Mentors and Giants: An Interview with Christopher Achen

Christopher Achen is Roger Williams Straus Professor of Social Sciences and Professor of Politics at Princeton University. According to his bio, he “was the first president of the Political Methodology Section of the American Political Science Association, and is a member of the American Academy of Arts and Sciences. He has received fellowships from the Center for Advanced Study in the Behavioral Sciences, the National Science Foundation, and Princeton’s Center for the Study of Democratic Politics. He received the first career achievement award from The Political Methodology Section of The American Political Science Association in 2007. He is also the recipient of an award from the University of Michigan for lifetime achievement in training graduate students. Recent academic placements of graduate students for whom he was the principal dissertation advisor include Stanford, Duke, and the London School of Economics.”

During my first year at Laurier, I was appointed colloquium officer. We had a tiny budget, but I, being fresh out of grad school, was feeling ambitious and was determined to try and bring to Laurier a big name in American political science to spend the day with us. My hope was that this individual would give a public lecture and host a smaller workshop with political science graduate students and faculty members. There was also, at the time, a strong push to help develop LISPOP, and so I thought I would attempt to bring in someone who was a giant in public opinion and/or methodology.

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One of the first names that came immediately to mind was Chris Achen. I remember reading his monograph, Intermediate Regression Analysis (Sage: 1982), at UofT, which, although dated, really helped me get a handle on the logic and math underpinning regression analysis. As well, although I’m sure there were others, at the time I thought he was one of the few “big names” in political science who was rallying against a certain methodological trend of “dumping” as many variables as one could into regression models and magically finding statistical significant relationships. And so I really wanted to meet him!

Happily, Chris accepted my invitation and his public talk and workshop were amazing. As my colleague Loren King mentioned the other day, he was a pioneer in getting to know your data and figuring out how to do matching to establish causality long before matching became a trend in recent days. An added bonus was that Chris was such a nice, humble, and encouraging guy. I made a lot of rookie mistakes during my first year at Laurier, including taking Chris to a bit of a “dumpy” bar instead of a fancy restaurant (darn budget!). But rather than complain, he happily had a beer and burger with the rest of us and told me he preferred the bar to the fancy restaurant (even though I’m sure that’s not true)!

Even though I haven’t spent very much time with Chris in person, I count him both as a giant and a mentor to me. His work and his visit to Laurier had a profound effect on how I have pursued my academic career so far.

Enjoy!

I wish someone had told me at the beginning of my career

How much time faculty spend on committees and administration, and how important it is to learn to manage those obligations while making sure that teaching and research get the time they need.

The individual I admire the most academically

I have a long list of predecessors I greatly admire, but Harold Gosnell, founder of political methodology, is a personal favorite. He did the first field experiments in the 1920s, he used statistical techniques in the 1930s that didn’t come into common use for another 30 years, and he pioneered among students of African-American politics. I had one memorable lunch with him when he was already in his nineties. Alas, he is no longer with us.

My best research project during my career

I always feel that my current one will be the best.

My worst research project during my career

I spent a summer before Bayesian software was invented, laboriously programming and analyzing a Bayesian model of the representativeness of Austrian mayors.

The most amazing or memorable experience when I was doing research

I wrote a paper about rational party identification in 1989 and published it in 1992. The original draft included a footnote saying that if the argument of the paper was correct, the Republicans would become the majority party in the House of Representatives in the not-too-distant future. At that point, the Democrats had controlled the House for nearly all of the last 60 years. The footnote seemed crazy, and I lacked courage. I took it out before publication. Of course, in the 1994 elections, the GOP took over the House, and they have controlled it all but four years since then. The moral: stick to your guns.

The one story I always wanted to tell but never had a chance

One year my APSA paper with Duncan Snidal collapsed completely on August 15, two weeks before the convention. We had to work hard and quickly on a new paper, worrying that the argument was all wrong, and hoping that no one would attend the panel. Instead, it struck a nerve and, after considerable revision, became the lead article in World Politics. We were lucky. But there is a moral here, too: sometimes not worrying about crossing t’s and dotting i’s can free the mind.

A research project I wish I had done

Using political science tools to understand the Weimar elections that led to Hitler. The electoral patterns are quite complex and varied across German subdivisions, as Weimar historiography makes clear. Just mushing the electoral units together statistically at the national level was a very helpful starting point twenty-five or thirty years ago, but it has long been clear that something more locally informed is needed in the twenty first century. A serious command of German and of regional history and politics, a good deal of time in archives, and many years of patient investigation would all be needed, but the result would be a tremendous contribution. I hope someone will do it.

If I wasn’t doing this, I would be

retired from playing middle linebacker for the Oakland Raiders in their glory years. Alas, I am small, slow, and talentless, so I had to go into poli sci.

The biggest challenge in American politics in the next 10 years will be

managing the growing specialization into subfields—political behavior, institutions, American political development, public law, race and politics, public policy, and much else. The important problems and the most interesting intellectual challenges cut across those divisions.

The biggest challenge in political science in the next 10 years will be

making experimentation and other forms of causal inference become as fruitful on the big, longstanding theoretical issues in the study of politics as they have been in political psychology and public policy.

