Hostname: page-component-cc8bf7c57-pd9xq Total loading time: 0 Render date: 2024-12-11T16:29:27.121Z Has data issue: false hasContentIssue false

Analytical Democratic Theory: A Microfoundational Approach

Published online by Cambridge University Press:  01 August 2022

HENRY FARRELL*
Affiliation:
Johns Hopkins University, United States
HUGO MERCIER*
Affiliation:
Institut Jean Nicod, France
MELISSA SCHWARTZBERG*
Affiliation:
New York University, United States
*
Henry Farrell, Stavros Niarchos Foundation Agora Institute Professor of International Affairs, Johns Hopkins School of Advanced International Studies, Johns Hopkins University, United States, henry.farrell@gmail.com.
Hugo Mercier, Permanent CNRS Research Scientist, Institut Jean Nicod, Département d’études cognitives, ENS, EHESS, PSL University, CNRS, France, hugo.mercier@gmail.com.
Melissa Schwartzberg, Silver Professor of Politics, Department of Politics, New York University, United States, ms268@nyu.edu.
Rights & Permissions [Opens in a new window]

Abstract

A prominent and publicly influential literature challenges the quality of democratic decision making, drawing on political science findings with specific claims about the ubiquity of cognitive bias to lament citizens’ incompetence. A competing literature in democratic theory defends the wisdom of crowds, drawing on a cluster of models in support of the capacity of ordinary citizens to produce correct outcomes. In this Letter, we draw on recent findings in psychology to demonstrate that the former literature is based on outdated and erroneous claims and that the latter is overly sanguine about the circumstances that yield reliable collective decision making. By contrast, “interactionist” scholarship shows how individual-level biases are not devastating for group problem solving, given appropriate conditions. This provides possible microfoundations for a broader research agenda similar to that implemented by Elinor Ostrom and her colleagues on common-good provision, investigating how different group structures are associated with both success and failure in democratic decision making. This agenda would have implications for both democratic theory and democratic practice.

Type
Letter
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the American Political Science Association

Over the last 15 years a prominent academic literature tied to libertarian thought has argued that democracy is generally inferior to other forms of collective problem solving such as markets and the rule of cognitive elites (Brennan Reference Brennan2016; Caplan Reference Caplan2008; Somin Reference Somin2016). Following a long tradition of skepticism about democracy, these libertarians appeal to findings in cognitive and social psychology and political behavior to claim that decision making by ordinary citizens is unlikely to be rational or well grounded in evidence. Their arguments have been covered in magazines such as the New Yorker (Crain Reference Crain2016) and popularized in proposals in the National Review for restrictions to dissuade “ignorant” people from voting (Mathis-Lilley Reference Mathis-Lilley2021). Democratic theorists have mostly retorted with “epistemic” accounts, invoking mechanisms through which citizens can potentially reach good decisions—most significantly, deliberative mechanisms (Schwartzberg Reference Schwartzberg2015).

This debate has been largely unproductive. Libertarian skeptics argue that democracy is generally inferior because of incorrigible flaws in citizens’ individual psychology, whereas democratic theorists lack a shared, compelling, and realistic micropsychological theory within which to ground their broader claims. Each side emphasizes empirical evidence that appears to support its own interpretation while discounting counterevidence.

This letter adopts a different approach. It demonstrates that democratic skeptics’ pessimistic conclusion—that democracy is unfixable—rests on a misleading and outdated account of the relevant psychological literature. Similarly, epistemic democrats often overestimate deliberation’s role in producing wise results or assume that aggregative models will operate at scale. We seek to avoid unwarranted skepticism and enthusiasm alike, instead providing microfoundations for a more empirically robust program investigating both the successes and mishaps of democracy, drawing on the experimental psychological literature on group problem solving (inter alia) to discover the conditions under which specific institutions perform well or fail in discovering solutions to collective problems.

