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Sometimes you come across people that permanently change the way you think. About life, yourself, or an area of study. They instill a sense of resolute optimism about the world and your abilities. Bear Braumoeller was that person for us. Wise, accomplished, brilliant, humble, and kind. Anyone who can be remembered that way lived life well. Bear is one of those people. He was our professor, mentor, colleague, and friend. We were richer for knowing him, and are poorer for his passing.
We first got the chance to meet Bear during our recruitment process to Ohio State. We gravitated toward him and his research. Bear went out of his way to bring in the best and brightest graduate students to the program, and was absolutely relentless in his efforts. He took phone calls from us, discussed all of our options, and went out of his way to procure funds and opportunities for every student. Bear was known to showcase some of the best places to eat in Columbus, too. We all got along with Bear immediately, and he became a powerful force in our proverbial corner, helping us navigate and thrive in graduate school.
We’ve been fortunate to have terrific professors, but Bear was an unusually good professor. In graduate seminars, we were exposed to a wide breadth of topics in political and social science. The breadth that Bear introduced in his courses was unique for a political science class. Most importantly, he taught us how to read books and articles critically and constructively. Graduate students are often great at tearing apart a piece of scholarship. And that’s important. But published works are generally published for a reason, he reminded us, and so it’s equally important to identify their strengths in addition to their weaknesses. That approach cultivated humility (there are always tradeoffs in research) but was also encouraging. If graduate students think pieces published by top scholars in good journals are bad because we only focus on their downsides, how could we possibly do good work?
Bear’s take on the literature and the discipline was just like his research interests: complex, rich, and nuanced. He loved what he studied, and his knowledge in these areas often seemed encyclopedic. He would recommend a citation and quote on a whim, from memory. He always asked big, important questions, and he did his best to answer them. His two books, The Great Powers and the International System and Only the Dead, address two important questions in international politics: how leaders and historical circumstances jointly shape major historical outcomes, and whether war is declining. He was methodologically sophisticated, but for him it was about getting closer to the truth. He truly didn’t care what method you used if it fit the question. He had a great academic pedigree (University of Chicago, University of Michigan) but he wasn’t elitist. He wanted to hear from smart people, and he believed in demystifying the academy, making it accessible.
Bear was a formal advisor, but also a tremendous mentor to us. He helped guide many important decisions in graduate school, from the type of training we needed, our choice of dissertation topics, to the construction of our committees. Bear’s was ready to provide feedback on any idea or draft, regardless of its stage of development. He was also kind when he didn’t have to be, and when no one would praise him for it publicly. It’s just who he was. His feedback was always constructive and intended to enable better work. When we made mistakes he would correct us – firmly, gently, and privately.
Bear created the MESO (Modeling Emergent Social Order) Lab, which has been supported by NSF and the Carnegie Corporation of New York. It didn’t start as a lab, though. The first day some of us gathered in the conference room, it was just a group of people who Bear thought might be interested in an idea he had. We talked it over – a question about the relationship between hierarchical order and war – and decided it was interesting enough to pursue. One of the first things we did was to gather on a Thursday and just start working, the whole day, with no distractions, putting ideas on paper and into code. He would call them Hackathons, reminiscent of a Silicon Valley start-up. These early days made a huge impact on Bear. Numerous times after that, in presentations or conversations about what we were doing, he would mention that he had never before felt as productive as he did in those early research sessions. He realized that this was it, this was the way forward for him. This was not merely working on a project. This represented a change in how he was going to do research, in how he approached being a professor and working with graduate students.
International Relations is not known for collaborative research. The vast majority of major work in the field has a single author, more rarely two, and very rarely more than two authors. Some of us had co-authored with Bear before, but this was different. Whereas previous partnerships were more traditional co-authored research projects in which each author did their part, this was something bigger. Bear had a vision beyond group publications. He wanted us to grow into scholars who would think big, who wouldn’t be afraid to tackle questions that might seem intimidatingly broad, and who would pull the right minds together to tackle those problems. Our first project was “Hierarchy and War”, which addresses two of the biggest topics in the discipline. We were meant to say something new about both – and the relationship between them – in a single paper. The ambition was daunting, but that was Bear’s way: take big, important questions and swing as hard as you could at answering them.
