Since I wrote my IJ piece on the policy-strategy distinction, I’ve thought a lot about academia, policy relevance, and the proper place for interaction between researchers and policymakers.
As a PhD student that has a foot more in the policy world than purely academic world, the frequent complaints about the policymaker-academia gap in International Relations and Political Science have never made sense to me. But it has taken me time to think about why.
It struck me today that the basic mental model many academics decrying the gap have in mind is the following:
- Academic creates scholarly output
- Policymaker evaluates output
- Policymaker exclaims “Wow, John Doe’s theory of ___ is brilliant! I previously thought X policy issue should be handled by choosing Y, now I think I will use ____ theory to influence my decisions!”
- Everyone lives happily ever after
This is a deliberate caricature, but it’s distilled from reading thousands of op-eds in various print and online journals lamenting the gap. So if this is so straightforward and simple, why doesn’t it happen?
The consensus explanation is the following sequence:
- Academic creates scholarly output
- Policymaker evaluates output
- Policymaker says “Wow, John Doe’s theory of ___ is so theoretical, poorly written, and filled with math. I’m just going to ignore it and not allow it to influence X policy issue I’m deciding.”
- An academic writes an op-ed decrying IR for having too much math, theory, and thus repelling the policymaker.
I am extremely dubious about this. First off, policymakers themselves rarely take an interest in any detailed subject-matter topic. They do not have the time to research warfare, technology, or complex economics and financial instruments. Instead, an army of 22-year old aides distills highly technical details into PowerPoints and memos. They have foreign policy and economic advisors that control and structure their flow of information. And policymakers seem to like math and theory in some areas and hate it in others.
The second sequence, which some academics seem to buy into is, is equally bogus.
- Academic creates scholarly output
- Policymaker evaluates output
- Policymaker says, “Wow, John Doe’s theory of ____ speaks truth to power about my imperialistic attempt to control the peaceful nation of X or oppress the subaltern in the Global South! I must not only ignore it, but I must starve the academy of funds so no one will discover my dastardly scheme!”
- Research is ignored, funding is cut.
This conception of policymaker reception of academic literature really, really fundamentally overstates how much a professor that writes for a journal with an tiny audience threatens a policymaker by “speaking truth to power.”
It’s definitely plausible that some politico may have an ideological aversion to social science (like NSF defunder Rep. Coburn), but one doubts Coburn really fears that professors talking about Foucault or the Frankfurt School are going to subvert America into The People’s Revolutionary Republic of Zizek. Instead, Coburn used traditional populist themes about shrinking the size of government, and implicitly referenced William F. Buckley’s famous Jacksonian rhetoric about preferring to be governed by random people in a phone book rather than Ivy League academics. So Coburn’s defunding of the poli-sci NSF budget is not really specific to political science — it’s just another episode in the recurring quest to shrink government and promote Jacksonian cultural concepts. Indeed, it’s pretty obvious from the hearings that Coburn never really bothered to evaluate any poli-sci research funded by the NSF.
A more mild variation of this that is still problematic goes as follows:
- Academic creates scholarly output
- Policymaker evaluates output
- (a) Policymakers says, “Wow, I’m so lazy that I can’t be bothered to take John Doe’s theory of ____ seriously.” (b)”Wow, John Doe’s theory is useless to me because it doesn’t help me win elections.” (c) ”Wow, John Doe’s theory is useless to me because I am a practically minded person and I don’t like theory to begin with.”
- Research is ignored.
There are grains of truth inherent in this as well but it also doesn’t really describe the full picture. And like the more extreme version, it flatters the academic too much.
As I considered all of this, there was something nagging me that I couldn’t quite get out until now. What all of these mental models of the policy-academic interaction have in common is a basic structure that assumes academics make research that has policy implications, and policymakers inherently should take this research seriously. All of the respective sequences differ over who is to blame for it not being taken seriously, and why. But they all have in common the assumption that it should.
