Science is Real. Measurement is Real. Improvement Is Real

Bill Gates, the co-founder of the company I work for and a personal hero of mine, has an op-ed in the Wall Street Journal titled “My plan to fight the world’s biggest problems.” It’s an exciting piece because it ties together several of my recent posts very well.

Science allows us to predict, control, and improve variation in the world. In order to actually make progress to these goals, it’s important to establish exemplars of great work. This is enabled through operational definitions that allow concepts to be measured. The quest for progress in science collapses when measurement becomes too difficult tor too expensive.

But the reverse is also true: progress in science begins when measurement becomes accessible.

Bill Gates’ op-ed is so awesome because he brings us back to the real world. When someone says “science,” others thinks of some cartoon view of men in white coats in a laboratory. When someone says that goal of science is the prediction, improvement, and control of variation, someone else will say that such is a “very narrow definition of science, downgrading as it does understanding and explanation.”

But the person who writes you write like Bill Gates does — who never even bother with the word “science” and hammers in that improvements are real:

Such measuring tools, Mr. Rosen writes, allowed inventors to see if their incremental design changes led to the improvements—such as higher power and less coal consumption—needed to build better engines. There’s a larger lesson here: Without feedback from precise measurement, Mr. Rosen writes, invention is “doomed to be rare and erratic.” With it, invention becomes “commonplace.”

In the past year, I have been struck by how important measurement is to improving the human condition. You can achieve incredible progress if you set a clear goal and find a measure that will drive progress toward that goal—in a feedback loop similar to the one Mr. Rosen describes.

This may seem basic, but it is amazing how often it is not done and how hard it is to get right. Historically, foreign aid has been measured in terms of the total amount of money invested—and during the Cold War, by whether a country stayed on our side—but not by how well it performed in actually helping people. Closer to home, despite innovation in measuring teacher performance world-wide, more than 90% of educators in the U.S. still get zero feedback on how to improve.

An innovation—whether it’s a new vaccine or an improved seed—can’t have an impact unless it reaches the people who will benefit from it. We need innovations in measurement to find new, effective ways to deliver those tools and services to the clinics, family farms and classrooms that need them.

… that’s the sort of person who can make a difference. The theory of science, measurement, and improvement are all left below the surface. What is left is a how-to guide to build a better world.

I write this blog for selfish reasons, I enjoy learning about the world. Bill Gates does what he’s doing to change the world.

The Search for Academic Utility

Over the past few weeks I talked a lot about “paradigms.” Paradigms are “research programs” that focus on a few exemplars of high quality work. This allows science to make progress, and breaks up “old boy” networks by privileging results over connections. The need for progress also allows students to have better lives after they graduate. Professors, like all people, crave money, power and respect.

Thus, normal science, paradigms, research programs, and exemplars align our the need for progress, student’s need for good lives, and professor’s need for professional accomplishment. This is how academia works. Science is not a cartoon. It is a great human achievement that gets human beings to predict, control, and improve variation of the objects scientists study.

Normal Science is good because it is useful, not because it is True.

Consider three areas of work: race-based explanations for school performance, my UFO theory, and the ancient astronaut theory of Great Pyramid construction. If I had to bet, I would bet a great deal of money there’s a very strong impact of race in academic performance not explainable by income, I would bet a small amount of money the aliens at Roswell were from Japan, and I would bet against someone claiming that the logistics of Great Pyramid construction was designed by creatures from beyond the Moon.

ancient_ufo

But attempting to found an academic career on either of these theories would lead to a failure to gain tenure. The reason is all are currently outside of the normal science in educational psychology, digital humanities, and Egyptology. None of these theories are currently useful in the field, so none are pursued.

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Normal Science is just part of Science, which along with Inquiry are two of the ways of knowing about the world. There’s more to this world than captured in data sets. My friend Mark Safranski recent captured readers after linking to a data set, stating “ there are hidden qualitative decisions in who did the counting, how and by what yardstick.” Indeed, Normal Science has even more limitations than that.

A lot of grief is caused by considering Science the search for Truth. It may that, but Normal Science is the search for utility in an academic context.