As membership in the MESO Lab grew and expanded, Bear expanded the lab’s projects as well. As always, all projects are led by us, the students. Bear gave us remarkable autonomy and control over these projects: despite our status as graduate students, we had the final say over theoretical framing, modeling decisions, and data analysis. He gave us room to explore different paths, even if it meant delaying the progress of the project. In addition to developing us as scholars, he helped us develop as people. Bear understood that a good life outside of work with food, travel, and family, was of equal importance to doing great work. He expected high quality work from us, but the lab never became a source of stress or frustration. Being in the MESO Lab has been one of the greatest blessings from being Bear’s students. Just as a system is not equal to the sum of its parts, our lab produces scholarship that is more creative and fruitful than what we could individually create.
The loss of Bear leaves a gaping hole, not only in our lab but in our profession more broadly. People around the world have so beautifully expressed their appreciation and admiration for Bear, with an outpouring of tributes and memories. As is so often the case with grieving, those left behind expressed a desire for one more conversation, one more snarky comment, one more belly laugh, one more smile. His presence and reputation were felt with the same gravity and strength across the discipline. So many people felt as strongly and warmly about Bear as we did.
It is impossible to properly account for all the things Bear taught us. He taught us to be ambitious in our research. He taught us to be fearless when exploring and implementing new ideas. He taught us to be gentle and kind, with others and ourselves. His ideas and influence are all over our projects and dissertations. We will do our best to carry forward that work and legacy.
Rest in peace, Bear. It was a privilege and honor to have known you as a leader, mentor, and friend. Your memory is a blessing and you are missed.
About the authors
Maryum Alam, Andrew Goodhart, Michael Lopate, Haoming Xiong, and Liuya Zhang are political science Ph.D. candidates at The Ohio State University. Maël van Beek is an incoming postdoctoral research associate at Princeton University. David Peterson is an incoming post-doctoral fellow at the University of Michigan. Jared Edgerton is an Assistant Professor of political science at the University of Texas, Dallas.
Please consider donating to support Bear’s daughter, Molly Braumoeller.
There is an increasing focus in academic and policy circles on research-policy partnerships. These partnerships are often achieved through co-creation, or “the joint production of innovation between combinations of industry, research, government and civil society.” Co-creation is central to innovation in the hard sciences and technology, but its role in international relations scholarship and aid policy remains underdeveloped.
As scholars of international aid practice, we believe that co-creation can help us design and conduct more relevant, rigorous, and impactful research. It is also a core mission of the Research on International Policy Implementation Lab (RIPIL), whose co-creation process engages policymakers and practitioners in: 1) the generation of important, policy-relevant research questions; 2) research on these questions, through regular validation and consultation; and 3) the development and dissemination of findings and their policy implications, which often leads to the identification of important new research questions and opportunities.
In this piece, we focus on the first phase: the co-creation of research questions. This is one of the trickiest phases of the co-creation process because it requires researchers and policymakers to find a common question and research design that aligns with academics’ incentive to publish rigorous research and policymakers’ incentive to feed evidence into the policy process. Future blog posts will discuss how to implement co-created research and disseminate co-created findings.
At the beginning of the COVID-19 pandemic, we initiated a collaboration intended to generate policy-relevant research questions on the changing nature of international aid. Our aim was to get a sense of whether the combined shocks of COVID-19, growing calls to decolonize aid, and the rise of populism and popular protest had changed the underlying power dynamics in aid.
Importantly, in this project, we did not just want to learn from practitioners based in Western Europe or North America. We wanted insights from key thinkers and actors from the context where aid dependency has been most acute: the African continent. We wanted to understand how these thought leaders viewed aid-related power dynamics and how research could help answer their most puzzling questions.
Between 2020 and 2022, we conducted one-on-one interviews, organized virtual focus groups, and hosted a high-level roundtable in Geneva with donor governments and international non-government organizations (INGOs) on power in aid, all to better understand the changing nature of aid and the research questions that matter to policymakers, practitioners, and key African thinkers.