The problem, in other words, is the very assumption that policymakers inherently ought to pay attention to academic research when making policy decisions. This assumption itself is overly flattering to the academic ego and probably represents the #1 barrier that academics face in trying to get their research out. I will explain why in the following paragraphs.
Academics are not thinking about the following questions: (1) why should a politician take my research seriously? (2) is the function that I would be providing with my research actually being fulfilled by someone else already? (3) could I realistically outcompete whoever else is performing in a similar function in the market for a policymaker’s attention?
The assumption that the academic-policy relationship should be structured as academic output ——> policy influence is faulty. So forget about whether or not theory or less math would make a difference. Think instead about whether we eggheads are selling a product that policymakers actually need.In fact, we are selling them something they already have, and is provided by people within the DC political ecosystem that live to boil down complex issues for the Senator, cabinet member, or chief executive. You cannot evaluate the policy influence question purely in the abstract, you have to consider who else is in the market.
Academics chasing policy influence are trying to supply a market is already extremely saturated. And they are competing with other market suppliers that have a substantial structural advantage and are better optimized to serve the needs of the customer. And the result is akin to what would happen if a quirky indie bookstore tried to compete with Amazon.com in the areas where Jeff Bezos has the most competitive advantage. Yet the quirky indie bookstore might eventually realize that it might be better selling to a subset of the market that values indie-ness and rare books rather than try to step into the world of mass-market retail. IR and poli-sci lamenters of the “gap” haven’t caught on yet.
I only came to realize this basic faulty assumption due to thoughts provoked by my own unique coursework this semester and my preparation for next semester.
In preparation for classes I will be taking next year on software engineering and artificial intelligence, I have also been cramming my head with concepts from engineering and theoretical computer science. Relative to social science, the more mathematically based disciplines of optimization, computational complexity, etc are a very different world. They have theory that are just as rich and interesting as social science, but the underlying purpose deals more directly with problem-solving than most social science.
Computer scientists, engineers, economists, and mathematicians also have a much easier time being able to gain attention, funding, and research kudos from government than political scientists or other “softer” sciences. Why? I have been critical of bad academic-side assumptions, but fairness dictates that we must recognize that part of it is underlying policymaker bias. For whatever reasons, policymakers simply rate poli-sci/IR and related disciplines a lot lower than economics. I wholly agree with Daniel Drezner that policymakers are inconsistent in their preferences. They claim to find math and theory impractical, but seem to eat up economics (the so-called “dismal science”). That’s at least part of the problem. But I also think that prejudice alone as an explanation lets academics off the hook too easily.
One way of visualizing the problem is the market metaphor I introduced above. Academics are trying to sell product in a market that’s oversaturated and dominated by establishment players. So of course there is low demand for academic inputs to policy. But another way of thinking about it lies in the policy-strategy distinction that I explored in classical strategy. I am using here a framework that is derived from the classical strategic (e.g. Clausewitzian) as a broader metaphor for the problem.
First, let’s ask the question what does it mean to be policy-relevant? In order to answer that, it would help to have a coherent distinction between policy, strategy, and tactics. They are all very different, and the relationship between them matters.
Policy is a condition or stipulation (e.g. Carthage must be destroyed, South Korea must remain independent) that must be satisfied by strategy. Strategy is a bridge between action and political payoff. Strategy, in turn, is implemented as tactical actions. Though strategy is a process of dialogue and negotiation, it also involves hard problem-solving. The idea of balancing ends, ways, and means is in some ways structurally similar to the process of mathematical optimization that engineers and computer scientists consider, even if it lacks concepts like convexity, concavity, and local and global optima on a fitness landscape.
Most importantly, what produces policy and strategy is very strikingly different. Strategy, as an instrumental structure, is about how you get from here to there. And while strategy at its most abstract is tied to the underlying policy, it is also composed of numerous subproblems having to do with particular combinations of tactics. This is sometimes called “operational art” or the “operational level of war,” although I’ve become very nervous about using the term except in the most metaphorical of ways. While I think operational art can describe a class of strategic problems and methods, I don’t believe in an operational level of war anymore.
