How do humans build better explanations?

Human beings do not merely accumulate beliefs. They organize beliefs, values, identities, and experiences into explanatory structures that allow them to make sense of themselves and the world. Although existing research offers powerful accounts of belief formation, cognitive organization, explanation, and belief revision, many approaches treat beliefs, narratives, or representations as the primary cognitive objects of interest. I argue that these phenomena are more fruitfully understood as components of higher-order explanatory frameworks: cognitive architectures that integrate diverse forms of information into coherent understandings and that are periodically reorganized as new experiences accumulate. The article develops a general theory of explanatory frameworks, identifies their defining properties, distinguishes them from related concepts, and advances a set of theoretical propositions concerning their organization, growth, and revision. Finally, I argue that recent advances in conversational elicitation provide empirical access to explanatory-framework organization and revision, allowing researchers to study these structures beyond what can be inferred from isolated beliefs or attitudes. Reconceptualizing human reasoning around explanatory frameworks offers a foundation for research on learning, judgment, belief revision, and political reasoning.

Human beings do not simply accumulate beliefs. They organize beliefs, values, experiences, and identities into increasingly encompassing explanations capable of making sense of themselves and the world. This book develops a general theory of these explanatory frameworks. It argues that explanatory frameworks constitute a higher-order cognitive architecture through which people organize experience, generate beliefs, and reorganize their understanding over time. Rather than treating learning as the acquisition of isolated facts or attitudes, the theory reconceptualizes learning as the growth of increasingly encompassing explanatory frameworks. Drawing together evidence from political reasoning, cognitive science, philosophy, education, and artificial intelligence, the book proposes explanatory frameworks as a fundamental object of study for understanding human judgment, learning, and belief revision across domains.

How do social norms surrounding racial attitudes differ among white Democrats and Republicans? Do these norms differ from the prevailing ‘norm of equality,’ and how do they affect civic discourse? Using a novel video-based discussion experiment, I show how co-partisan discussion among white Republicans (versus talking to a white Democrat) increases their racial resentment, as measured both in post-treatment surveys and the rhetoric subjects use during discussion. White Democrats do not significantly change their racial attitudes or rhetoric according to the partisan identity of their discussion partner. Among white Republicans, racially resentful language increases by more than 10% when discussing politics with a co-partisan compared to conversing with a white Democrat. This result is driven by the partisan identity of the discussion partner rather than the content of their speech. Even when a co-partisan takes a position on race-related policy that is counter-typical to their party (such as a Republican supporting affirmative action), white Republicans still use significantly more racially resentful language than when they talk to a Democrat, even one who ‘sounds like’ a Republican on race-policy. Findings highlight polarization as a democratic social ill, suggesting consequences for American civic discourse around race.

The claim that partisanship has developed into a social identity is one of the dominant explanations for the current rising levels of affective polarization among the U.S. electorate. We provide evidence that partisanship functions as a social identity, but that the salience of partisan identity—in and of itself—does not account for increased affective polarization. Using a two-wave panel survey capturing natural variation in the salience of politics, we find that partisanship contributes more to individuals’ self-concept in times of heightened political salience. We also show that partisans can be detached from their Democratic or Republican identity by having them focus on individuating characteristics through a self-affirmation treatment. However, we find only limited evidence that when partisan social identity is made less salient, either by way of natural variation in political context or through a self-affirmation treatment, partisans are any less inclined to express in-party favoritism and out-party hostility. Taken together, our evidence shows that partisanship does operate as an important social identity, but that affective polarization is likely attributable to more than the classic in-group versus out-group distinction.

To what extent does ideological constraint emerge through political conversation? Existing research typically treats ideological constraint as a stable property of individuals' belief systems. Using more than 800 transcripts from experimentally moderated political discussions, this paper examines whether the apparent coherence of political beliefs depends partly on the conversational environments in which they are expressed. Participants discussed police reform, affirmative action, abortion, and climate change with confederates whose partisan identity and ideological consistency were experimentally varied. While participants' policy positions shifted primarily in response to the arguments they encountered rather than the confederate's partisan identity, the apparent constraint among their expressed attitudes also changed systematically. Correlations across political positions were stronger following conversations with ideologically orthodox Democrats and Republicans than after discussions with counter-typical partisans. These findings suggest that ideological constraint is not solely an internal cognitive property but can emerge through interaction with others. More broadly, the study demonstrates the value of combining experimental interventions with conversational data to study the organization of political belief systems.

How do people maintain coherence among political beliefs that do not naturally fit together? Existing research has devoted considerable attention to why individuals hold particular political attitudes and when those attitudes change, yet we know remarkably little about the organization of the explanatory frameworks that hold those attitudes together. Using transcripts from a large-scale conversational study, this paper describes recurring patterns in the structure of political reasoning by examining how participants connect principles, values, empirical assumptions, identities, and lived experience into coherent explanations. Rather than revealing a single form of coherence, the analyses identify multiple organizational patterns through which explanatory frameworks accommodate competing commitments, absorb new information, or leave tensions unresolved. These findings suggest that political disagreement is often rooted not in isolated differences over individual beliefs, but in differences in how explanatory frameworks organize and prioritize those beliefs. By providing a descriptive account of the internal organization of explanatory frameworks, the paper establishes a foundation for studying political reasoning as a dynamic process of explanatory integration rather than a collection of independent attitudes.

This project investigates when conventional survey responses accurately capture the reasoning people express during conversation. It contributes to the broader research agenda by examining the relationship between static attitude measures and the explanatory frameworks revealed through dialogue.