A synthesis of our thematic findings is available here. In this blog, we discuss our four most important lessons learned about the co-creation process itself.
We saw our discussions as an exchange of knowledge. Therefore, we wanted to make sure that we brought something to the table. Before each meeting and workshop, we circulated a summary of the existing research and our discussions from previous meetings. Having set the stage with these syntheses, we then focused each interview and workshop on listening (not talking). This allowed us to build on the existing academic knowledge, and to use the conversations to identify how it diverged from the everyday experiences of our interviewees and workshop participants. It also allowed each participant to arrive feeling well-prepared, in part through the materials we provided.
Importantly, we began each workshop and roundtable with presentations by African scholars and practitioners. They helped shape the power dynamics of the conversation from the outset.
The process worked. Our preparation, planning, and careful facilitation enabled open and respectful communication among key African thinkers and representatives of international non-governmental organizations (INGOs), donor governments, recipient governments, and the United Nations.
We wanted to hear what donors, recipients, and key observers had to say about changing power dynamics around aid. We wanted to understand the perspectives of people from different recipient and donor countries to see if there might be broader trends.
Most of the people who participated in our discussions did not know us or each other. To enable an open conversation, we had to create an environment where they could trust us, and each other. This took time. We had to reach out to people repeatedly; build relationships through one-on-one conversations at the beginning of the process; and use these one-on-one conversations and our repeated meetings over time to establish our own credibility. This paid off in the quality of the conversations we were eventually able to have in our focus-group discussions and, subsequently, in our high-level panel in Geneva.
If the point of co-creation is to spark new lines of inquiry, researchers involved in co-creation must be willing to let go of the questions they think they should be asking and be open to the questions that others think are most important.
In our initial one-on-one conversations, we focused on asking open-ended, big picture questions to get a sense of whether participants thought power dynamics had changed and, if so, how. In some cases, their answers confirmed our assumptions. In others, we were surprised by new insights.
For example, respondents indicated that the rise of populism in Africa was leading to a backlash against aid recipients and donors. This led us to start a new research project on aid and populism that we could not have imagined at the beginning of the process.
This is hard to understate. Co-creating research questions involves the translation and transfer of ideas between science, policy, and practice over an extended period. This means that researchers should not engage in co-creation expecting quick wins or immediate research results. Co-creation is not a quick strategy to increase your research output, but a long-term commitment to identifying important research questions and building the relationships necessary to answer them.
When done well, co-creation has the potential to improve the relevance and impact of research, foster greater collaboration and understanding between researchers and practitioners, and ultimately contribute to positive change in the aid sector. But it is time-consuming and requires patience, careful planning, regularly questioning one’s assumptions, and continuous communication.
We believe that the investment of adequate time up front has been worthwhile, greatly enhancing our understanding of the power dynamics in aid today and enabling us to ask (and answer) cutting-edge research questions. It has also given us the connections necessary to conduct research on these dynamics, ensuring that our research authentically reflects the views shared by African stakeholders and is relevant to aid policymakers and practitioners globally.
To learn more about RIPIL, visit https://bridgingthegapproject.org/ripil/.
The Chronicle of Higher Education recently ran a piece by Owen Kichizo Terry, an undergraduate at Columbia University, on how college students are successfully using ChatGPT to produce their essays.
The more effective, and increasingly popular, strategy is to have the AI walk you through the writing process step by step. You tell the algorithm what your topic is and ask for a central claim, then have it give you an outline to argue this claim. Depending on the topic, you might even be able to have it write each paragraph the outline calls for, one by one, then rewrite them yourself to make them flow better.
As an example, I told ChatGPT, “I have to write a 6-page close reading of the Iliad. Give me some options for very specific thesis statements.” (Just about every first-year student at my university has to write a paper resembling this one.) Here is one of its suggestions: “The gods in the Iliad are not just capricious beings who interfere in human affairs for their own amusement but also mirror the moral dilemmas and conflicts that the mortals face.” It also listed nine other ideas, any one of which I would have felt comfortable arguing. Already, a major chunk of the thinking had been done for me. As any former student knows, one of the main challenges of writing an essay is just thinking through the subject matter and coming up with a strong, debatable claim. With one snap of the fingers and almost zero brain activity, I suddenly had one.