Adapting a term from past debates, we contribute one foundational element of an approach that might be dubbed “analytical democracy.” Like the “analytical Marxism” associated with scholars such as G. A. Cohen, Jon Elster, John Roemer, and Adam Przeworski (see Roemer Reference Roemer1986), we provide more demanding and specific microfoundations for an account we find broadly sympathetic. Our research program might also be analogized to Ostrom’s work on the decentralized provision of common goods (Ostrom Reference Ostrom1990). This emerged in response to Garrett Hardin’s influential article on “the tragedy of the commons,” which claimed that common-goods governance would inevitably collapse (Hardin Reference Garrett1968). Ostrom and her colleagues tested and falsified Hardin’s claims. However, rather than simply defending the proposition that decentralized communities could provide common goods, they investigated when common-good provision was likely to succeed or fail. Similarly, a research program on democratic problem solving, investigating success and failure, might not only provide possible foundations for a truly realistic account of democracy but also generate practical advice on building and improving democratic institutions. This program would build on research on the consequences of group composition and structure to understand the conditions under which democratic problem solving will operate well or badly.

Democratic Skepticism, Optimism and Social Science

A recent pessimistic literature, dominated by libertarian scholars, diagnoses widespread democratic ignorance and incompetence. Bryan Caplan (Reference Caplan2008, 19) asserts that voters are irrational and “rule by demagogues … is the natural condition of democracy.” Jason Brennan believes that the democratic electorate is “systematically incompetent” so “some people ought not have the right to vote, or ought to have weaker voting rights than others” (Reference Brennan2016, 201, viii). Ilya Somin claims that “widespread public ignorance is a type of pollution” so that “democracy might function better if its powers were more tightly limited” (Reference Somin2016, 6, 9).

Each argues that democracy is profoundly flawed because of irremediable problems in individual incentives and cognition. Each proposes circumscribing democracy in favor of some purportedly superior alternative principle of social organization. Caplan claims that markets impose an effective “user fee” for irrationality that is absent from democracy (Reference Caplan2008, 133–4). Brennan proposes “epistocracy,” an aristocracy of those who know best. He defends restrictions on suffrage, identifying familiar possibilities such as restricting the franchise to those who pass a voter qualification exam and assigning plural votes to college graduates. Somin advocates what he calls “foot voting” (exit) over “ballot box voting” and emphasizes “the market and civil society as an alternative to government” (Reference Somin2016, 154), although he admits that the benefits “are likely to vary from issue to issue, from nation to nation, and perhaps also from group to group” (180).

These scholars ground their claims in social science findings. They invoke a literature leading back to Downs’s (Reference Downs1957) argument that citizens are rationally ignorant about politics because they do not have sufficient incentive to gather good information or to make good decisions. They emphasize that ordinary citizens display severe cognitive bias. Caplan (Reference Caplan2008) blames such biases for differences between voters’ beliefs about economics and the beliefs of PhD economists, which he takes as a reasonable representation of empirical truth. Brennan (Reference Brennan2016, 37ff) and Somin (Reference Somin2016, 94ff) cite work showing that biases lead people to search for information that supports their prior views and “not only reject new information casting doubt on their beliefs but sometimes actually respond by believing in them even more fervently” (Somin Reference Somin2016, 93–4; invoking the “backfire effects” described in Nyhan and Reifler Reference Nyhan and Reifler2010).

Brennan (Reference Brennan2016, 40) unites rational ignorance and cognitive bias into a single stylized account in which most voters are either low information “hobbits” (ignorant) or politically fanatical “hooligans” (biased). He invokes Mercier and Sperber’s explanation of how “[r]easoning was not designed to pursue the truth. Reasoning was designed by evolution to help us win arguments” (Reference Brennan2016, 38). Furthermore, “human beings are wired not to seek truth and justice but to seek consensus… . They cower before uniform opinion” (Brennan Reference Brennan2012, 8; see also Reference Brennan2016, 47) as demonstrated by the famous Asch (Reference Asch1956) “conformity experiments,” where participants followed the obviously false opinions of confederates who were sitting next to them.

Achen and Bartels’ (Reference Achen and Bartels2016) “realist” account of democracy does not share the skeptics’ normative priors but provides a similarly bleak judgment. They too draw on Asch and “similar studies” for social psychological microfoundations that stress the force of group identity and conformity (Reference Achen and Bartels2016, 220).

There is little scope for democratic problem solving if individual consensus seeking invariably leads to group conformity and “echo chambers” (Sunstein Reference Sunstein2002), affective polarization (Iyengar et al. Reference Iyengar2018), the rejection of countervailing arguments from nongroup members, and backfire effects. Yet it is far from clear that the despairing picture is empirically accurate. Growing affective polarization may not increase ideological polarization and extremism (e.g., Desmet and Wacziarg Reference Desmet and Wacziarg2021). People’s economic beliefs are affected by economic reality (e.g. Duch and Stevenson Reference Duch and Stevenson2008). Party leaders influence party members on some issues but on others adopt what they perceive to be the public’s dominant opinion (Lenz Reference Lenz2013). Backfire effects are the exception, not the rule (Nyhan Reference Nyhan2021; Wood and Porter Reference Wood and Porter2019). People generally change their minds when presented with well-sourced facts and good arguments (see, e.g., Nyhan et al. Reference Nyhan, Porter, Reifler and Wood2020; Sides Reference Sides2015).

