A New Solution to the Collective Action Problem: The Paradox of Voter Turnout
检验了随机学习理论对投票悖论的解释，发现公民遵循“赢则留、输则改”的模式决定是否投票，从而解决了传统模型中投票概率几乎为零的难题。
Macy's work offers a potential solution to the paradox of voter turnout. The stochastic learning theory of voter turnout (Kanazawa 1998) posits that citizens perceive a correlation between their behavior (voting versus abstention) and the outcome of collective action (win versus loss for their candidate), and that they interpret the outcome as a reinforcer or a punisher. The theory can solve the paradox of voter turnout because now p, the probability that one's vote is or appears decisive, equals approximately .500 in the calculus-of-voting model (instead of p ≅ 0). I use General Social Survey data to test the theory. The empirical results indicate that citizens make their turnout decisions according to the “Win-Stay, Lose-Shift” pattern predicted by the stochastic learning theory, especially if there are no strong third-party candidates.