My job was now reduced to defending this claim. But ChatGPT can help here too! I asked it to outline the paper for me, and it did so in detail, providing a five-paragraph structure and instructions on how to write each one. For instance, for “Body Paragraph 1: The Gods as Moral Arbiters,” the program wrote: “Introduce the concept of the gods as moral arbiters in the Iliad. Provide examples of how the gods act as judges of human behavior, punishing or rewarding individuals based on their actions. Analyze how the gods’ judgments reflect the moral codes and values of ancient Greek society. Use specific passages from the text to support your analysis.” All that was left now was for me to follow these instructions, and perhaps modify the structure a bit where I deemed the computer’s reasoning flawed or lackluster.
The kid, who just completed their first year at Williams, confirms that this approach is already widespread at their campus.
I spent a few hours yesterday replicating the process for two classes in my rotation: one the politics of science fiction, the other on global power politics. Here are my takeaways about the current “state of play.”
First, professors who teach courses centered on “classic” literary and political texts need to adapt yesterday. We don’t expect students to make original arguments about Jane Austen or Plato; we expect them to wrestle with “enduring” issues (it’s not even clear to me what an “original” argument about Plato would look like). ChatGPT has—as does any other internet-based LLM—access to a massive database of critical commentary on such venerable texts. These conditions make the method very effective.
Second, this is also true for films, television, popular novels, and genre fiction. I ran this experiment on a few of the books that cycle on and off my “science-fiction” syllabus—including The Fifth Head of Cerberus, The Dispossessed, The Forever War, and Dawn—and the outcomes were pretty similar to what you’d expect from “literary” classics or political philosophy.
Third, ChatGPT does significantly less well with prompts that require putting texts into dialogue with one another. Or at least those that aren’t fixtures of 101 classes.
For example, I asked ChatGPT to help me create an essay that reads The Forever War through Carl Schmitt’s The Concept of the Political. The results were… problematic. I could’ve used them to write a great essay on how actors in The Forever War construct the Taurans as a threat in order to advance their own political interests. Which sounds great. Except that’s not actually Schmitt’s argument about the friend/enemy distinction.
ChatGPT did relatively better on “compare and contrast” essays. I used the same procedure to try to create an essay that compares The Dispossessed to The Player of Games. This is not a common juxtaposition in science-fiction scholarship or science-fiction online writing, but it’s extremely easy to the two works in conversation with one another. ChatGPT generated topics and outlines that picked up on that conversation, but in a very superficial way. It gave me what I consider “high-school starter essays,” with themes like ‘both works show how an individual can make a difference’ or ‘both works use fictional settings to criticize aspects of the real world.’
Now, maybe my standards are too high, but this is the level of analysis that leaves me asking “and?” Indeed, the same is true of example used in the essay: it’s very Cliff’s Notes. Now, it’s entirely possible to get “deeper” analysis via ChatGPT. You can drill down on one of the sections it offers in a sample outline; you can ask it more specific prompts. That kind of thing.
At some point, though, this starts to become a lot of work. It also requires you to actually know something about the material.
Which leads me to my fourth reaction: I welcome some of what ChatGPT does. It consistently provides solid “five-paragraph essay” outlines. I lose track of how many times during any given semester I tell students that “I need to know what your argument is by the time I finish your introduction” and “the topic of an essay is not its argument.” ChatGPT not only does that, but it also reminds students to do that.
In some respects, ChatGPT is just doing what I do when students me with me about their essays: helping them take very crude ideas and mold them into arguments, suggesting relevant texts to rope in, and so forth. As things currently stand, I think I do a much better job on the conceptual level, but I suspect that a “conversation” with ChatGPT might be more effective at pushing them on matters of basic organization.
