Tag Archives: John Mearsheimer

Controversies in Normal Science

tl:td: “Normal Science” refers to science when scientists focus on making progress, not just arguing in circles. The difference between probabilistic and bayesian — or “go-up” and “go-next” — statistics matters much more to the future of normal science and the nonsense that Walt and Meirsheimer came up with in a recent article.

Will F. Moore, at his blog A Second Mouse has a really funny up titled “Commentary on Mearsheimer and Walt.” Not surprisingly, it is a commentary on Mearsheimer’s and Walt’s (d’uh! :-) ) recent post, which I also criticized. Basically, Mearsheimer and Walt wrote a piece in which they demonstrated deep confusion of scientific methods, and lamented the decline of the “old boys network” and its replacement by objective methods of evaluation.

One of the ridiculous parts of Mearsheimer and Walt’s columns is their inability to distinguish substantive from non-substantive divisions in normal science. For instance, a large part of Mearsheimer and Walt’s piece is dedicated to a discussion of “scientific realism,” which appears to be a confused discussion of instrumental validity. Mearsheimer and Walt completely miss the division of scientific research into frequestist and bayesian camps, which Will Moore humorously emphasizes:

Quantitative approaches—particularly the misapplication of hypothesis testing methods which make complete sense in the context of survey research but no sense whatsoever in the context of the analysis of one-off populations—may be wrong, but at least we can systematically say why they are wrong.[4] Grand theory?—welcome to the narrative fallacy and that wonderful little hit of dopamine that your brain gives you in response to any coherent story. And that’s all they’ve got to work with.

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[4] And again, we know of plenty of alternatives, including the rapid emergence of Bayesian model averaging which is likely to wipe out the cult of incremental frequentist garbage can models. The cult otherwise known by the initials APSR and AJPS.

Previously on this blog, I’ve referred to “frequentist” and “bayesian” statistics as “go-up” and “go-next,” because frequentist work tends to emphasize building a model of reality, while bayesian models tend to focus on predicting what will happen next. As I wrote previously:

The Go-Up view of statistics is that statistics measures the population from which an observation comes from. The appropriate way to go-up is to wait until you have a sufficient number of observations. and then generalize about the population from our observations. So if you are conducting science, and you notice. This is the method that Derbyshire was describing in 2010. A large number of observations of academic performance show consistent gaps between black and white learners. Because we’re “going-up” from observations to populations, we can conclude some things about the population, and how outcomes in the population should work-out over all, but it makes no sense to try to predict any given student’s success based on this. We’re going-up, not going-next.

The Go-Next view of statistics is that statistics gives us the likelihood of something being true, based on what has come before. In Go-Next statistics, population-averages are besides the point. What matters is guessing what’s going to happen, next, based on what you’ve seen before. The whole point is to guess what’s going to work for individuals you know only a few things about, based on your experience with other individuals who shared some things with the new strangers.

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The superstructure of science changes as the infrastructure of the economy changes. The Go-Next philosophy of statistics, once the peasant stepchild of the serene Go-Up interpretation, now reigns supreme.

The unfolding victory of Go-Next Statistics matters much, much more than, say, the Copernican Revolution. The number of people whose daily conversations were actually impacted by Copernicus may have been a few dozen, all involved in the Papal-Academic complex.

How many times a day does Facebook’s decision of which news to share impact you?

There are real controversies and real research programs in normal science.

Too bad Walt and Mearsheimer know so little about normal science they were unable to identify either.

Science, Paradigms, and the Old Boy Network

On Facebook, Daniel Nexon pointed me to this post by Steve Saideman, titled “Lamenting The Loss of the Light, The Ebbing of Grand Theory and The Decline of Old Boy Networks.” Saideman’s post itself is a commentary on Stephen Walt‘s and John Mearsheimer‘s ridiculous article, “Leaving Theory Behind: Why Hypothesis Testing Has Become Bad for IR,” which will soon appear in the European Journal of International Relations.

Walt and Mearsheimer’s article is absurd on many levels. But I mention it for how well it reflects my post, “Progress, Science, and Exemplars — or — When It Sucks to Be Young.”

In that post, I mention that it is horrible for your career to be young in a science with loose exemplars — that is, in a field that is “non-paradigmatic” or a “revolutionary science.” The more revolutionary the science, the looser the exemplars, the more “knowledge” and “experience” are both measured in years. The less things change — the less progress is made — the less youth matters relative to years of experience.

Or in diagrammatic form:

ways_of_knowing_3

What’s bizarre is that Walt and Mearsheimer agree with me! But this makes them sad. Walt and Mearsheimer would rather political science stay as anti-youth and revolutionary as possible, so that their power and influence could remain strong:

Over time, professions also tend to adopt simple and seemingly objective ways to evaluate members. Instead of relying on “old boy” networks, a professionalized field will use indicators of merit that appear to be impersonal and universal. In the academy, this tendency leads to the use of “objective” criteria—such as citation counts—when making hiring and promotion decisions. In extreme cases, department members and university administrators do not have to read a scholar’s work and form an independent opinion of its quality; they can simply calculate the “h-index” (Hirsch 2005) and make personnel decisions on that basis.22

The second part of the paragraph is literally incoherent, attacking the use of an h-index by arguing it’s a raw count of citation. Walt and Meirsheimer seem unable to do math, and so their inability to understand even basic fractions should not surprise you. What should be surprising is they are so openly defending the power aristocracy that comes from using subjective scores and the “old boys” network!

In fairness to Walt and Meirsheimer, the intellectual poverty they confess through their incoherent ramblings is not entirely their fault. Political science has been so revolutionary, so paradigmatic, so subjective for so long that few may know what a science actually is, or even understand the terms used to describe science.

Consider this earlier passage in Walt and Meirsheimer’s article, in which the “worse than wrong” passage is intended to be uncontroversial:

Indeed, some senior IR scholars now rail against the field’s grand theories. In his 2010 ISA presidential address, for example, David Lake described the “isms” as “sects” and “pathologies” that divert attention away from “studying things that matter” (Lake 2011: 471). Thus, it is not surprising that “the percentage of non- paradigmatic research has steadily increased from 30% in 1980 to 50% in 2006” (Maliniak et al 2011: 439). Of course, one could advocate for middle range theories while disparaging grand theories, and indeed Lake does just that. The field is not moving in that direction, however. Nor is it paying more attention to formal or mathematically oriented theories (Bennett et al 2003: 373-74). Instead, it is paying less attention to theories of all kinds and moving toward simplistic hypothesis testing.

The highlighted passage, originally by Daniel Maliniak simply means that empirical research is increasing, and that non-empirical research is declining, within political science. But Maliniak, and thus Walt and Mearsheimer, bizarrely use “paradigmatic” to refer to less paradigmatic (that is, less capable of progress) fields, and “non-paradigmatic” to more to more paradigmatic (that is, more capable of progress) fields.

ways_of_knowing_2

Political science has been in the fever swamp for so long that the notion of progress as an outcome of normal science has almost entirely been lost. If Walt and Mearsheimer had their way, it might be lost, and the field simply divided into a stationary oligarchy of old boys network.

At one point in their article, Walt and Meirsheimer say that “the creation and refinement of theory is the most important activity in [social science].” This is nonsense. The most important activity in science is the prediction, control, and improvement of behavior. Theory can help, diagram can help, interviews can help, process tracing can help. But the paen to old boys network, and the nonsense that Walt and Mearsheimer try to pass off as a scholarly article, certainly doesn’t.