What are strategic (e.g. instrumental) questions? One example is the challenge of defending Britain against the Luftwaffe, which required synchronization of air forces, ground-based weapons, and communications networks to produce competitive advantage against Hitler’s strategic air offensive. Let’s jump to the Civil War. The switch from “concentration in space” (trying to defeat the Army of Northern Virginia with one fell swoop or capturing Richmond) to “concentration in time” (a distributed offensive on the entire continent to force the Confederacy to deal with an strategic dilemma. And in peacetime it is competitive strategy that chooses the best area of a strategic competition to “invest” in to create advantage. Does the United States choose to stick with aircraft carriers, or should it try to create long-range autonomous strike systems to counter an anti-access/area denial strategy?
And each of these general questions have in turn tons of more narrow subproblems that must be solved in order to effectively implement strategy. Take the Europe or Pacific strategic question in WWII. One can choose to prioritize the European theater first but this necessitates solving the problem of the German U-Boat offensive against the Anglo-American merchant marine. And that involved thinking about the optimal formations for hunting and destroying U-Boat wolfpacks. Questions about nuclear strategy involve considerations about the best ways to deploy nuclear weapons, the dynamics of coercion and deterrence, and ideas about the security dilemma and cooperation — each of which can be decomposed to technical subproblems.
These sorts of questions are areas where social scientists and academics in general have historically provided great value. And in providing that value, academics have also stimulated advances in their own fields. We owe a substantial amount of economic theory to the game theory and decision theory problems of World War II and the Cold War. Trying to find out how to best understand Japanese culture in WWII produced a landmark work of anthropology. Thinking about specific communication, command, and control problems spurred landmark theoretical innovations in computer science. And we also owe Clausewitz’s On War to the “cognitive challenge of war” faced by the Scharnhorst school as it attempted to grapple with how to comprehend the shifts in warfare signaled by the “God of War” Napoleon Bonaparate.
There is also the matter that the process of strategic dialogue lends itself better to academic talents than trying to influence top-level policy. Because policy is “what must be” and strategy is “how we can make it so,” the dynamics that craft policy and strategy are different. While both creatures of politics, policy is at least in theory more related to the outcome of a messy political process. Why is it messy? A political process is essentially a struggle to decide what should be that plays out as a struggle between policy elites.
Unless academics become policy elites themselves or gain access to policy elites that can serve as surrogates, they are ill-equipped to engage in policy advocacy. And being academics does not lend them any extra credibility as advocates — on the contrary, it seems to actually diminish credibility due to the populist stereotype of the Ivory Tower “pointy head.” There is nothing inherent in the status of an academic that commands deference in America.
The Jacksonian sentiments that Coburn exploited have real resonance that academics often miss when they make fun of politicians and populist rhetoric. A mixture of populism and pragmatism is a core aspect of American political culture. America has built its cultural mythos around the scrappy underdog, the practical and pragmatic engineer, and the entrepreneur that drops out of school to revolutionize the computing industry. This is not Europe or Asia, where public intellectuals and scholars command a certain level of automatic deference.
There are no American equivalents of China’s narratives of the wise Confucian scholar that imparts wisdom to disciples. If a scholar in the US envisions this — not heavy does of Jacksonian populism — as the natural way of things, they ought to curse themselves for not being born in Han China and missing out on the opportunity to chill out with Dong Zhongshu. But America is unlikely to become Han China anytime in the near future.