Fifth, ChatGPT still has a long way to go when it comes to the social sciences—or, at least International Relations. For essays handling generic 101 prompts it did okay. I imagine students are already easily using it to get As on short essays about, say, the difference between “balance of power” and “balance of threat” or on the relative stability of unipolar, bipolar, and multipolar systems.
Perhaps they’re doing so with a bit less effort than it would take to Google the same subjects and reformulate what they find in their own words? Maybe that means they’re learning less? I’m not so sure.
The “superficiality” problem became much more intense when I asked it to provide essays on recent developments in the theory and analysis of power politics. When I asked it for suggestions for references, at least half of them were either total hallucinations or pastiches of real ones. Only about a quarter were actually appropriate, and many of these were old. Asking for more recent citations was a bust. Sometimes it simply changed the years.
I began teaching in the late 1990s and started as a full-time faculty member at Georgetown in 2002. In the intervening years, it’s becoming more and more difficult to know what to do about “outside sources” for analytical essays.
I want my students to find and use outside articles—which now means through Google Scholar, JSTOR, and other databases. But I don’t want them to bypass class readings for (what they seem to think are) “easier” sources, especially as many of them are now much more comfortable looking at a webpage than with reading a PDF. I would also be very happy if I never saw another citation to “journals” with names like ProQuest and JSTOR.
I find that those students who do (implicitly or explicitly) bypass the readings often hand in essays with oddball interpretations of the relevant theories, material, or empirics. This makes it difficult to tell if I’m looking at the result of a foolish decision (‘hey, this website talks about this exact issue, I’ll build my essay around that’) or an effort to recycle someone else’s paper.
The upshot is that I don’t think it’s obvious that LLMs are going to generate worse educational outcomes than we’re already seeing.
Which leads me to the sixth issue, which is where do we go from here. Needless to say, “it’s complicated.”
The overwhelming sentiment among my colleagues is that we’re seeing an implosion of student writing skills, and that this is a bad thing. But it’s hard to know how much that matters in a world in which LLM-based applications take over a lot of everyday writing.
I strongly suspect that poor writing skills are still a big problem. It seems likely that analytic thinking is connected to clear analytic writing—and that the relationship between the two is often both bidirectional and iterative. But if we can harness LLMs to help students understand how to clearly express ideas, then maybe that’s a net good.
Much of the chatter that I hear leans toward abandoning—or at least deemphasizing—the use of take-home essays. It means, for the vast majority of students, doing their analytic writing in a bluebook under time pressure. It’s possible that makes strong writing skills even more important, as it deprives students of the ability to get feedback on drafts and help with revisions. I’m not sure it helps to teach those skills, and it will bear even less resemblance to any writing that they do after college or graduate school than a take-home paper does.
(If that’s the direction we head in, then I suppose more school districts will need to reintroduce (or at least increase their emphasis on) instruction in longhand writing. It also has significant implications for how schools handle student accommodations; it could lead students to more aggressively pursue them in the hope of evading rules on the use of ChatGPT, which could in turn reintroduce some of the Orwellian techniques used to police exams during the height of the pandemic).
For now, one of the biggest challenges to producing essays via ChatGPT remains the “citation problem.” But given various workarounds, professors who want to prevent the illicit use of ChatGPT probably already cannot pin their hopes on finding screwy references. They’ll need to base more of their grading not just on whether a student demonstrates the ability to make a decent argument about the prompt, but on whether they demonstrate a “deeper” understanding of the logic and content of the references that they use. Professor will probably also need to mandate, or at least issue strict directions about, what sources students can use.
(To be clear, that increases the amount of effort required to grade a paper. I’m acutely aware of this problem, as I already take forever to mark up assignments. I tend to provide a lot of feedback and… let’s just say that it’s not unheard of for me to send a paper back to a student many months after the end of the class.)
We also need to ask ourselves what, exactly, is the net reduction in student learning if they read both a (correct) ChatGPT explanation of an argument and the quotations that ChatGPT extracts to support it. None of this strike me as substantively all that different from skimming an article, which we routinely tell students to do. At some level, isn’t this just another route to learning the material?