In part, we do not see the expected universally negative consequences because citizens are not as ignorant as the skeptical consensus suggests. “Issue publics,” whose members acquire specialized information on a particular issue across a spectrum of opinion (Converse Reference Converse1964), provide an important epistemic resource for democracy (Elliott Reference Elliott2020; Han Reference Han2009). Citizens do better on domain-specific knowledge, including information about candidates’ positions on issues they care about (Henderson Reference Henderson2014; Krosnick Reference Krosnick1990), than on the surveys of general factual information that skeptics rely on.

More fundamentally, individual-level biases are not devastating for collective democratic problem solving. The psychological literature on group effects and individual cognition is systematically misunderstood by skeptics and underexploited by political scientists. Contrary to Brennan’s (Reference Brennan2016) misinterpretation, scholars like Mercier and Sperber (Reference Mercier and Sperber2017) find that even if humans are subject to “myside bias,” they can filter out erroneous messages (including those from their “side”) and change their minds when presented with good evidence from the other “side.” A realistic understanding of the capacities of democratic citizens need not be altogether bleak.

But it should not be overly sanguine. Democratic theorists (including those who are interested in practicalities) often rely on either conjecture or quasi-empirical claims. For instance, David Estlund argues that democratic procedures will tend to outperform non-democratic ones epistemically while acknowledging that the claim is conjectural rather than empirical (Reference Estlund2008, 157, 160, 176). Hélène Landemore (Reference Landemore2020, 8) asserts more forcefully that what she calls “open democracy” is empirically superior to other forms of social decision making: “in a complex and uncertain world, … empowering all members of the demos equally … is overall the best method we have to figure out solutions to common problems.”

We lack a research framework for establishing whether this strong assertion is more robust than competing claims from those who champion different forms of democratic decision making or who emphasize the possibility of democratic failure. Even if deliberation and other forms of reasoned exchange are morally valuable, they may not necessarily yield superior solutions to problems. Extrapolations such as Landemore’s (Reference Landemore2013, 104) “Numbers Trump Ability” postulate that democracy can readily be scaled up so that “if twelve jurors are smarter than one, then so would forty-one or 123 jurors,” building on Hong and Page’s (Reference Hong and Page2004) “Diversity Trumps Ability” theorem. Such claims are qualified by empirical findings from jury deliberations (Watanabe Reference Watanabe2020) and Hong and Page’s later prediction that increasing group size does not necessarily improve problem-solving capability (Hong and Page Reference Hong and Page2021).

To move away from general claims for democracy’s superiority, epistemic democrats need to understand not just when democracy works but also when it doesn’t. Neblo et al. (Reference Neblo2017, 915) establish an important possibility claim by showing how “scholars have assembled strong evidence that deliberative institutions positively influence citizens.” Still, it is hard to build from such demonstrations to a properly scientific account that can explain both democratic success and failure without some externally grounded theory of human decision making. Similarly, there is no very straightforward way of moving from a demonstration that Habermasian claims for deliberation can be grounded in plausible psychological mechanisms (Minozzi and Neblo Reference Minozzi and Neblo2015) to a broader account of when these mechanisms will or will not operate.

Surprisingly, possible microfoundations for such an account can be found in the literature on group psychology and cognition that skeptics have deployed against democracy. As Landemore (Reference Landemore2013, 143) says, the “argumentative theory of reasoning” allows us to predict where deliberation will and will not work well. This is a pivotally important claim: we need to know where deliberation will function well to empirically assess theories of institutional design and practical justifications of democracy.

The argumentative account of reasoning is grounded in a recent “interactionist” literature in psychology, which explores how individual bias may or may not be corrected through social interaction. It investigates how mechanisms of “epistemic vigilance” allow people to employ cues to evaluate communicated information including the expertise and benevolence of the source, the plausibility of the message, and the quality of the arguments (for an overview, see Mercier Reference Mercier2020; Sperber et al. Reference Sperber2010). Chambers (Reference Chambers2018) has also identified both the interactionist approach and the empirical literature on deliberation as reasons to doubt skeptical claims based on group psychology.