Policymakers also sometimes take a dim view of academics telling them how to do their jobs. Policymakers face pressures academics do not, have goals that academics do not, and have access to information academics do not. They also already have an existing staff and advisor infrastructure for input to decisions that are already well-acclimated to their goals and preferences. Sometimes these choices can be highly idiosyncratic. John F. Kennedy used his brother Robert, who had no national security portfolio beyond his purview as Attorney General, as an enforcer during the Cuban Missile Crisis negotiations. Barack Obama’s confidante and consigliere was Rahm Emanuel, a man whose talents lay more in the campaign trail than governance.
As I’ve said before, academics seeking to influence policy are scrappy upstarts trying to break into a highly saturated market. Unless they can find a way of disrupting that market as to break the dominance of the giants that dominate it, they’re simply not going to gain traction.
So academics seeking to make a difference in the government find themselves facing two choices — both of which are genuine but have distinct tradeoffs.
If they want to influence policy, they have to become a part of the DC ecosystem that feeds into policy. They have to learn how to navigate a wholly different environment than the university, and acquire the connections and relationships necessary to move around in DC. This isn’t impossible. Many academics, with Henry Kissinger being the most famous, have made this transition from scholar to politico. But the problem with this is that many academics become academics precisely because they want to pursue knowledge. Very few academics get a PhD with the expressed purpose of being in the Beltway.
Compare this with the backgrounds and motivations of many other Beltway residents. Many politicians and advisors get their start on campaigns, and have legal, corporate, consulting, public relations backgrounds. It is precisely the desire to pursue something higher and more monastic than the corporate life, the PR world, or the daily fracas of domestic politics that drives most academics to endure the rigors of a PhD. The opportunity costs — especially today — are too great otherwise. There are exceptions — Kissinger (again) was a political animal with a deep background in geopolitics, strategic history, and nuclear warfare. But Kissinger triumphed over equally brainy men because he developed the skillset necessary to be successful in a policy environment.
And often the experience of being in a policy environment can be very destabilizing to those used to the norms, social discourse, and incentives of the academy. Academics are no strangers to politicking, but there is a huge difference between the highly ritualized conflict over grants and hiring committees and the more free-flowing and dynamic DC political game. Vali Nasr’s unhappy experience working on Afghan policy is a case in point. Yes, much of what Nasr experienced in his articles was petty, unfortunate, and suboptimal. You feel for the guy. But Nasr (through no fault of his own) seems to express in his memoir that he wasn’t prepared for the bureaucratic dynamics he would encounter. Perhaps if he had access to the policy equivalent of what the military calls the Intelligence Preparation of the Battlefield beforehand, he might have been better able to adapt to the dynamics he found so challenging.
So doing what it takes to influence policy isn’t for every social science PhD or prof. What if they still want to make a difference?
The alternative approach lies in giving up on influencing policy, and focusing on very narrow aspects of problem-solving that have to do (loosely) with strategy and tactics. Social scientists are uniquely placed to provide value with this area. They have a wide base of expertise and knowledge that allows them to think about narrow problems from a holistic standpoint. And they also have the methodological training to handle technical questions — they are trained in advanced quantitative and qualitative research methods that go beyond Stat 101 or an undergrad ethnography/anthro course. Many also can read and write in rare foreign languages and have done fieldwork in exotic places of interest to the USG.
Most of all, social science academics live for intellectual puzzles and challenges. They stay up late pondering abstract questions like structure, agency, and Nash equilibriums. They are competitive and trained to systematically evaluate previous ideas, ascertain what is missing/find bad assumptions, and propose an original contribution that goes a step beyond the state of the art. And if they’ve completed their dissertation, they have demonstrated tenacity and grit. Many do not make it to that point. All of these things are selling points for academics generally, but they are selling points in particular for the idea of the policy-engaged academic as strategic/tactical problem-solver instead of policy advisor.