AI enthusiasts claim that it won’t be long before LLM hallucinations—especially those involving references—become a thing of the past. If that’s true, then we are also going to have to reckon with the extent that the use of general-purpose LLMs creates feedback loops that favor some sources, theories, and studies over others. We are already struggling with how algorithms, including those generated through machine-learning, shape our information environment on social-media platforms and in search engines. Google scholars’ algorithm is already affecting the citations that show up in academic papers, although here at least academics mediate the process.
Regardless, how am I going to approach ChatGPT in the classroom? I am not exactly sure. I’ve rotated back into teaching one of our introductory lecture courses, which is bluebook-centered to begin with. The other class, though, is a writing-heavy seminar.
In both my class I do intend to at least talk about the promises and pitfalls of ChatGPT, complete with some demonstrations of how it can go wrong. In my seminar, I’m leaning toward integrating it into the process and requiring that students hand in the transcripts from their sessions.
What do you think?
UPDATE: As a commenter helpfully pointed out, the person whose tweet I’m responding to was a political science Professor, not a historian. This kind of messes with the framing of this post but rather than stealth re-write it I’ll leave it as is and let you interpret my Freudian slip as you like
When I was in grad school, my Department’s grad student organization made shirts that read, “Political Science: Four sub-fields, no discipline.” Behind this joke is a common observation about political science, that it is defined by its focus rather than a formal set of methods or theories. Not everyone agrees with this characterization, and there have been some efforts to craft political science-specific tools. But generally political science is a field that draws on insights and tools from other areas to study politics. This is most pronounced in international relations. IR looks not just to other fields but also other sub-fields of political science to study the world.
Many present IR’s lack of discipline as a critique. They view IR scholars as a group of raiders, pillaging ideas and methods from other disciplines then returning to our barren homeland. Two recent Twitter kerfuffles, however, demonstrate that this aspect of IR is actually our greatest strength.
I don’t spend much time on Twitter anymore, but I still seem to discover the latest controversy. Two academic ones were related in their attacks on political science.
First, a historian responded angrily to a new article in the American Political Science Review by Anna Grzymala-Busse on European state formation. The historian suggested she used overly-simplistic methods to make a point that “real” experts on early modern Europe already knew (I’ve anonymized the tweet as I don’t like engaging in Twitter attacks).
This is a common complaint I’ve heard from historians studying international issues. IR and CP either take history’s insights and repackage them as our own, or don’t realize historians have already said this. Several academic institutions I’ve been a part of have included fierce and rather petty attacks by historians on political scientists.
As some respondents to this tweet noted, however, this historian isn’t really being fair. The role of religion in state formation is hardly settled ground–I took an entire class on debates over the role of religion in nationalism in grad school. Also, isn’t it a good thing to test and confirm certain arguments using a different set of data and methods? And when pressed, he couldn’t point to what historical works the author overlooked.
Critiques of IR and political science take the place of addressing real issues within other areas of study
In a follow-up tweet, the historian also makes an ironic call for interdisciplinarity. Ironic because this is an interdisciplinary work! Grzymala-Busse combined insights from comparative politics and history to generate new knowledge; this is in line with her other work, which involves careful attention to historical detail. Those calling for interdisciplinary engagement should cheer this, unless “interdisciplinary” just means listening to historians…
The second Twitter incident involved a data scientist. A data science grad student tweeted a broadside against the replication crisis in psychology, followed by attacks on political science and the social sciences in general. Another data scientist responded by pointing out that social scientists don’t conduct our own statistical analysis and instead get “real statisticians” to do it.
Again, people took issue with this. Some noted the data science grad student hadn’t really characterized the replication crisis accurately. Others asked for specific examples (which weren’t forthcoming). I’d also point out that it is true data science does have a real impact on our lives, but it’s hardly a positive one; one data science course I took focused on things like getting around CAPTCHA tests and tricking spam filters. And in practice “interdisciplinary” for data science often means using Python to study political or social issues without engaging actual subject matter experts.
