Quantitative Testing of Alternative Models Median Policy Policy-Based Proximate Majority Intuitive Confidence-Weighted Aggregation of Policies The median policy for the experimental triads is always given by w$_{2}$ , the pre-discussion wager of the intermediate member. It is plotted as a function of disagreement level for the complete and chain networks in Figure S3. The zero-parameter χ 2 goodness-of-fit test for the median yields Q = 10 − 10 for χ 2 = 72 . 6. The proximate majority model based on the policies is the same as the RPM model with the rhetorical issue identical to the policy. In other words, Equation 2 in the main text with ρ$_{i}$ = x$_{i}$ where x$_{i}$ is taken to be the wager w$_{i}$ . The results are plotted in Figure S3. The zero-parameter χ 2 goodness-of-fit test for the policy-based proximate majority model yields Q = 7 × 10 − 4 for χ 2 = 33 . 9. This model aggregates policies with weights determined by the intuitive confidence of Simmons and Nelson (2006), which is set by the probability of game victory for whichever team one believes more likely to win. Network structure is not taken into account. The consensus wager w$_{f}$ for the intuitive confidence aggregation model is given by The intuitive confidence weight c$_{i}$ is the difference between the probability of game victory and 1 / 2 (which indicates zero confidence): c$_{i}$ = ρ ( w$_{i}$ ) − 0 . 5 for ρ ( w$_{i}$ ) ≥ 0 . 5 and c$_{i}$ ( w$_{i}$ ) = 1 − ρ ( w$_{i}$ ) − 0 . 5 for ρ ( w$_{i}$ ) < 0 . 5 where ρ ( w ) is the subjective probability of favorite game victory as given by Equation 6. We set σ = 12 . 8 for ρ ( w ) as for S6 w$_{f}$ = c$_{1}$w$_{1}$ + c$_{2}$w$_{2}$ + c$_{3}$w$_{3}$ c$_{1}$ + c$_{2}$ + c$_{3}$ , (S8)