Christian List

We offer a new argument for the claim that there can be non-degenerate objective chance (“true randomness”) in a deterministic world. Using a formal model of the relationship between different levels of description of a system, we show how objective chance at a higher level can coexist with its absence at a lower level. Unlike previous arguments for the level-specificity of chance, our argument shows, in a precise sense, that higher-level chance does not collapse into epistemic probability, despite higher-level properties supervening on lower-level ones. We show that the distinction between objective chance and epistemic probability can be drawn, and operationalized, at every level of description. There is, therefore, not a single distinction between objective and epistemic probability, but a family of such distinctions.

In this paper, I introduce the emerging theory of judgment aggregation as a framework for studying institutional design in social epistemology. When a group or collective organization is given an epistemic task, its performance may depend on its ‘aggregation procedure’, i.e. its mechanism for aggregating the group members’ individual beliefs or judgments into corresponding collective beliefs or judgments endorsed by the group as a whole. I argue that a group’s aggregation procedure plays an important role in determining whether the group can meet two challenges: the ‘rationality challenge’ and the ‘knowledge challenge’. The rationality challenge arises when a group is required to endorse consistent beliefs or judgments; the knowledge challenge arises when the group’s beliefs or judgments are required to track certain truths. My discussion seeks to identify those properties of an aggregation procedure that affect a group’s success at meeting each of the two challenges.

The systems studied in the special sciences are often said to be causally autonomous, in the sense that their higher-level properties have causal powers that are independent of the causal powers of their more basic physical properties. This view was espoused by the British emergentists, who claimed that systems achieving a certain level of organizational complexity have distinctive causal powers that emerge from their constituent elements but do not derive from them. More recently, non-reductive physicalists have espoused a similar view about the causal autonomy of special-science properties. They argue that since these properties can typically have multiple physical realizations, they are not identical to physical properties, and further they possess causal powers that differ from those of their physical realisers. Despite the orthodoxy of this view, it is hard to find a clear exposition of its meaning or a defence of it in terms of a well-motivated account of causation. In this paper, we aim to address this gap in the literature by clarifying what is implied by the doctrine of the causal autonomy of special-science properties and by defending the doctrine using a prominent theory of causation from the philosophy of science.

How can collective decisions be made among individuals with conflicting preferences or judgments? Arrow’s impossibility theorem and other social-choice-theoretic results suggest that, for many collective decision problems, there are no attractive democratic solutions. In response, deliberative democrats argue that group deliberation makes collective decisions more tractable. How can deliberation accomplish this? In this paper, I explore the distinction between two different types of agreement and discuss how they can facilitate collective decision making. Deliberative democrats have traditionally defended the hypothesis that group deliberation generates consensus on what decision option should be chosen: "substantive agreement". But substantive agreement is not only empirically unrealistic, but also logically unnecessary for meaningful collective decision making. An alternative, less demanding hypothesis is that, under certain conditions, group deliberation generates consensus on how a decision problem should be conceptualized: "meta-agreement". I assess the latter hypothesis, explain how it can be empirically tested, and cite some evidence consistent with it. My discussion addresses two contexts of democratic decision making: preference aggregation and judgment aggregation.

Can we design a perfect democratic decision procedure? Condorcet famously observed that majority rule, our paradigmatic democratic procedure, has some desirable properties, but sometimes produces inconsistent outcomes. Revisiting Condorcet’s insights in light of recent work on the aggregation of judgments, I show that there is a conflict between three initially plausible requirements of democracy: “robustness to pluralism”, “basic majoritarianism”, and “collective rationality”. For all but the simplest collective decision problems, no decision procedure meets these three requirements at once; at most two can be met together. This “democratic trilemma” raises the question of which requirement to give up. Since different answers correspond to different views about what matters most in a democracy, the trilemma suggests a map of the “logical space” in which different conceptions of democracy are located. It also sharpens our thinking about other impossibility problems of social choice and how to avoid them, by capturing a core structure many of these problems have in common. More broadly, it raises the idea of “cartography of logical space” in relation to contested political concepts.

The concept of preference structuration not only provides possible escape-routes from socialchoice-theoretic impossibility problems, but also points towards ways of formalizing notions of 'pluralism', 'consensus' and 'issue-dimensionality'. The present note introduces two methods of (operationally) measuring preference structuration, giving attention to both their conceptual characteristics and their computational feasibility. The method to be advocated, called the 'fractionalization' approach, combines well-known social-choice-theoretic criteria of preference structuration (such as single-peakedness or value-restriction) with the frequently used Rae-Taylor (1970) and Laakso-Taagepera (1979) approaches towards measuring the level of fractionalization, and the effective number of components, in a system.