A Lucid Visit

Yesterday I had a lucid dream of visiting my grandparents.

That is, I had a dream of it, but I was aware that I was dreaming, so I could make the most of my time.

Lucid dreaming requires being in the hypnagogic state, where you possess consciousness without wakefulness. You can enter a hypnagogic state from wakefulness, or from dreamland. The problem in either case is maintaining consciousness, as it’s easy to lose in dreamland.

Yesterday, I entered the hypnagogic state by counting to myself while falling asleep. I first began counting sheep, but that was too cartoony, so then I imagined trying to count sheep in a pen, then cattle in a field, and that became cattle in my grandfather’s field. Soon I was counting the steps to his house. Then I was in a hypnagogic state.

I did not want to lose consciousness, so I then looked down while moving. In software terms, the human mind has a “known bug” in the graphics driver while sleeping: if you look down while you’re walking in a dream, you’re feet either will be invisible or else will look very, very strange. This is so noticeable that even in dreamland, it alerts your consciousness. So you can stay lucid dreaming even in dreamland by looking at your feet while walking.

In a lucid dream you can control your environment (instead of a normal dream, which is like watching a movie). You can also warp your environment if you want to, though this requires a noticeable act of will. Yesterday, I just controlled what I did and where I went, but I let dreamland unfold as it wanted to.

I visited the garage, saw the things inside vividly and individually. “There are things here I never asked about,” I thought. Outside the garage, saw the sod house flicker into and out of existence.

I entered the farmhouse through the front door. I saw the little entryway, and all the sounds inside, WNAX on the radio, my grandfather sitting down by the table, my grandma standing, my dad was there too. I heard them all. I felt the shadows of the living, but I only heard my grandpa, my grandma, and my dad.

The sounds and the textures were hyper-real, though visually everything was like a ‘progressive render,’ where it became noticeably clearer as I focused. I saw the little TV on the refrigerator. I walked from the kitchen to the dining room. I saw the old phone, the desk with the recorder that my idiot uncle gave my grandparents, the plants, and the cabinet with the radio. (I knew there was an Atari in there somewhere, though I did not look for it.)

I passed through the glass portico into the living room. I felt the tape on the large comfortable chairs. I felt the shadows of the living again. I saw the couch, the painting above the couch, and the chairs on each side. The old television (that I caused havoc with when I was young). The long table with the storage area underneath, I once hid in. The bull.

I saw the loveseat, the window, and walked to the back entry way. I was hopefully because there was a building set I loved, that belonged to my uncle when he was young, and I wanted to see the brand name, but I could not make it out. I could see the pieces vividly, see the army men and the home-made Parcheesi set set, but I could not make out the brand name.

Disappointed, I walked in the remaining rooms of the house. Each was vivid. The downstairs bathroom, my grandfathers room (in which I had a nightmarish flash back to reality, back after my grandfather died, going thru his things with my mom, then back to dreamland). Then the hall again, then up the stairs. I felt the texture, again hyperreal. I saw the old fire alarm / extinguisher / whatever it was — the least safe home-safety device ever created, seemingly constructed to explode glass outward during a fire. “I knew that would kill us all one day,” I thought.

Then I woke.

The Progress of the Humanities

Over on Facebook, my friend Adam Elkus linked me to an article by David Lake, titled “Theory is Dead, Long Live Theory: The End of the Great Debates and the Rise of Eclecticism in International Relations. [pdf]” The piece is extremely strong, and describes International Relations split into two camps: one engaged in normal science capable of progress, and the other a tiresome collection of “Great Debates” that are never answered.

There’s a lot to love in Lake’s paper — it really is very high quality — but the most evocative image from it is the threat that International Relations will split into two fields that do not even study the same phenomenon. What if the scientists focus on experiments (and quasi-experiments) that can be conducted in the here and now, while the Great Debaters retreat into history and just-so stories?

