Deliberation, Single-Peakedness, and the Possibility of Meaningful Democracy Christian List joint work with: Robert Luskin.

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Presentation transcript:

Deliberation, Single-Peakedness, and the Possibility of Meaningful Democracy Christian List joint work with: Robert Luskin James Fishkin Iain McLean Presentation at the SCW Conference Moscow, July 2010

The challenge  According to an influential view in political science, expressed most prominently in William Riker’s book Liberalism against Populism, Condorcet’s paradox and the impossibility results of social choice theory pose some serious challenges for democracy. ▫Rational individual preferences may lead to irrational majority preferences (collective irrationality). ▫Pairwise majority voting may fail to produce a stable winning outcome (instability). ▫When pairwise majority votes are taken sequentially, the outcome may depend on the order in which votes are taken and may thus be manipulable by agenda setters (path dependence, leading to agenda manipulability).

What can be said in response?  Several authors have recently argued that majority cycles are empirically rare (e.g., List and Goodin 2001, Mackie 2004, Regenwetter et al. 2006), though the literature as a whole has not yet conceded that point.  But even if cycles are empirically rare, we should understand why they are not more frequent, and what helps minimize their frequency.  One much-discussed hypothesis is that group deliberation can provide protection against majority cycles, by suitably structuring individual preferences.  In this paper, we investigate this hypothesis.

Overview  Two hypotheses on group deliberation  Operationalizing the hypothesis that deliberation induces single-peakedness  Empirical evidence  Concluding remarks

Overview  Two hypotheses on group deliberation  Operationalizing the hypothesis that deliberation induces single-peakedness  Empirical evidence  Concluding remarks

Two hypotheses on group deliberation  First hypothesis: Group deliberation induces (substantive) consensus. “Rather than aggregating or filtering preferences, the political system should be set up with a view to changing them by public debate and confrontation. The input to the social choice mechanism would then not be the raw, quite possibly selfish or irrational, preferences …, but informed and other-regarding preferences.... There would [then] not be any need for an aggregation mechanism, since a rational discussion would tend to produce unanimous preferences.” (Elster 1986)  Unrealistic?!

Two hypotheses on group deliberation  Second hypothesis: Group deliberation induces single-peakedness (via a meta- consensus). “If, by reason of discussion, debate, civic education, and political socialization, voters have a common view of the political dimension (as evidenced by single-peakedness), then a transitive outcome is guaranteed.” (Riker 1982; see also Miller 1992; Knight & Johnson 1995; List 2002; Dryzek and List 2003).  Still demanding, but perhaps more realistic?!

Single-peakedness  Recall that a profile of preference orderings across individuals is single-peaked if the alternatives can be aligned from ‘left’ to ‘right’ (in a geometrical sense) such that each individual has a most preferred position on that left-right alignment with decreasing preference as alternatives get increasingly distant from the most preferred position.

Single-peaked preference orderings (with respect to x, y, z, v, w)

A non-single-peaked preference ordering (with respect to x, y, z, v, w)

A possible three-step mechanism of deliberation-induced single-peakedness (1)Group deliberation leads people to identify a common issue dimension in terms of which to conceptualize the decision problem in question. (2)Group deliberation then leads people to agree on how the alternatives are aligned from left to right with respect to that issue dimension; so people determine which geometric alignment of the alternatives best represents the given issue dimension. (3)Group deliberation finally leads each individual to determine a most preferred position (his or her ‘peak’) on that alignment, with decreasing preference as options get increasingly distant from the most preferred position.

Overview  Two hypotheses on group deliberation  Operationalizing the hypothesis that deliberation induces single-peakedness  Empirical evidence  Concluding remarks

Quantifying single-peakedness  How can single-peakedness be quantified, given that it is an on/off notion? (A profile of preference orderings either satisfies or violates single-peakedness.)  For each profile: ▫Define M to be the maximal subset of the set of individuals N = {1, 2, …, n} such that all individuals in M have preference orderings that are single-peaked with respect to the same left-right alignment of the alternatives. ▫Let m be the number of individuals in M. Define the index of proximity to single-peakedness to be m / n. ▫The index ranges between 0 and 1; an index value of 1 corresponds to perfect single-peakedness.

Why is this measure social- choice-theoretically significant?  For any threshold  (with 0 no cycle), conditional on the index of proximity to single-peakedness exceeding  (rather than conditional on an impartial culture).  It can be shown that this probability increases with  (Niemi 1969; some results reported in the present paper; and recent work by William Gehrlein).  In other words, the higher a profile’s proximity to single- peakedness, the lower the probability of a cycle.

Operationalizing the hypothesis that deliberation induces single-peakedness  The hypothesis operationalized: Post-deliberation proximity to single-peakedness is greater than pre-deliberation proximity to single- peakedness.  We are also interested in various refinements of this hypothesis, e.g.: ▫The pre-to-post increase is greatest among those learning the most new information. ▫Deliberation affects single-peakedness less for high-salience issues than for low-salience issues.