The two most influential traditions of contemporary theorizing about democracy, social choice theory and deliberative democracy, are generally thought to be at loggerheads, in that the former demonstrates the impossibility, instability or meaninglessness of the rational collective outcomes sought by the latter. We argue that the two traditions can be reconciled. After expounding the central Arrow and Gibbard-Satterthwaite impossibility results, we reassess their implications, identifying the conditions under which meaningful democratic decision making is possible. We argue that deliberation can promote these conditions, and hence that social choice theory suggests not that democratic decision making is impossible, but rather that democracy must have a deliberative aspect.

Using data from a randomized field experiment within a Deliberative Poll, this paper examines deliberation’s effects on both policy attitudes and the extent to which ordinal rankings of policy options approach single-peakedness (a help in avoiding cyclical majorities). The setting was New Haven, Connecticut, and its surrounding towns; the issues were airport expansion and revenue sharing – the former highly salient, the latter not at all. Half the participants deliberated revenue sharing, then the airport; the other half the reverse. This split-half design helps distinguish the effects of the formal on-site deliberations from those of other aspects of the treatment. As expected, the highly salient airport issue saw only a slight effect, while much less salient revenue-sharing issue saw a much larger one.

Political science is divided between methodological individualists, who seek to explain political phenomena by reference to individuals and their interactions, and holists (or nonreductionists), who consider some higher-level social entities or properties such as states, institutions, or cultures ontologically or causally significant. We propose a reconciliation between these two perspectives, building on related work in philosophy. After laying out a taxonomy of different variants of each view, we observe that (i) although political phenomena result from underlying individual attitudes and behavior, individual-level descriptions do not always capture all explanatorily salient properties, and (ii) nonreductionistic explanations are mandated when social regularities are robust to changes in their individual-level realization. We characterize the dividing line between phenomena requiring nonreductionistic explanation and phenomena permitting individualistic explanation and give examples from the study of ethnic conflicts, social-network theory, and international-relations theory.

Social choice theory is the study of collective decision processes and procedures. It is not a single theory, but a cluster of models and results concerning the aggregation of individual inputs (e.g., votes, preferences, judgments, welfare) into collective outputs (e.g., collective decisions, preferences, judgments, welfare). Central questions are: How can a group of individuals choose a winning outcome (e.g., policy, electoral candidate) from a given set of options? What are the properties of different voting systems? When is a voting system democratic? How can a collective (e.g., electorate, legislature, collegial court, expert panel, or committee) arrive at coherent collective preferences or judgments on some issues, on the basis of its members' individual preferences or judgments? How can we rank different social alternatives in an order of social welfare? Social choice theorists study these questions not just by looking at examples, but by developing general models and proving theorems.

Are companies, churches, and states genuine agents? Or are they just collections of individuals that give a misleading impression of unity? This question is important, since the answer dictates how we should explain the behaviour of these entities and whether we should treat them as responsible and accountable on the model of individual agents. Group Agency offers a new approach to that question and is relevant, therefore, to a range of fields from philosophy to law, politics, and the social sciences. Christian List and Philip Pettit argue that there really are group or corporate agents, over and above the individual agents who compose them, and that a proper approach to the social sciences, law, morality, and politics must take account of this fact. Unlike some earlier defences of group agency, their account is entirely unmysterious in character and, despite not being technically difficult, is grounded in cutting-edge work in social choice theory, economics, and philosophy.

Pettit (2006) argues that deferring to majority testimony is not generally rational: it may lead to inconsistent beliefs. He suggests that “another ... approach will do better”: deferring to supermajority testimony. But this approach may also lead to inconsistencies. In this paper, I describe conditions under which deference to supermajority testimony ensures consistency, and conditions under which it does not. I also introduce the concept of “consistency of degree k”, which is weaker than full consistency by ruling out only “blatant” inconsistencies in an agent’s beliefs while permitting less blatant ones, and show that, while super-majoritarian deference often fails to ensure full consistency, it is a route to consistency in this weaker sense.

Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This article reviews several proposed solutions to this problem. We focus on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). We present axiomatic characterisations of each class of pooling functions (most of them classic, but one new) and argue that linear pooling can be justified procedurally, but not epistemically, while the other two pooling methods can be justified epistemically. The choice between them, in turn, depends on whether the individuals' probability assignments are based on shared information or on private information. We conclude by mentioning a number of other pooling methods.

