Abstract: Considering information cascades (both upwards and downwards) as a problem of incentives, better incentive design holds some promise. This academic paper suggests a model in which making truth-finding rewards contingent on reaching a certain number of votes prevents down-cascades, and where an informed (self-interested) choice of payout odds and threshold can also prevent up-cascades in the limit of a large population of predictors.
1) cf. avturchin from the question about distribution across fields, pointing out that up-cascades and down-cascades are both relevant concerns, in many contexts.
2) Consider information cascades as related to a problem of incentives -- in the comments of the Johnichols post referenced in the formalization question, multiple commentators point out that the model fails if agents seek to express their marginal opinion, rather than their true (posterior) belief. But incentives to be right do need to be built into a system that you're trying to pump energy into, so the question remains of whether a different incentive structure could do better, while still encouraging truth-finding.
3) Up-Cascaded Wisdom of the Crowd (Cong and Xiao, working paper) considers the information-aggregation problem in terms of incentives, and consider the incentives at play in an all-or-nothing crowdfunding model, like venture capital or Kickstarter (assuming that a 'no' vote is irrevocable like a 'yes' vote is) -- 'yes' voters win if there is a critical mass of other 'yes' voters and the proposition resolves to 'yes'; they lose if there is a critical mass and the proposition resolves to 'no'; they have 0 loss/gain if 'yes' doesn't reach a critical mass; 'no' voters are merely abstaining from voting 'yes'.
Their main result is that if the payment of incentives is conditioned on the proposition gaining a fixed number of 'yes' votes, a population of symmetric, common-prior/private-info agents will avoid down-cascades, as a single 'yes' vote that breaks a down-cascade will not be penalized for being wrong unless some later agent intentionally votes 'yes' to put the vote over the 'yes' threshold. (An agent i with negative private info still should vote no, because if a later agent i' puts the vote over the 'yes' threshold based in part on i's false vote, then i expects to lose on the truth-evaluation, since they've backed 'yes' but believe 'no'.)
A further result from the same paper is that if the actor posing the proposition can set the payout odds and the threshold in response to the common prior and known info-distribution, then a proposition-poser attempting to minimize down-cascades (perhaps because they will cast the first 'yes' vote, and so can only hope to win if the vote resolves to 'yes') will be incentivized to set odds and a threshold that coincidentally minimize the chance of up-cascades. In the large-population limit, the number of cascades under such an incentive design goes to 0.
4) I suspect (but will not here prove) that augmenting Cong and Xiao's all-or-nothing "crowdfunding for 'yes'" design with a parallel "crowdfunding for 'no'" design -- i.e., 'no' voters win (resp. lose) iff there is a critical mass of 'no' voters and the proposition resolves 'no' (resp. 'yes') -- can further strengthen the defenses against up-cascades (by making it possible to cast a more informed 'no' vote conditioned on a later, more-informed agent deciding to put 'no' over the threshold).