For example, contrary to skeptical claims that people conform to majority opinion, the experimental literature finds that people take account of relevant cues when evaluating the majority opinion including the absolute and relative size of the majority, the competence and benevolence of the majority’s members, the degree of dependency in the opinions of the majority, and the plausibility of the opinion (for review, see Mercier and Morin Reference Mercier and Morin2019). The much-bruited Asch (Reference Asch1956) experiments describe the consequences of external pressure rather than those of internalized bias. Practically no one was influenced when participants did not have to voice their opinion in front of the group, and contrary to the widespread academic folklore (Friend, Rafferty, and Bramel Reference Friend, Rafferty and Bramel1990), the experiments demonstrated independence as well as conformity. The literature finds that people are well able to evaluate arguments, that they are more influenced by strong than weak reasons (e.g., Hahn and Oaksford Reference Hahn and Oaksford2007), and that they partly change their minds when confronted with challenging but good arguments (e.g., Guess and Coppock Reference Guess and Coppock2020).

Interactionist scholarship suggests that reasoning processes are best evaluated in their normal environment of social interaction. It provides possible microfoundations for theories of variation. Instead of looking to the (supposedly invariant) cognitive limitations of ordinary citizens as skeptics do, an interactionist approach suggests that we should investigate the social context of decisions—how groups are structured—to understand when group identity and social pressure can distort or swamp problem solving. Both problem-solving capacity (which depends on whether groups harness individual biases and mechanisms of epistemic vigilance) and collective pressures to conformity will plausibly vary with group structure. Skeptical accounts, which depict group politics as simple condensates of individual bias writ large, are poorly fitted to capturing this variation. Equally, interactionism provides microfoundations for a framework that can investigate democratic theorists’ findings about when democracy works well while also investigating democratic failure.

This provides a more promising path forward than does the universal pessimism of democratic skeptics. It also provides more robust foundations for the claim that deliberation can occur under psychologically realistic circumstances and a starting point for investigating what those circumstances are. Democratic “realists” like Achen and Bartels (Reference Achen and Bartels2016) need not be democratic pessimists. A microfoundational approach, grounded in endemic individual cognitive bias, avoids the possible charge that the desired normative outcomes are baked into the initial empirical assumptions.

If outright democratic skeptics are sincerely committed to understanding the cognitive underpinnings of democratic processes, as their reliance on this literature ought to entail, they too should find it attractive. It allows the serious investigation of observed democratic failure as well as democratic success. Of course, these are not the only possible microfoundations, and like all empirically based accounts, they may be modified or even rejected as empirical evidence emerges.

Still, such microfoundations could support a broader analytical account that seeks to understand and address variation. If both the benefits and disadvantages of democracy arise at the group rather than individual level, then the challenge for advocates of democracy is to build democratic institutions that can better trigger the relevant cognitive mechanisms so as to capture the benefits of group problem solving instead of deferring to the social pressures that do sometimes lead to conformity. In other words, our goal is to better explain how democracy incorporates the capacities of groups to solve problems (under some circumstances) as well as their tendency to magnify conformity and factionalism (under others).

We do not provide a complete alternative account of democracy here. That would be a heroic undertaking, which would involve not just providing microfoundations but rebuilding existing institutional and organizational theories on their basis. Instead, we sketch the beginnings of a broader research program that we hope others will find attractive.

A Research Program on Democratic Problem Solving

Ostrom (Reference Ostrom1990) began by demonstrating the systematic flaws in Hardin’s skepticism of common goods but went on to articulate a coherent alternative research agenda on the conditions under which common goods provision succeeds or fails. Political science and related disciplines should commence a similar research program, uniting scientific research on group composition, network structure, and institutional form to investigate the conditions under which democratic problem solving is likely to succeed or fail.