This paper reassesses the question of whether Craig’s theorem poses a challenge to Quine's empirical underdetermination thesis. It will be demonstrated that Quine’s account of this issue in his paper “Empirically Equivalent Systems of the World” (1975) is flawed and that Quine makes too strong a concession to the Craigian challenge. It will further be pointed out that Craig’s theorem would threaten the empirical underdetermination thesis only if the set of all relevant observation conditionals could be shown to be recursively enumerable — a condition which Quine seems to overlook — and it will be argued that, at least within the framework of Quine’s philosophy, it is doubtful whether this condition is satisfiable.

On the orthodox view in economics, interpersonal comparisons of utility are not empirically meaningful, and "hence" impossible. To reassess this view, this paper draws on the parallels between the problem of interpersonal comparisons of utility and the problem of translation of linguistic meaning, as explored by Quine. I discuss several cases of what the empirical evidence for interpersonal comparisonsof utility might be and show that, even on the strongest of these, interpersonal comparisons are empirically underdetermined and, if we also deny any appropriate truth of the matter, indeterminate. However, the underdetermination can be broken non-arbitrarily (though not purely empirically) if (i) we assign normative significance to certain states of affairs or (ii) we posit a fixed connection between certain empirically observable proxies and utility. I conclude that, even if interpersonal comparisons are not empirically meaningful, they are not in principle impossible.

In a recent paper on ‘The Many as One’, Lewis A. Kornhauser and Lawrence G. Sager look at an issue that we take to be of great importance in political theory. How far should groups in public life try to speak with one voice, and act with one mind? How far should public groups try to display what Ronald Dworkin calls integrity? We do not expect the many on the market to be integrated in this sense. But should we expect integration among the many in the legislature, for example, or among the many on the courts? We agree with Kornhauser and Sager about a number of their claims but think that they miss out on important detail and do not achieve a fully general perspective on the issues raised. Our own contribution is in three sections. We address, first, the nature of the integrity challenge; second, the range of cases in which the challenge arises; and third, the question of whether public groups should be designed and required to meet that challenge.

When animals share decisions with others, they pool personal information, offset individual errors and, thereby, increase decision accuracy. This is termed ‘swarm intelligence.’ But what if those decisions involve conflicts of interest between individual decision-makers? Should animals share decisions with individuals whose goals are different from, and partially in conflict with, their own? A group decision model developed by Larissa Conradt and colleagues finds that, contrary to intuition, conflicting goals often increase both decision accuracy and the individual gains derived from shared decisions. Thus, conflicts of interest, far from hampering effective decision making, can actually improve decision outcomes for all stakeholders, as long as they also have some goals in common. By contrast, conflict-free decisions shared by animals which all have the same goals are often surprisingly poor.

The aim of this article is to introduce the theory of judgment aggregation, a growing interdisciplinary research area. The theory addresses the following question: How can a group of individuals make consistent collective judgments on a given set of propositions on the basis of the group members' individual judgments on them? I begin by explaining the observation that initially sparked the interest in judgment aggregation, the so-called "doctinal" and "discursive paradoxes". I then introduce the basic formal model of judgment aggregation, which allows me to present some illustrative variants of a generic impossibility result. I subsequently turn to the question of how this impossibility result can be avoided, going through several possible escape routes. Finally, I relate the theory of judgment aggregation to other branches of aggregation theory. Rather than offering a comprehensive survey of the theory of judgment aggregation, I hope to introduce the theory in a succinct and pedagogical way, providing an illustrative rather than exhaustive coverage of some of its key ideas and results.

I argue that free will and determinism are compatible, even when we take free will to require the ability to do otherwise and even when we interpret that ability modally, as the possibility of doing otherwise, and not just conditionally or dispositionally. My argument draws on a distinction between physical and agential possibility. Although in a deterministic world only one future sequence of events is physically possible for each state of the world, the more coarsely defined state of an agent and his or her environment can be consistent with more than one such sequence, and thus different actions can be “agentially possible”. The agential perspective is supported by our best theories of human behaviour, and so we should take it at face value when we refer to what an agent can and cannot do. On the picture I defend, free will is not a physical phenomenon, but a higher-level one on a par with other higher-level phenomena such as agency and intentionality.

Free will is widely thought to require (i) the possibility of acting otherwise and (ii) the intentional endorsement of one’s actions (“indeterministic picking is not enough”). According to (i), a necessary condition for free will is agential-level indeterminism: at some points in time, an agent’s prior history admits more than one possible continuation. According to (ii), however, a free action must be intentionally endorsed, and indeterminism may threaten freedom: if several alternative actions could each have been actualized, then none of them is necessitated by the agent’s prior history, and the actual action seems nothing more than the result of indeterministic picking. We argue that this tension is only apparent. We distinguish between actions an agent can possibly do and actions he or she can do with endorsement. One can consistently say that someone who makes a choice has several alternative possibilities, and yet that, far from merely indeterministically picking an action, the agent chooses one he or she endorses. An implication is that although free will can consistently require (i) and (ii), it cannot generally require the possibility of acting otherwise with endorsement.