These are very different controversies, and I’m sure these two people wouldn’t agree on much if forced to have a conversation. But both involve the perennial attack on political science (and IR by extension): we don’t come up with our own insights or methods, we just steal the former and implement the latter badly.
I thought of this debate recently while visiting the excellent Jorvik Viking Centre in York, England. The popular view of the Norse raiders known as vikings is of pillaging hordes, and that was certainly the case initially. But as often happens, they settled down. And in the case of Jorvik, they created a thriving cosmopolitan society enabled through their wide-ranging travels.
Maybe I’m pushing this metaphor a bit here, but I think of IR as Jorvik.
Yes, we got our start by combining economic models and humanistic insights. Yes, our research tends to include references from disparate traditions. Yes, our data is messier than other fields or even sub-fields within political science.
These issues all became strengths, however.
Because of IR’s broad roots we have to be conversant in different disciplines. When engaging with people from other disciplines, I often get the sense they’ve never really read anything from my field; their critiques are often caricatures. By contrast, many IR scholars are well-read in other fields.
Additionally, we recognize the difficulty of drawing on and testing different disciplines. That’s why you can find IR and political science discussions about combining methodologies or triangulating among competing schools of historiography.
Finally, the challenge of dealing with incredibly messy data has created problems for IR but also led to fertile debates. For example, the problem of selection effects in conflict onset has led to a useful back-and-forth.
Interdisciplinary means each side listens to and learns from the other, not that one asserts superiority and territoriality
Beyond that, these critiques of political science and IR take the place of addressing real issues within other areas of study. In C.P. Cavafy’s poem, “Waiting for the Barbarians” (which I referenced above) the inhabitants of a classical city sit and wait for the barbarians to arrive instead of dealing with the problems in their civilization. We can sense this in some of the attacks I’m discussing.
Historians are rightly frustrated at the lack of support for and interest in the humanities from universities and the general public. They often, however, see political science as the problem, such as Grzymala-Busse making a splash by engaging in historical debates. I am also reminded of a seminar my grad school put on to help students prepare and turn their dissertations into books; we went around the room discussing our topics and one history student made a crack about how “relevant” mine would be in DC. Rather than finding ways to demonstrate the value of a humanistic and historical approach to contemporary issues, some historians seem to blame political science and IR for sucking up all the attention (and student interest).
Likewise, data scientists are rightly tired of inadequate statistical models and badly interpreted findings. But what many of them seem to miss is that this is not a problem of stupidity: it is over-confidence, something data science tends to exhibit. I also sense a bit of frustration that political scientists are still seen as the expert on…politics despite our lack of cutting edge programming skills. This could be solved by closer collaborations between data scientists and subject matter experts, something that is often lacking.
It’s almost like political science and IR have become the Other to our critics, alleviating the need for any deeper reflection. As Kavafy ended his poem: “those people were a kind of solution.”
So what should be done?
Well, I am just finishing a fellowship at Edinburgh University’s Institute for Advanced Studies in the Humanities (IASH), which was funded by the Centre for the Study of Islam in the Contemporary World. It includes fellows from across the humanities, as well as the social and natural sciences. Part of the fellowship is a “work in progress” talk, which I gave last week. The empirical subject was my new work using social network analysis to study international religious politics, but the broader theme was my ongoing effort to test concepts from the humanities using quantitative social science methods.
I was unsure about the reaction. I didn’t know if the crowd of humanities scholars would react hostilely to me as an interloper. Instead, it was an incredibly fruitful discussion. There were tough questions and critiques, but they were in the spirit of collaboration and community. They recognized that I valued their disciplines, and they did not see the fact that I drew on theirs and mixed it with others (i.e., my lack of discipline) as a problem.
In this context, interdisciplinary meant each side listened to and learned from the other, rather than one asserting superiority and territoriality. It’d be nice if that attitude spread outside IASH.
After months, and perhaps years, of cajoling and haranguing the Hayseed Scholar, friend of the pod (episode14) Matt McDonald finally convinced Brent to turn the tables and become a guest on the podcast.