Overview  Two hypotheses on group deliberation  Operationalizing the hypothesis that deliberation induces single-peakedness  Empirical evidence  Concluding remarks

Empirical evidence  We use data from deliberative polls (conducted by Fishkin and Luskin) to test our hypotheses.  In a deliberative poll: ▫A controversial political issue is selected. ▫ members of the public are randomly drawn. ▫They are first interviewed on their preferences/opinions (the T1 interview). ▫Then they receive briefing materials and participate in a day or weekend of group deliberation. ▫Finally, they are interviewed again, using the same interview questions as before (the T2 interview).  In some of these experiments, there is also a control group (not in all, unfortunately; very costly …).

Empirical evidence  Our data come from the following deliberative polls: ▫Six DPs on energy provision in Texas (Luskin, Fishkin, Plane 1999). ▫An Australian national DP on the 1999 referendum on making Australia a republic (Luskin, Fishkin, McAllister, Higley, Ryan 2000). ▫A British national DP on the future of the Monarchy. ▫A regional New Haven DP about revenue-sharing and the future of the local airport (Farrar et al., 2010).

Does deliberation increase substantive consensus (reduce fragmentation)? IssueDPnkF1F1 F2F2 F 2 – F 1 Electric Utility Policies SWEPCO CPL WTU Revenue Sharing New Haven Electric Utility Goals SWEPCO CPL WTU Entergy HL&P SPS Airport Expansion New Haven Australian Head of State Australian Const. Ref Changing the British Monarchy British Monarchy Note: n is the sample size; k the number of alternatives; and F 1 and F 2 the index of top-preference fragmentation at T1 and T2.

IssueDPnkS1S1 S2S2 S 2 – S 1 Electric Utility Policies SWEPCO CPL WTU Revenue Sharing New Haven Electric Utility Goals SWEPCO CPL WTU Entergy HL&P SPS Airport Expansion New Haven Australian Head of State Australian Const. Ref Changing the British Monarchy British Monarchy Note: n is the sample size; k the number of alternatives; and S 1 and S 2 the proximity to single-peakedness at T1 and T2. Does deliberation increase proximity to single-peakedness?

Does deliberation increase proximity to single-peakedness, conditional on information learning? “Low I 2 ”“High I 2 ”S 2 – S 1 IssueDPS1S1 S2S2 S1S1 S2S2 “Low I 2 ”“High I 2 ” Electric Utility Policies SWEPCO CPL WTU Revenue SharingNew Haven Electric Utility GoalsSWEPCO CPL WTU Airport ExpansionNew Haven Australian Head of State Australian Const. Ref Changing the British Monarchy British Monarchy Note: “Low I 2 ” S 1 and S 2 are the proximity to single-peakedness at T1 and T2 for the low T2 information subsample, “High I 2 ” S 1 and S 2 the proximity to single-peakedness at T1 and T2 for the high T2 information subsample.

Overview  Two hypotheses on group deliberation  Operationalizing the hypothesis that deliberation induces single-peakedness  Empirical evidence  Concluding remarks

Concluding remarks  We have found no evidence for the hypothesis that deliberation induces consensus, in the sense of reducing fragmentation. This suggests that the original consensus- oriented (“Habermasian”) account of deliberation’s effects was too idealistic.  But we have found evidence for the hypothesis that deliberation increases proximity to single-peakedness. ▫The effect is stronger for low-salience issues than for high- salience issues. ▫The effect is stronger among those individuals who emerge well informed after deliberation than among those who emerge less well informed.

Concluding remarks  This suggests that deliberation – at least in the kinds of settings created by deliberative polls – may indeed provide an escape-route from the challenges for democracy posed by Condorcet’s paradox and Arrow’s theorem.

Thank you!

Quantifying substantive consensus  We can measure the level of fragmentation among different individuals with respect to their top-preferences.  Suppose n 1 individuals most prefer the first alternative, n 2 most prefer the second, …, n k most prefer the k-th.  Then we can compute the Laakso-Taagepera index of fragmentation: 1 LT =  (n 1 /n) 2 + (n 2 /n) 2 + … + (n k /n) 2  LT = 1 means perfect consensus; LT   means extreme fragmentation.

IssueDPnkS1S1 S2S2 S 2 – S 1 Electric Utility Policies SWEPCO (0.032)0.556 (0.033)0.151 (0.046) CPL (0.033)0.519 (0.034)0.130 (0.047) WTU (0.032)0.496 (0.033)0.122 (0.046) Revenue Sharing New Haven (0.043)0.803 (0.035)0.288 (0.056) Electric Utility Goals SWEPCO (0.028)0.362 (0.032)0.125 (0.042) CPL (0.034)0.579 (0.034)0.135 (0.048) WTU (0.028)0.330 (0.031)0.087 (0.042) Entergy (0.036)0.691 (0.035)0.051 (0.050) HL&P (0.036)0.677 (0.034)0.156 (0.049) SPS (0.033)0.649 (0.032)0.090 (0.046) Airport Expansion New Haven (0.036)0.811 (0.034)0.038 (0.050) Australian Head of State Australian Const. Ref (0.020)0.776 (0.023) (0.030) Changing the British Monarchy British Monarchy (0.030)0.647 (0.030) (0.042) Note: n is the sample size; k the number of alternatives; and S 1 and S 2 the proximity to single-peakedness at T1 and T2. The parenthetical entries in the S 1 and S 2 columns are estimated standard errors. Appendix: Results with estimated standard errors