To me, the best hope to save International Relations from such a fate lies in the “digital humanities.” The digital humanities are not just a method for those interested in the past to escape the “humanities ghetto of low employment and low wages
— rather, the “Digital Humanities” use Big Data techniques to understand our common past, in the same way that companies like Facebook use many of the same techniques to understand many private pasts. (Some more information on the digital humanities is available on the personal site of Jason Heppler of Stanford University.)

As an example, take Lake’s discussion of Zara Steiner‘s Triumph of the Dark, a narrative history of the outbreak of the Second World War. Lake notes the rigor of the book, but sadly states such a work can generate no hypotheses or tests. But a digital humanities approach — say working from the massive newspaper, magazine, book, and census corpora at our disposal, is not so limited. It is easy to imagine hypotheses that explain the reason for the motives of leaders with that amount of data to work with. Perhaps the degree to which “Hitler wanted war” can be tracked by measuring the day-to-day bellicosity of the written works of those he met with? Or might the locations that we knew Neville Chamberlain spent certain parts of his life be linked to pro-peace inflections in the lives of others?

International Relations is the science dedicated to predicting, controlling, and improving the behavior of States. This should be done through hypotheses testing, modeling building, and including the methods of the digital humanities. There are many ways to advance science.

In the chaos of old boy networks – in stagnant fields with no progress – it sucks to be young. But in all those areas where science and technology march hand-in-hand toward progress, it is a joy to be young!

Money, Power, and Normal Science

Fabio Rojas has a post up titled Theory Death in Political Science. It links to a post by Stephen Saideman, “Leaving Grand Theorists Behind,” which was published as Saideman’s Semi-Spew. (A companion piece was also published at Duck of Minerva and discussed by me earlier.)

Here’s the beginning of the post:

A definition: theory death is when some intellectual group tires of theory based on armchair speculation. Of course, that doesn’t mean that people stop producing theory. Rather, it means that “theory” no longer means endless books based on the author’s insights. Instead, people produce theory that responds to, or integrates, or otherwise incorporates a wealth of normal science research. In sociology, theory death seems to have happened sometime in the 1980s or 1990s. For example, recent theory books like Levi-Martin’s Social Structures or McAdam and Fligstein’s A Theory of Fields are extended discussions of empirical research that culminate in broader statements. The days of endlessly quoting and reinterpreting Weber are over. 🙁

Now, it seems, theory death is hitting some areas of political science.

What Fabio Rojas calls “theory death” is the “normalization of science.” That is, the establishment of methods that allow for progress in the prediction, control, and improvement of behavior of some object of study (molecule, person, State, etc.) over time.

The next line is particularly important:

Science becomes normalized when the power the Old Boys network achieves through limiting competition is overtaken by the money available for creating progress.

There have been two great flowerings of science in American history. Both emerged from the establishment of the great American University System in the late 19th century, but they accelerated at different times. As I wrote previously:

Following the Second World War science boom, the federal government accelerated the rise of the American research universities. From the Second World War to the Vietnam War, physics was a favorite area for funding. From this we received many new physical inventions, such as a transistor. After the Vietnam War, medicine is a favorite area for funding. Now we have great medical breakthroughs.

While social science research funding is only a fraction of medical research, the federal academic complex ensures that there is bleed through from health sciences to the social sciences as well. The bureaucratic momentum for peer-reviewed scientific research funding. Such funding requires that researchers seek to achieve progress in some areas, which of course privileges normal science (which is capable of achieving progress) relative to non-paradigmatic science (Which is not).

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The reason that Political Science is late to normalization — why it is experiencing “theory death” later than other fields — come from the obvious exception to this general rule for how academia works:

Professors, like most people, respond to the incentives of power, influence, and money.

The institution of tenure reduces uncertainty regarding money, and focuses the incentives on power and influence.

Power in academia comes from the number of bodies a professor has under him. These bodies might be apprentices (graduate students he advises), journeymen (post-docs who have a PhD and work at the lab, or staff researchers), or simple workers (lab technicians, etc).

Influence in academia comes from the extent to which one is successful in influencing one’s peers. This is typically measured in terms of influence scores, which are a product of how often the academic is cited, weighted by how important of a publication he is cited in.