I’m portraying these two approaches as absolutes, but there are always exceptions to the rule. Anyone who follows the wonk world in DC can name a person that sits smack dab in the middle of the dichotomy I have just constructed. It is not purely a binary, and the degree to which an academic-policy connection fits into either category sits on a sliding scale. But jobs that really straddle the line between the policy game and strategic and tactical problem-solving are far and few between. Trying to base your dreams around the hope of snagging one is like being a rapper that wants to one day rock arenas like Jay-Z and (like HOV) hold down six summers. Dreams are great, but there are very, very people that can be Jay-Z. But of course if you can be Jay-Z, then selling out arenas, touring exotic places with Beyonce in tow, and making a record like The Blueprint are things you shouldn’t give up for anything in the world!
My portrayal of the problem-solving role as an alternative for academics also comes from some personal experience. Working at Caerus Analytics as as a summer fellow was one of my most fulfilling experiences since I entered college. Yes, I ended up having to leave early due to family matters that I had to attend to and preparations for starting at GMU — and I hated being dragged away from working on Caerus’ fascinating projects so I could have to take care of personal business. But despite these external obstacles, I loved the experience of putting my social science skills and subject matter base to use working on real problems. I also was thrilled watching my GMU classmate David Masad build computer programs that helped meet client needs and use event data to think about the Syrian Civil War. And applying my IR and security knowledge as a civilian volunteer at the LA Sheriff’s Department in undergrad was also a great experience.
How could something that puts social science to work in a different way be structured? Well, now you are about to see why my current coursework is prompting these thoughts.
In the technical fields of computer science, mathematics, and engineering, both the government and industry contracts/employs more academics than you would expect for the social sciences. Some of it is applied research with very narrow parameters. But the corporate community also funds substantial amounts of basic research in the hope it will lead to innovations. Facebook, for example, has just plunked down a great deal of $$ to create an artificial intelligence research lab stocked with top-notch academics. But could you imagine Google ransacking the chair of a top poli-sci department to head a research lab?
Social scientists ought to take a hint. Yes, computer science is an experimental discipline that has a lot to do with engineering. But there is nothing that in theory prevents Facebook from funding an comparative politics lab and hiring a professor from a top 10 school to head it. As long as the basic and applied research could plausibly lead to innovations that help Facebook make more money, it could happen. The AI research lab at Facebook, for example, studies theoretical research in machine learning AI — which has obvious commercial applications in terms of optimizing FB’s bread and butter algorithms. But the actual topics being studied are so dense and theoretical that they make political science look tame. Yet Facebook still thinks that paying a bunch of PhDs to think deep thoughts about the nature of AI and learning could pay off.
There are many deep topics in comparative politics/IR that might similarly relate to Facebook’s bottom line. And I might also note that top political scientists like Gary King are increasingly using research methods right out of a Silicon Valley toolbox — the two disciplines are converging in important ways. And (as I will note later) social science subject matter expertise could also be used to create technical tools that could produce monetary value. So the idea of an corporate R&D-style approach to social science is not really that far off. And it doesn’t have to be just a ” deep thoughts about poli-sci R&D lab.” It could be an interdisciplinary research environment.
Given that King is already doing large-scale text analysis researching comparative politics anyway, why not take some political scientists interested in basic research, combine them with some computer scientists, give them a rough prompt to work on, and see what happens? This is precisely how the RAND Corporation model worked in the early Cold War, combining the expertise of economists, engineers, physicists, and mathematicians into interdisciplinary teams engaged in both basic and applied research.
A ecumenical RAND-like R&D system may also expose all kinds of scientists (social or otherwise) to ideas that would enhance their research. Technically-oriented academics in the computer sciences, engineering, mathematics, physics, biology, and related disciplines could learn valuable social science concepts that could help them pursue new lines of research. Robert Axelrod’s ideas about cooperation in international relations, for example, turn out to be equally valid at explaining microbiology. And as I write this, I am using a simulated annealing algorithm I borrowed from an engineering textbook to theorize about collective action and balancing theory in International Relations.
Even if I wouldn’t go so far as to agree with this op-ed anymore (though it was appealing at my first read), every scientist can benefit from a free exchange of ideas and collaboration. If Axelrod’s deep thoughts about nuclear deterrence and the security dilemma can help a biologist, a biologist can help a deterrence theorist.