My advice for young researchers at the start of their career is

listen to wise advice, but follow your heart.

Dr. Alcantara Discusses “Flipped” Classrooms in The Globe and Mail

Published Oct. 22, 2013 in The Globe and Mail

“Flipping” classrooms is a new, innovative teaching method that many professors are finding to be effective in their classrooms. Dr. Alcantara, a user of this method, discusses how it has changed the dynamics of his teaching experience and enabled him to engage with students on a new level. Read more about what Dr. Alcantara has to say by clicking here.

Second New Blog Series to be launched!

I will also be (hopefully!) launching a second new interview series, sometime soon, entitled “Mentors and Giants of Canadian Political Science.”.

The initial series of posts will be a couple of interviews I recently did with several senior political scientists who have had a substantial impact on my work or career.

Stay tuned!

Polls and Punditry in the U.S. Presidential Race

If, like me, you have some geek in you, then you will be heartened by a trend in recent coverage of the U.S. presidential campaign, which pits the statistical prowess of folks like Nate Silver, Sam Wang, Drew Linzer, and Richard Gott and Wesley Colley, on the one hand, against an increasingly defensive tribe of established pundits, on the other (joined recently by the Globe and Mail‘s very own Margaret Wente, who doesn’t let ignorance temper confidence, to judge by this bit of fluff).

Enough has been said about this spat to lead sensible folks to side with the geeks, but a late entry from the pundit camp takes a somewhat novel approach. Michael Gerson of the Washington Post offers some of the usual complaints about the statisticians, and about political science in general (“physics envy!” “subjective values!”), but he also opines thus … Continue reading

The main problem with this approach to politics is not that it is pseudo-scientific but that it is trivial. An election is not a mathematical equation; it is a nation making a decision. People are weighing the priorities of their society and the quality of their leaders. Those views, at any given moment, can be roughly measured. But spreadsheets don’t add up to a political community. In a democracy, the convictions of the public ultimately depend on persuasion, which resists quantification.

The irony of a former speech-writer for George W. Bush, once labouring in the shadow of Karl Rove, now channelling Rousseau on the general will, should not be lost on the astute reader. As Bush’s campaign strategist, and then White House insider, Rove did far more damage to America’s democracy than any number-crunching academic ever could. Gerson is a part of that sad legacy.

Still, for political theorists, Gerson is singing in a familiar key. Many of us would readily agree that democracy should be more than a simple aggregation of preferences. As citizens we should, ideally, be persuaded by evidence and argument as we reflect on what is in the public interest, and we should vote in light of those judgements.

So, is Gerson offering his remark as an ideal of democracy? Is he suggesting, perhaps, that the number crunchers are pandering to partisan politics as it is, rather than imagining democracy as it might be?

No, he isn’t.

He surely must know that democracy, as we practice it in North America, is ridiculously far from the ideal picture he paints?

If he does, he offers no hint here, least of all when he offers up the following remarkable conceit:

If political punditry has any value in a democracy, it is in clarifying large policy issues and ethical debates …

… wow.

Tell you what, Mike: when you and your fellow partisan pundits — Republican and Democrat — demonstrate a modicum of scientific and philosophical sophistication, then I’ll happily endorse your vision of pundits as public intellectuals, tackling big issues and ethical quandaries, shaping public opinion with reason and evidence, rather than impressions and sound bites.

Until then? I want you and your fellow pundits to stay well away from innocent citizens!

We’ll know tomorrow (hopefully) whether or not (and which of) the number nerds are correct, but if folks like Gerson don’t like the fact that statisticians can now give a (better than) decent guess at election outcomes based on aggregated polling data, then maybe they should take a long hard look at how the United States — and, of course, the rest of us — implement our democratic ideals.

For his part, Gerson could start by apologizing for his involvement with a U.S. administration that never seemed especially friendly to the ideal of democracy as rooted in civil exchanges among informed citizens, seeking the public good together, across the political aisle.

If he did that, then maybe I’d take his high-minded rhetoric seriously.

Groups or Individuals? Which are More Likely to Make Decisions in a Game Theoretic Way?

I haven’t read the article below yet, but the findings in the abstract remind me of Condorcet’s Jury Theorem, which uses math to show how a group (e.g. a jury) is more likely to reach a correct (and unbiased) decision compared to a single individual (e.g. a judge).

Groups Make Better Self-Interested Decisions

Gary Charness & Matthias Sutter
Journal of Economic Perspectives, Summer 2012, Pages 157–176

Abstract: In this paper, we describe what economists have learned about differences between group and individual decision-making. Continue reading

This literature is still young, and in this paper, we will mostly draw on experimental work (mainly in the laboratory) that has compared individual decision-making to group decision-making, and to individual decision-making in situations with salient group membership. The bottom line emerging from economic research on group decision-making is that groups are more likely to make choices that follow standard game-theoretic predictions, while individuals are more likely to be influenced by biases, cognitive limitations, and social considerations. In this sense, groups are generally less “behavioral” than individuals. An immediate implication of this result is that individual decisions in isolation cannot necessarily be assumed to be good predictors of the decisions made by groups. More broadly, the evidence casts doubts on traditional approaches that model economic behavior as if individuals were making decisions in isolation.