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Notification
« Experimental prudence in political science (Part II) | Main | Unobservable Quantities in Competing Risks »
23 February 2006
Making Votes Honest: Part I
Drew Thomas
First, apologies for my delay in posting to the blog. I've spent most of the last two months involved in the Canadian federal election as a candidate in my home riding. That I lost wasn't unexpected, nor was winning necessarily my goal. I wanted to talk about ideas that weren't being brought up by other candidates. First and foremost on the list was how an election shapes the debate - and why electoral reform is necessary to allow more ideas into the public forum.
While it's clear to me that, first and foremost, Canadians value our right to vote, how that valuation takes place depends directly on what a vote means. As in many party systems, there are two main interpretations for what a vote represents: a belief in the best candidate for the local job, and a belief in the best national party to lead the country. Quite often these two goals do not coincide.
In addition, "tactical" voting, in which a second-choice candidate is chosen merely to block a (much) less desirable candidate, reflects neither of these qualifications.
These problems, among others, anchor my belief that electoral reform is a must for Canada, as well as any multiparty democracy using single member districts and First Past the Post. But band-aid solutions, like the addition of proportionally allocated at-large seats to a FPTP single-member district scheme, would do little to explore the issue. The question before electoral reform revolves not around which of the two focuses - the candidate or the party - is most important to the voters, but rather whether the public can truly express their will through a system that encourages dishonest voting.
So here is my first quantitative question: How does one measure the "strategic effect" on vote counts alone? Survey data is commonly taken, but in comparison to the Ecological Inference problem, drawing this tactical inference from the data themselves would be a huge step towards determining how to reduce it - and what level we could consider acceptable.
Posted by Andrew C. Thomas at February 23, 2006 6:00 AM