the many non-epistemic benefits of new information: reducing cognitive dissonance, shoring up personal beliefs systems, creating or cementing identification with 'likeminded' others, providing ammunition in hypothetical or real debates, and many more (Chater & Loewenstein, 2016;Wojtowicz, Chater & Loewenstein, 2022).…”

Section: Misinformationmentioning

confidence: 99%