Unlike other places in academia, professors hope to influence national policy makers, and so are relatively immune to academic discipline. This actually hurts scholarship. For instance, Victor Cha’s otherwise great book on North Korea, The Impossible State, is pretty much ruined by his analysis of Kim Jung Il, which was basically a job application. Likewise, Stephen Walt and John Mearsheimer (who began this discussion by defending the Old Boys network) basically produce political propaganda for the Old Right (pessimistic, Army-focused, and anti-Zionist). The lack of academic discipline has allowed political science to get away with graduating students into the “humanities ghetto” — because skills don’t matter in political science as much as connections, those without connections are left with high unemployment and bitter job prospects:

wages_employment_majors_humanities_ghetto_md

The way forward is probably for grant-funding organizations to support normal science in political science research, and for political agitators to coalesce within agenda-driven “think tanks.” Educational sciences have already experienced this split. It’s time for Political Science to normalize, too.

Definitions and Progress

A couple days ago a post on Duck of Minerva linked to a working paper called “I can has IR theory?” [pdf]. The title was funny, but something about the contents bothered me.

I Can Has IR Theory Appears to have tow components
1. It is an extended hit peace against “neopositivism,” which appears to be a methodology (or something) disliked by the authors. It is difficult to know if this is true, however, because the authors do not bother to define their terms.
1. It includes a discussion of “scientific ontology,” which likewise is never defined.

Unlike “neopositivism” though (the only thing I can tell about which is that the authors — Patrick Jackson and Daniel Nexon — dislike it, and that it appears to be related to quantitative methods), the article includes numerous descriptions of “scientific ontology.” It is these descriptions that bothered me.

“Scientific ontology” appears to be synonymous for “nomological network,” an antiquated and simplistic form of modeling that is prone to error.

First, some passages from Jackson and Nexon’s working paper:

To be more precise, we think that international-relations theory is centrally involved with scientific ontology, which is to say, a catalog—or map—of the basic substances and processes that constitute world politics. International-relations theory as “scientific ontology” concerns:
• The actors that populate world politics, such as states, international organizations, individuals, and multinational corporations;
• Their relative significance to understanding and explaining international outcome
• How they fit together, such as parts of systems, autonomous entities, occupying locations in one or more social fields, nodes in a network, and so forth;
• What processes constitute the primary locus of scholarly analysis, e.g., decisions, actions, behaviors, relations, and practices; and
• The inter-relationship among elements of those processes, such as preferences, interests, identities, social ties, and so on.

(Note how they are measured is left out.)

And this passage (as mentioned above, “Neopositivism” is never defined and only loosely described, so focus on the passage related to “scientific ontology”)

The Dominance of Neopositivism
This line of argument suggests that neopositivist hegemony, particularly in prestige US journals, undermines international-relations theorization via a number of distinct mechanisms:
• It reduces the likelihood that international-relations theory pieces will be published in “leading” journals because neopositivism devalues debate over scientific ontology in favor of moving immediately to middle-range theoretic implications; • It reduces the quality of international-relations theorization by requiring it to be conjoined to middle-range theorizing and empirical adjudication; and
• It forces derivative middle-range theories to be evaluated through neopositivist standards.

(Note that scientific ontology thus excludes “middle-range theoretical implications.)

In an earlier work, I wrote that :

As a measure of construct validity, nomothetic span is more inclusive than Cronbach and Meehl’s (1955) concept of the nomological network, as nomothetic span includes not only how a construct relates to other construct, but also how measures of the same construct relate to each other (Messick, 1989).

Because the undefined concept of “scientific ontology” appears to be more or less identical to the idea of nomological network, which was described a half century ago. Without incorporating measurement into a model, it’s impossible to a functional definition, a method of falsifying the model, or even a way to make useful predictions. And without this ability, it’s impossible to make progress.

Operational definitions are absent from Jackson’s and Nexon’s piece, both from their primary terms, and their view of “scientific ontology.”

