Collective Action and Voter Turnout
While recently learning about collective action, the connection drawn to political protest under a repressive regime was especially interesting to me because of how it highlighted the consequential nature of network structure. When it comes to political action, it is not surprising that social networks are extremely decisive in who participates in politics, whether that be through something as extreme as an uprising, or something as commonplace as voting in an election. From my understanding of collective action, I think that its corresponding network model can apply broadly to voter turnout, and contribute to our understanding of why voter participation varies considerably across different communities.
Consider a swing state versus a safe state (one that consistently votes Republican or Democratic). Citizens of a swing state are aware that they live in a state where there are similar levels of support for each political party, thus, they are more likely to participate in the collective action of voting because they know their vote could play a role in pushing their state to either red or blue. On the other hand, those in a safe state like New York know that they are one of many citizens who will simply not affect their state’s outcome due to the political party that historically dominates the state. Thus, they may be less likely to go to the polls, because they feel that their vote will not count. An article published by the Niskanen Center emphasized how voting becomes complicated when it comes to collective action: “the likelihood of casting the decisive vote in a U.S. presidential election is 1 in 60 million. And yet when voters act collectively, thousands of individually meaningless votes can quickly add up and become a force to be reckoned with” (Hammond). The decision of whether or not to cast a vote is not always an easy one, even if it should be—however, evidence shows that indeed, voter participation in swing states is significantly higher than in the rest of the country (National Popular Vote).
This phenomenon is comparable to the political protest scenario explained in our textbook, but somewhat inversely. In the textbook example, each participant has an individual threshold that measures her willingness to participate in some type of collective action, dependent on her neighbors. The more knowledge and confidence they have in their neighbors participating (thus reaching their threshold), the more likely that individual is to participate. In the voting scenario, it is when a voter has less confidence in the political alignment of their neighbors (i.e. fellow citizens) that they will be more likely to cast their vote. Thus, to calculate the likelihood of someone voting, a mathematical model might take an adapted form of the one from class: a threshold of k would not mean “I will join the action if I am sure that at least k people in total will show up,” rather, it would mean “I will join the action if I am sure that at least k people in total will vote against my party.”
While working out the actual math for this would surely be easier said than done, this model would theoretically allow us to take the voter history of a state (whether it is a swing state or a safe state) and, accounting for other factors, predict a voter’s likelihood to participate in an election based on their understanding of their state’s political leaning.