Distributed cognition refers to processes which are (i) cognitive and (ii) distributed across multiple agents or devices rather than performed by a single agent. Distributed cognition has attracted interest in several fields ranging from sociology and law to computer science and the philosophy of science. In this paper, I discuss distributed cognition from a social-choice-theoretic perspective. Drawing on models of judgment aggregation, I address two questions. First, how can we model a group of individuals as a distributed cognitive system? Second, can a group acting as a distributed cognitive system be ‘rational’ and ‘track the truth’ in the outputs it produces? I argue that a group’s performance as a distributed cognitive system depends on its ‘aggregation procedure’ – its mechanism for aggregating the group members’ inputs into collective outputs – and I investigate the properties of an aggregation procedure that matter.

Many groups make decisions over multiple interconnected propositions. The “doctrinal paradox” or “discursive dilemma” shows that propositionwise majority voting can generate inconsistent collective sets of judgments, even when individual sets of judgments are all consistent. I develop a simple model for determining the probability of the paradox, given various assumptions about the probability distribution of individual sets of judgments, including impartial culture and impartial anonymous culture assumptions. I prove several convergence results, identifying when the probability of the paradox converges to 1, and when it converges to 0, as the number of individuals increases. Drawing on the Condorcet jury theorem and work by Bovens and Rabinowicz , I use the model to assess the “truth-tracking” performance of two decision procedures, the premise- and conclusion-based procedures. I compare the present results with existing results on the probability of Condorcet’s paradox. I suggest that the doctrinal paradox is likely to occur under plausible conditions.

Drawing on the so-called “doctrinal paradox”, List and Pettit (2002) have shown that, given an unrestricted domain condition, there exists no procedure for aggregating individual sets of judgments over multiple interconnected propositions into corresponding collective ones, where the procedure satisfies some minimal conditions similar to the conditions of Arrow’s theorem. I prove that we can avoid the paradox and the associated impossibility result by introducing an appropriate domain restriction: a structure condition, called unidimensional alignment, is shown to open up a possibility result, similar in spirit to Black’s median voter theorem. Specifically, I prove that, given unidimensional alignment, propositionwise majority voting is the unique procedure for aggregating individual sets of judgments into collective ones in accordance with the above mentioned minimal conditions.

This item was published as 'Appendix 3: An Implication of the k-option Condorcet jury mechanism for the probability of cycles' in List and Goodin (2001) http://eprints.lse.ac.uk/705/. Standard results suggest that the probability of cycles should increase as the number of options increases and also as the number of individuals increases. These results are, however, premised on a so-called "impartial culture" assumption: any logically possible preference ordering is assumed to be as likely to be held by an individual as any other. The present chapter shows, in the three-option case, that given suitably systematic, however slight, deviations from an impartial culture situation, the probability of a cycle converges either to zero (more typically) or to one (less typically) as the number of individuals increases.

May's theorem famously shows that, in social decisions between two options, simple majority rule uniquely satisfies four appealing conditions. Although this result is often cited in support of majority rule, it has never been extended beyond decisions based on pairwise comparisons of options. We generalize May's theorem to many-option decisions where voters each cast one vote. Surprisingly, plurality rule uniquely satisfies May's conditions. This suggests a conditional defense of plurality rule: If a society's balloting procedure collects only a single vote from each voter, then plurality rule is the uniquely compelling electoral procedure. To illustrate the conditional nature of this claim, we also identify a richer informational environment in which approval voting, not plurality rule, is supported by a May-style argument

Two essential intuitions about the concept of multidimensional inequality have been highlighted in the emerging body of literature on this subject: first, multidimensional inequality should be a function of the uniform inequality of a multivariate distribution of goods or attributes across people (Kolm, 1977); and, second, it should also be a function of the cross-correlation between distributions of goods or attributes in different dimensions (Atkinson and Bourguignon, 1982; Walzer, 1983). While the first intuition has played a major role in the design of fully-fledged multidimensional inequality indices, the second one has only recently received attention (Tsui, 1999); and, so far, multidimensional generalized entropy measures are the only inequality measures known to respect both intuitions. The present paper proposes a general method of designing a wider range of multidimensional inequality indices that also respect both intuitions, and illustrates this method by defining two classes of such indices: a generalization of the Gini coefficient, and a generalization of Atkinson's onedimensional measure of inequality.