Escaping the Humanities Ghetto: Definitions and Paradigms

In both Political Science and the Humanities, the old boys network which prevented progress is collapsing, though it is hard for those who have lived in a field without progress to describe this.

ways_of_knowing_2

Earlier I criticized, Stephen Walt and John Mearsheimer for saying that International Relations work capable of progress is “non-paradigmatic”

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.

But if I am fair, I need to also mention that my friend Jason Heppler of Stanford University made a similar claim, about the Digital Humanities:

Those doing digital humanities tend to agonize over how we define the field (or is it a methodology?). Matt Gold’s edited volume Debates in Digital Humanities nicely sums up many of the ways people have tried to define digital humanities and what we mean when we say we do digital humanities. Certainly there are some common characteristics within the broad range of approaches, but the work itself is broad: it’s interpretation, coding, building, archives, theorizing.

Why define digital humanities? The enterprise is somewhat pointless. The promise and excitement of digital humanities lies with what we can do with it, not how it’s defined. But the queston is inescapable.

I don’t believe that the new International Relations work is apardigmatic, or that Digital Humanities is undefined. Rather, like other useful areas, these fields are defined by their tools and methods, not by ancient theoretical battles that can never be won. Chemistry is not the science of phlogiston, it is the science of titration and fission. Likewise, International Relations and Digital Humanities are increasingly defined by the tools they use to make progress, not connections in an old boys network.

This is a good change. Yesterday I mentioned the ghetto of the humanities, those fields whose graduates (a) can’t do math, (b) can’t conduct useful research, (c) can’t stay employed, and (d) can’t get paid.

wages_employment_majors_humanities_ghetto_md

The adoption of useful tools and progressive science is the best way to turn this around. The emerging paradigms of International Relation are embedded within statistics and modeling. The emerging definitions of Digital Humanities are embedded within text mining, semantic networks, and big data. What do these have in common? Useful tools designed to provide answers and enable progress.

The Language of Theory, or, How to Escape the Humanities Ghetto

This morning I read an article by Patrick Thaddeus Jackson and Daniel Nexon, titled “Paradigmatic Faults in International-Relations Theory.” This piece originally appeared in a 2009 edition of Internaionl Studies Quartlerly.

I like when people agree with me, so when I saw my words echoed across time (it’s as if Jackson and Nexon read my post, built a time machine, and told their former selves what a great idea they read on tdaxp). Yesterday, I said it was riduclous to describe the International Relations cliques of “Realism,” “Liberalism,” and such as paradigms. I wrote:

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.

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.

As Jackson and Nexon write:

The terminology of ‘‘paradigms’’ and ‘‘research programmes’’ produces a num-ber of deleterious effects in the field. It implies that we need to appeal to criteria of the kind found in MSRP in order to adjudicate disputes that require no such procedures. In order to do so, we spend a great deal of time specifying the ‘‘boundaries’’ of putative research programmes and, in effect, unfairly and misleadingly holding scholars accountable for the status of theories they often view as rivals to their own.

Perhaps the most well-known instance of this kind of boundary-demarcation occurs in the debates surrounding ‘‘realism’’ in international relations theory. The proliferation of countless lists of the ‘‘core commitments’’ of a realist ‘‘paradigm’’—by adherents and critics alike—shifts the focus of scholarship away from any actual investigation of whether these commitments give us meaningful leverage on the phenomenal world, and instead promotes endless border skirmishes about who is and is not a realist (Legro and Moravcsik 1999), whether predictions of balancing are central to the ‘‘realist paradigm’’ (Vasquez 1998:261–65), and so forth. Such debates and demarcations not only distract us from the actual study of world politics, but also harm disputes over international relations theory by solidifying stances that ought to remain open to debate and discussion.

So I enjoyed Jackson’s and Nexon’s takedown of the so-called “paradigms” in International Relations.

But they don’t go far enough.

Their piece ends with an appeal to Max Weber (how non-progressive can you get?!?) and an unfalsifiable taxonomy that I won’t go into

ideal_typical_taxonomy

A more useful conclusion to the paper would have been to recognize that statistics is the language of theory, the language of modeling. Instead of inviting international relations scholars to chase their own tale and bow to Max Weber and the dead, how much more useful would a positive theory of research programs in International Relations have been? For instance, consider a citation indexing method, such as PageRank [pdf] to determine if they are “clusters” PageRank sets in which certain articles were influential (exemplars?) and others were not. Did Jackson and Nexon really have no one availability to sketch even a proposed methodology for testing their claim?