As we have argued, this program could build on research in experimental cognitive psychology, which provides an alternative set of microfoundations to both rational choice and the social psychological arguments that have dominated political science debates. Specifically, this research identifies specific dimensions along which trade-offs in group problem solving plausibly occur:

By understanding how different positions in this multidimensional space are associated with better or worse problem solving, we can arrive at useful hypotheses about how to fashion democratic systems. This research program should also incorporate scholarship on a broader level of social aggregation, which explores how network structure and social influence affect flows of information and opinion between individuals with different perspectives (Feng et al. Reference Feng, Teplitskiy, Duedec and Evans2019). It might incorporate practical findings about democratic decision making—for instance, the circumstances under which juries can form more accurate collective beliefs (Salerno and Diamond Reference Salerno and Diamond2010) and how citizen constitutional assemblies (Farrell and Suiter Reference Farrell and Suiter2019) and online town halls (Neblo, Esterling, and Lazer Reference Neblo, Esterling and Lazer2018) can support better communication between politicians and the public.

Crucially, the proposed research program would investigate democratic failures as well as successes, better explaining, for example, the circumstances under which epistemic breakdown and misinformation can become established in democracies. O’Connor and Weatherall (Reference O’Connor and Weatherall2018; Weatherall and O’Connor Reference Weatherall and O’Connor2021) investigate how epistemic factionalization occurs among people who do not trust others with different beliefs. Nyhan (Reference Nyhan2021) emphasizes the importance of elite messaging and information decay in spreading misinformation, suggesting that punishing elites who spread falsehoods and focusing on intermediaries may have benefits.

Finally, such a research program would help address recent (Neblo et al. Reference Neblo2017) and current (Notes from the Editors 2020) demands for a “translational” approach to democracy that “challenges dominant disciplinary norms.” It would seek to reconcile scientific rigor with normative analysis, providing the groundwork for institutional improvement and reform.

ACKNOWLEDGMENTS

The authors gratefully acknowledge comments from Hahrie Han, Melanie Mitchell, Scott Page, and John Sides, as well as participants in a seminar at the Santa Fe Seminar on Collective Intelligence in Natural and Artificial Systems on August 31, 2021. We also appreciate the particularly helpful advice we received from the three anonymous reviewers for the APSR.

CONFLICT OF INTEREST

The authors declare no ethical issues or conflicts of interest in this research.

ETHICAL STANDARDS

The authors affirm this research did not involve human subjects.