A cautionary note:
I’m voicing a lot of opinions about the nature of social science and government, but I can only speak for myself. My case is unique. I’m a PhD student in an interdisciplinary program that forces me to simultaneously combine my subject-matter knowledge in strategy and political science with software engineering and concepts from computer science and artificial intelligence. I live in DC, and I’ve always idolized academics/think-tankers/consultants like Andrew Exum, Eliot Cohen, P.W. Singer, Jay Ulfelder, and Erin Simpson that apply social science skills to concrete problems while still writing and commenting on general theoretical topics.
My primary disciplinary influences are also nontraditional. My friend “Dan tdaxp” — who has advanced degrees in psychological and computational subjects and a private sector job, also strongly influenced my choice to pursue a PhD in Computational Social Science. My other friend and informal mentor Aaron Frank also currently works as a modeler for a large defense and technology firm. And the aforementioned John Myles White and his algorithm-loving social science comrades Trey Causey and Drew Conway all ended up being nontraditional academics as well.
So I’m biased. I admit. And I’m also not representative of the overall population that I’m addressing with this somewhat insider basebally post. Take what I say with a grain of salt, pepper, whatever else suffices.
But I strongly believe that the academic community really needs to fundamentally rethink the concept of policy relevance and the academic-policy linkage. Wanting to be a part of government or industry and influence people beyond your cloister is an understandable feeling. It’s not for everyone, and I wouldn’t consider it the purpose of social science. But it is a noble urge and also a practical one in a time of declining social science budgets. Those perpetually lamenting the gap are not wrong that the gap poses a threat to social science, and they are also correct to inquire deeply about relevance.
And let’s not forget as well that many people concerned with the gap are just patriotic Americans looking for a way to give back, and are trying to find a way to make their theoretical and methodological specialties help the country. I relate to both desires — I like abstraction but I also like being engaged in the world. And the Iraq War triggered a strong desire to acquire knowledge and skills that allow me to produce something of value for my country. Whether that means providing input on a thorny problem or devising better strategies or tactics that would help it defeat its enemies.
While many academics view military/intelligence involvement with trepidation, my heroes are men like Herman Kahn, Bernard Brodie, and Thomas Schelling. And as overhyped as the Surge may have been, it still mattered. The US government’s usage of people like Emma Sky, David Kilcullen, Kenneth Pollack, and other academics to help design and implement the Surge was also deeply inspiring to me. So I have nothing against academics helping the government, and think more should consider doing so.
But helping the government by trying to get them to pay attention to your research in the hope they’ll change their policy preferences is a losing battle unless you can be the one PhD inside the Situation Room when the President asks about how we’re going to deal with the security problem posed by the Homer Simpson People’s Liberation Army or Japan and China scrambling fighter jets over that contentious pile of rocks known as the Skinny Indie Rock Jeans Atoll. You could structure your career around trying to get to that Situation Room or other rooms like it, and still have a fulfilling life. Many of the people that I looked up to in college were those who could be that PhD in the Situation Room.
But it isn’t the only option.
Instead of telling the President that he needs to take a hard line against the Homer Simpson insurgents and battle for his attention with the Secretary of State’s more dovish opinion, you could pursue an easier means of effecting an intellectual contribution — as long as you are willing to trade being Kissinger for being a problem-solver that works within policy. Why not just make yourself available to lend a helping hand? Why not build something of value to the policymaker?
If you are reading the papers and you see that sailors are dying in droves because the Navy is powerless to counter the German U-boat wolfpacks, why not get down to your study and think about how you could use game theory to model the challenge of protecting the merchant fleet? If you are worried about civil liberties and oppose bulk NSA collection, why not work on a method that might negate the need for such heavy-handed procedures and thus make it easier for Ft. Meade to target its snooping more carefully?