The answer is probably “no.” My purpose isn’t to pick on Jackson and Nexon, but to point out the weakness of International Relations as a whole. In a related post by Patrick Musgrave, titled “The Crass Argument for Teaching More Math In Poli Sci Courses“, the following diagram showing is shown:

wages_employment_majors_md

Which clearly displays a “humanities ghetto,” that includes political science.

wages_employment_majors_humanities_ghetto_md

How can this be, if International Relations is the disciplined extraction of meaning from data, which is the same focus as the high-paying, well-employed fields?

The obvious answer is that International Relations does not teach actually useful methods for the disciplined extraction of data. It does not teach critical thinking or logical reasoning. It teaches something that apes these skills, a rhetorical ability that impresses old scholars and does not help society.

International Relations is a non-progressive field where, by and large, it sucks to be young.

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In an evocative comment that ties the article and the blog post together, Patrick Thaddeus Jackson states:

I don’t think that it is our job as university faculty to increase students’ future earning potential. Nor do I think that it is our job in teaching PoliSci undergrads to make sure that they can read APSR in the 1980s and 1990s. Our job is to teach students to think critically about politics, and while I am perfectly fine with the suggestion that some statistical literacy can be useful to that end, I am not prepared to give that higher pride of place than things like reading closely, writing cogently, and disagreeing with one another civilly.

The dichotomy that Jackson notes is entirely false. In his own piece, he was not able to express a constructive critical thought about paradigms — the original Nexon and Jackson article is devoid of the model specification or operationalization that would needed to turn his criticisms and taxonomy into something capable of progress. Any competent graduate from the humanities ghetto can read “closely” or write “cogently.” That’s needed is to think usefully, and for this statistical literary is required.

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.

Progress, Science, and Exemplars — or — when it sucks to be young

Some people divide the ways we know about our world into two types, Science and Inquiry. Science typically refers to using falsifiable hypotheses to make predictions about the world. Inquiry refers to any deviation or alteration of this method.

ways_of_knowing_0

For the rest of this post I’m going to talk about fields in which the objective is to control, predict, and improve the behavior of some object (cancer cell, human being, State, whatever). That is the purpose for which the tool of science is most applicable.

Some people further divide Science into two types: Normal Science and Revolutionary Science. These terms from from Kuhn’s book, The Structure of Scientific Revolutions. Normal Science, in Thomas Kuhn’s original model, was capable of progress but governed by religious-like “paradigms.” Revolutionary Science, likewise in Kuhn’s outdated model, was capable of freedom but incapable of progress.

ways_of_knowing_1

I say “original” and “outdated” because no one — except for pretentious modern literature types, and including Kuhn himself — takes that model seriously anymore. While The Structure of Scientific Revolutions was a breakthrough at the time (because it implied that science was not completely free, and that not all science would yield progress), the feedback to the model was intense and Kuhn’s model of science rapidly improved.

Instead of two distinct types of Science, Kuhn’s revised models described any scientific field as having “exemplars,” or examples of how the best research is conducted. Some fields (like structural equation modeling, say) have exemplars which are very similar and allow creativity only within that narrow and defined space. These “Normal” fields are capable of rapid progress. Other fields (like political science, say) have exemplars which are so wide and dispirit that researchers can basically do anything they want, and progress is extremely difficult.

ways_of_knowing_2

One way this matters is that in less-progressive, more scientific, looser-exemplar, fields, “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.

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The worse your bargaining position as you start in life, the more you find yourself without experience in an experiential field, the harder everything is. In some antiquated and retrogressive societies, workers with poor negotiating position are even told who they may and may not marry.

Of course, it’s possible for the young to do well in less progressive fields of study, as the old may do well in more progressive fields of study. It’s just that the field is never balanced. Experience pays, and the level of progressive in the field determines how much.