References

REFERENCES

Achen, Christopher, and Bartels, Larry. 2016. Democracy for Realists: Why Elections Do Not Produce Responsive Government. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Asch, Solomon. 1956. “Studies of Independence and Conformity: A Minority of One against a Unanimous Majority.” Psychological Monographs 70 (9): 170.CrossRefGoogle Scholar
Brennan, Jason. 2012. The Ethics of Voting. Princeton, NJ: Princeton University Press.Google Scholar
Brennan, Jason. 2016. Against Democracy. Princeton, NJ: Princeton University Press.Google Scholar
Baron, Robert. S. 2005. “So Right It’s Wrong: Groupthink and the Ubiquitous Nature of Polarized Group Decision Making.” In Advances in Experimental Social Psychology, vol. 37, ed. Zanna, Mark, 219–53. San Diego, CA: Elsevier Academic Press.Google Scholar
Caplan, Bryan. 2008. The Myth of the Rational Voter: Why Democracies Choose Bad Policies. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Chambers, Simone. 2018. “Human Life is Group Life: Deliberative Democracy for Realists.” Critical Review 30 (1–2): 3648.CrossRefGoogle Scholar
Converse, Philip E. 1964. “The Nature of Belief Systems in Mass Publics.” Critical Review 18 (1–3): 174.CrossRefGoogle Scholar
Crain, Caleb. 2016. “The Case against Democracy.” New Yorker, November 7, 2016.Google Scholar
Desmet, Klaus, and Wacziarg, Romain. 2021. “The Cultural Divide.” Economic Journal 131 (637): 2058–88.CrossRefGoogle Scholar
Downs, Anthony. 1957. An Economic Theory of Democracy. New York: Harper and Row.Google Scholar
Duch, Raymond M., and Stevenson, Randolph T.. 2008. The Economic Vote: How Political and Economic Institutions Condition Election Results. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Elliott, Kevin J. 2020. “Democracy’s Pin Factory: Issue Specialization, the Division of Cognitive Labor, and Epistemic Performance.” American Journal of Political Science 64 (2): 385–97.CrossRefGoogle Scholar
Estlund, David. 2008. Democratic Authority: A Philosophical Framework. Princeton, NJ: Princeton University Press.Google Scholar
Farrell, David M., and Suiter, Jane. 2019. Reimagining Democracy: Lessons in Deliberative Democracy from the Irish Front Line. Philadelphia: University of Pennsylvania Press.CrossRefGoogle Scholar
Fay, Nicolas, Garrod, Simon, and Carletta, Jean. 2000. “Group Discussion as Interactive Dialogue or as Serial Monologue: The Influence of Group Size.” Psychological Science 11: 481–86.CrossRefGoogle ScholarPubMed
Feng, Shi, Teplitskiy, Misha, Duedec, Eamon, and Evans, James A.. 2019. “The Wisdom of Polarized Crowds.” Nature Human Behaviour 3: 329–36.Google Scholar
Friend, Ronald, Rafferty, Yvonne, and Bramel, Dana. 1990. “A Puzzling Misinterpretation of the Asch ‘Conformity’ Study.’European Journal of Social Psychology 20 (1): 2944.CrossRefGoogle Scholar
Guess, Andrew, and Coppock, Alexander. 2020. “Does Counter-Attitudinal Information Cause Backlash? Results from Three Large Survey Experiments.” British Journal of Political Science 50 (4): 14971515.CrossRefGoogle Scholar
Hahn, Ulrike, and Oaksford, Mike. 2007. “The Rationality of Informal Argumentation: A Bayesian Approach to Reasoning Fallacies.” Psychological Review 114 (3): 704–32.CrossRefGoogle ScholarPubMed
Han, Hahrie. 2009. Moved to Action. Motivation, Participation, and Inequality in American Politics. Redwood City, CA: Stanford University Press.Google Scholar
Garrett, Hardin. 1968. “The Tragedy of the Commons.” Science. 162 (3859): 1243–48.Google Scholar
Henderson, Michael. 2014. “Issue Publics, Campaigns, and Political Knowledge.” Political Behavior 36 (3): 631–57.CrossRefGoogle Scholar
Hong, Lu, and Page, Scott. 2004. “Groups of Diverse Problem Solvers Can Outperform Groups of High-Ability Problem Solvers.” Proceedings of the National Academy of Sciences 101 (46): 16385–389.CrossRefGoogle ScholarPubMed
Hong, Lu, and Page, Scott. 2021. “The Contributions of Diversity, Accuracy and Group Size on Collective Accuracy.” Working Paper.Google Scholar
Iyengar, Shanto, Yphtach Lelkes, Matthew Levendusky, Neil Malhotra, and Sean J. Westwood. 2018. “The Origins and Consequences of Affective Polarization.” Annual Review of Political Science 21:129–46.Google Scholar
Krosnick, Jon. 1990. “Government Policy and Citizen Passion: A Study of Issue Publics in Contemporary America.” Political Behavior 12 (1): 5992.CrossRefGoogle Scholar
Landemore, Hélène. 2013. Democratic Reason: Politics, Collective Intelligence, and the Rule of the Many. Princeton, NJ: Princeton University Press.Google Scholar
Landemore, Hélène. 2020. Open Democracy: Reinventing Popular Rule for the Twenty-First Century. Princeton, NJ: Princeton University Press.Google Scholar