Matt interviewed Brent at the end of the International Studies Association conference in Montreal, in Matt’s hotel room.
Over a few beers and with much good cheer, they chat about Brent’s growing up in Iowa, attending Chicago Bears games as a kid, having two teachers as parents, and how golf shaped his college decision-making. They discuss Brent’s journey through graduate school, the PhD, and his positions at the University of Kansas and now the University of Utah.
Often pounding the table like some 1930s-era dictator, Brent talks about what the tenure process was like for him at KU, the difficult (but also life-changing) move to Utah, walking with Chase pups for all kinds of reasons, how he approaches writing, and how he unwinds and recharges by going back to Iowa and seeing his family.
Matt and Brent first connected in 2010 when Brent reached out to Matt about his IPS article. That leads to a discussion about how and why Brent sent those complimentary emails to scholars.
A number of F-bombs were dropped. Razzing of Jelena Subotic, Tony Lang, and Chris Agius ensued. Friend of the pod and special guest Cian O’Driscoll made an appearance towards the end of the conversation. It’s a whirlwind discussion, and one Brent remains self-conscious about. But it was also a rewarding experience.
Like many, I woke up in shock at the massive earthquake that struck Turkey and Syria. The earthquake, centered in Gaziantep, has killed 3,000 as of Monday afternoon devastated southeast Turkey and northern Syria. In addition to Gaziantep, other affected Turkish cities were Sanliurfa and Diyarbakir [Note-these aren’t the proper spellings as I can’t figure out how to insert Turkish characters].
Any destruction and death on this scale is a tragedy, but the earthquake followed a string of other problems for the region. Turkey’s southeast was long marginalized, and the site of an insurgency by its Kurdish population. This seemed like it may change when the Justice and Development Party (AKP) came to power in Turkey in 2002; the AKP invested in the southeast’s economy and made overtures to the Kurds.
It seemed particularly unfair that this region should suffer further.
When I first visited Gaziantep (also known as Antep), in 2009, it was booming. Expanded relations between Turkey and Syria led to a rise in Syrian tourism, from which Antep–on the border–benefited. New construction projects dotted the city and the local officials and civic groups I met with were full of pride and optimism. Nearby Sanliurfa (or Urfa), was quieter but still vibrant, attracting tourists to its many holy sites.
This did not last, however. As the Arab Spring spiraled into civi war in Syria, this region of Turkey absorbed many of the refugees fleeing the conflict. The resulting social and economic strain reversed some of this progress. Meanwhile, the AKP’s Erdogan slid further and further into authoritarianism, while the Kurdish conflict broke out again. And the bordering region of Syria–centered on the city of Aleppo–was devastated by the civil war.
So it seemed particularly unfair that this region should suffer further. Given Erdogan’s administrative and economic struggles, and the Syrian government’s lack of concern for its citizens, I’m skeptical that they will rebuild this area.
When I read the news this morning I thought I should say something. I try to avoid Facebook, and have increasingly avoided Twitter since Musk’s takeover, so the usual post on those sites wasn’t going to happen. I have this platform, but it felt lame to write a blog post that just says “how horrible.”
Is it a problem to write about how horrible a disaster is if I have nothing helpful to contribute?
I tried to think of some analytical spin on this. But it didn’t feel right. Should we really take a tragedy and use it to highlight our research? It would be one thing if I studied post-disaster reconstruction, but nothing I work on would really contribute to the response to this disaster.
At the same time, “thoughts and prayers” has come under fire, at least in the United States. This tends to be how conservatives respond to mass shootings, instead of taking action to prevent them. Does that extend to international relations? Is it a problem to write about how horrible a disaster is if I have nothing helpful to contribute?
Maybe.
I’d say definitely if I used this post to talk about how this disaster affected me (i.e. “I hope that kebab place I liked survived). And anytime a Westerner writes about the tragedy and promise of the Middle East it comes off a bit Orientalist. But maybe there is a way to just express solidarity, and maybe that’s better than trying to force an analysis onto a tragedy.
At the least, here is a useful article listing the organizations currently on the ground in Turkey and Syria.
FreshRSS 