And for those of us that can program or at least work with software engineers, why not help build tools that solve problems? Academics increasingly design analytical software tools as hobbies or for professional activities. And these tools are easier to sell to those outside the academy than research. John Myles White (a psychology PhD turned data scientist), for example, helped build the scientific programming language Julia. A host of people are working on event-data. An IR academic with expertise in International Political Economy might work with a computer scientist to help produce an computer program that would help give the USG a decision advantage in trade negotiations. An IR academic studying constructivism and norm diffusion could work with DoD and State Department public diplomacy and information personnel on making some kind of analytical tool that could better aid the creation of public diplomacy policies. Political scientists studying international humanitarian law and war law could help work to build first person shooter games (similar to the Battlefield and Call of Duty games US soldiers love) to help teach adherence to war law and IHL under very irregular conditions. The list goes on.
All of the potential use cases I can easily recite come from security and general IR, because that is my subject matter base. So, another bias you should take into account. But you could easily think about different applications.
The future of academia and policy is not as dark as portrayed. Nor are the obstacles as grand as they seem. If we can think outside our default assumption of what academics should do in government, we can start to bridge the gap by thinking differently. Despite what populists often say about us and practically-minded DC residents believe, we do have something unique, valuable, and important to contribute. And the policy world would be better off if we had a louder voice.
But in order to raise our forces, we need to think hard about where we want our impact to be felt. Policy influence implies academics being involved in elite forums that make policy, and adapting to the norms and dynamics of those forums. Problem-solving and an R&D-like approach at least has more congruence with what academics are used to.
I personally would be happy with either. I’ve tried to remain flexible about my own future, and try to enjoy the intellectual challenge of a PhD and research while also being creative about how I can use my knowledge and skills. I also have spent so much time participating in policy debates on blogs, Twitter, and defense and foreign affairs journals that I also am not completely attached to any one kind of environment.
But I suspect most academics really would prefer a setting that would exploit existing skills and seem at least partially familiar compared to learning new skills and social adaptation to what many might consider an alien landscape. Hence my raising of an alternative to the standard idea of gap-bridging that seems to be contemplated.
And who knows? Maybe if the R&D/problem-solving setting is successful enough, it could create the relationships and connections that would allow more academics to influence policy. A bridge across a gap can start out narrow. But if the customer ups his or her demand, then bridges are widened so the businessman can deliver more supply. But first let’s pull back from complaining about the existence of the gap and think a bit more critically.
I don’t mean to suggest that this is all purely a matter of academics rethinking their priors about the policy-academia gap. I’ve only focused on the academic side because the subject of this post is about the core misconception about fruitful research relationships. Both sides need to cooperate. The policy world first has to invest in creating more pathways for academics to participate in solving the kind of problems I mention above or building the tools I suggest. The kind of structures capable of facilitating those interactions are currently underdeveloped and still emerging. The Minerva program is a good first start, as is the normal National Science Foundation process. But it could be more streamlined, efficient, and modular.
One big problem is transaction costs and information barriers that prevent the “market” from re-adjusting itself. Academics are out of tune with what policymakers want, and policymakers lack an effective means to communicate to academics what they want. In turn, policymakers lack information about what academics can do to help, and academics lack viable means of communicating their strengths and skills.
The problem cries out for some kind of matching structure that could function almost in the manner of an online dating website. An OKCupid or Match.com for the policymaker and the professor. I’m being facetious about the dating website analogy, but it’s hard to bridge the gap without lowering the transaction costs and information barriers that currently characterize the substantial misunderstanding and divide between the academy and the policy world.
But even though academic misconceptions about the academia-policy relationship aren’t the only problem, they are a problem. Academics, to paraphrase JFK, that are interested in government should memorize this mantra: “Ask not how I can get a policymaker to use my research when making policy decisions.” Instead, we should be asking ourselves how we can creatively think about filling needs that already exist — or perhaps creating new ones.