Lenz, Gabriel. 2013. Follow the Leader?: How Voters Respond to Politicians’ Policies and Performance. Chicago, IL: University of Chicago Press.Google Scholar
Mathis-Lilley, Ben. 2021. “National Review Comes out against Voting, Explicitly.” Slate, April 9.Google Scholar
Mercier, Hugo, and Sperber, Dan. 2017. The Enigma of Reason. Cambridge, MA: Harvard University Press.Google Scholar
Mercier, Hugo. 2020. Not Born Yesterday: The Science of Who we Trust and What we Believe. Princeton, NJ: Princeton University Press.Google Scholar
Mercier, Hugo, and Claidière, Nicolas. 2022. “Does Discussion Make Crowds Any Wiser?Cognition 222: article 104912.CrossRefGoogle ScholarPubMed
Mercier, Hugo, and Morin, Olivier. 2019. “Majority Rules: How Good Are We at Aggregating Convergent Opinions?Evolutionary Human Sciences 1. doi:10.1017/ehs.2019.6.CrossRefGoogle Scholar
Minozzi, William, and Neblo, Michael. 2015. “Thrasymachus’s Blush: The Science and Politics of Motivated Reasoning and ‘Principled Rhetoric.’” (unpublished manuscript, March 2, 2015). Department of Political Science, Ohio State University.Google Scholar
Neblo, Michael, William Minozzi, Kevin M. Esterling, Jon Green, Jonathon Kingzette, and David M. J. Lazer. 2017. “The Need for a Translational Science of Democracy.” Science 355 (6328): 914–15.CrossRefGoogle ScholarPubMed
Neblo, Michael, Esterling, Kevin, Lazer, David. 2018. Politics with the People: Building a Directly Representative Democracy. New York: Cambridge University Press.CrossRefGoogle Scholar
Notes from the Editors. 2020. American Political Science Review 114 (4): v–vii.CrossRefGoogle Scholar
Nyhan, Brendan. 2021. “Why the Backfire Effect Does Not Explain the Durability of Political Misperceptions.” Proceedings of the National Academy of Science 118: e1912440117.CrossRefGoogle ScholarPubMed
Nyhan, Brendan, Porter, Ethan, Reifler, Jason, and Wood, Thomas. 2020. “Taking Corrections Literally but Not Seriously? The Effects of Information on Factual Beliefs and Candidate Favorability.” Political Behavior 42: 939–60.CrossRefGoogle Scholar
Nyhan, Brendan, and Reifler, Jason. 2010. “When Corrections Fail: The Persistence of Political Misperceptions.” Political Behavior 32 (2): 303–30.CrossRefGoogle Scholar
O’Connor, Cailin, and Weatherall, James. 2018. “Scientific Polarization.” European Journal for Philosophy of Science 8 (3): 855–75.CrossRefGoogle Scholar
Origgi, Gloria. 2017. Reputation: What It Is and Why It Matters. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Ostrom, Elinor. 1990. Governing the Commons: The Evolution of Institutions for Collective Action. New York: Cambridge University Press.CrossRefGoogle Scholar
Roemer, John, ed. 1986. Analytical Marxism. Cambridge: Cambridge University Press.Google Scholar
Salerno, Jessica M., and Diamond, Shari Seidman. 2010. “The Promise of a Cognitive Perspective on Jury Deliberation.” Psychonomic Bulletin & Review 17 (2): 174–79.CrossRefGoogle ScholarPubMed
Schwartzberg, Melissa. 2015. “Epistemic Democracy and Its Challenges.” Annual Review of Political Science 18:187203.CrossRefGoogle Scholar
Schulz-Hardt, Stefan, Brodbeck, Felix C., Mojzisch, Andreas, Kerschreiter, Rudolf, and Frey, Dieter. 2006. “Group Decision Making in Hidden Profile Situations: Dissent as a Facilitator for Decision Quality.” Journal of Personality and Social Psychology 91 (6): 1080–93.CrossRefGoogle ScholarPubMed
Sides, John. 2015. “Stories or Science? Facts, Frames and Policy Attitudes.” American Politics Research 44 (3): 387–14.CrossRefGoogle Scholar
Somin, Ilya. 2016. Democracy and Political Ignorance: Why Smaller Government Is Smarter. Redwood City, CA: Stanford University Press.Google Scholar
Sperber, Dan, Fabrice Clément, Christophe Heintz, Olivier Mascaro, Hugo Mercier, Gloria Origgi, and Deirdre Wilson. 2010. “Epistemic Vigilance.” Mind and Language 25 (4): 359–93.CrossRefGoogle Scholar
Stasser, Garold, and Titus, William. 1985. “Pooling of Unshared Information in Group Decision Making: Biased Information Sampling during Discussion.” Journal of Personality and Social Psychology 48 (6): 1467.CrossRefGoogle Scholar
Sunstein, Cass. 2002. “The Law of Group Polarization.” Journal of Political Philosophy 10 (2): 175–95.CrossRefGoogle Scholar
Watanabe, Takamitsu. 2020. “A Numerical Study on Efficient Jury Size.” Humanities and Social Sciences Communications 7 (62). https://doi.org/10.1057/s41599-020-00556-1.CrossRefGoogle Scholar
Weatherall, James Owen, and O’Connor, Cailin. 2021. “Endogenous Epistemic Factionalization.” Synthese 198:61796200.CrossRefGoogle Scholar
Wood, Thomas, and Porter, Ethan. 2019. “The Elusive Backfire Effect: Mass Attitudes’ Steadfast Factual Adherence.” Political Behavior 41 (1): 135–63.CrossRefGoogle Scholar
Submit a response

Comments

No Comments have been published for this article.