 My co-panelists have been giving me a bit of a hard time because I actually have a PowerPoint. But as you'll see, I think I have many of the same insights that we've already heard. So even though we're from different disciplines, I think we're kind of converging on at least what are some of the challenges of making our different disciplines work together. So I really kind of welcome the chance to give a few insights from my own perspective as a political scientist. I'm actually a daughter of a sociologist, and I'm married to an economist. So I'm kind of always thinking about these different issues and when it does, and it doesn't work very well. So what I thought I'd do is just talk briefly first about some of the challenges I think political scientists sometimes face in working in multidisciplinary environments. As Rachel mentioned, I've worked both at wider, where it's majority development economists, and out of pre-war, it's about 500 ag economists. And myself is a political scientist. So some of the challenges of being kind of a minority, what I'm calling a minority political scientist. And then just some brief insights that very much complement what the other panelists have said about when can you get multidisciplinary work to happen based on my own experience working in multidisciplinary teams or leading multidisciplinary projects. So focusing on the first issue is kind of a minority political scientist experience. I mean, some of the challenges that I think we face is first. And I think this is actually faced not just for political scientists, but across different disciplines, but as conflating disciplines with methodologies. And thinking perhaps that if you work on governance issues or political issues that you only use qualitative methods. Or as one of my colleagues calls qualitative blah blah, you do qualitative blah blah, which is not just kind of derisive of qualitative methods, which, as we know, can be quite robust and rigorous. But ignoring that quite a substantial share of political scientists also use quantitative methods. But relatedly, I think we've also seen within political science, we kind of seen a lot of kind of methodological hegemony, particularly with the popularity of experimental work and RCT work. Really starting to crowd out some really interesting and important research questions that are maybe difficult to have your randomized experiments. Or just can't be very easily quantified. And if you look at kind of our flagship journal, which is the American Political Science Review, it's almost uniformly experimental work that you're seeing now. And then I think thirdly is just general ignorance about what the aims of the discipline are. Again, we all face this across our different disciplines. But I think everyone kind of has a view on politics and opinion on politics. And so people think that I can give kind of an esoteric explanation of what's going on in my kind of town county politics, as well as what's kind of going on in the WTO global governance, as well as what's going on in kind of African democratization, which is kind of my main field, African party politics and democratization. And so I think sometimes it's kind of ascribed too much influence to the discipline, which on the plus side, as I've put it kind of the opportunities, a lot of deference. We've heard a lot the last two days about the importance of the role of the state, the importance of bringing politics into the discussion. And so I think often in a multidisciplinary environment, there can be great benefit for political scientists. Secondly, it's kind of notice more and more greater flexibility and engagement and development issues than some of my colleagues who are kind of considered pure political scientists who might just focus on voting or public opinion issues. So I think the ability to say, for example, how does decentralization or local governance structures affect the pattern of urbanization and urban housing markets, or how party regimes affect volatility and agricultural policies? Being able to show how politics or governance affects a particular development outcome has become quite valuable to me. And then thirdly, just pushing me much more towards policy relevance. Of course, we all need to have our theoretical contributions to our discipline. But I think also thinking about how does our work affect the donor community or affect national governments makes us think not just about addressing a gap in the literature, but also what are the issues that are really important to people and to policymakers. So how to make it work. As I said, I'm just going to give a few examples from my own experience. One is very much what Haruna has already mentioned about this issue of language communication. We know we all use different jargon, different terminology. And what I've found is really if you can just provide a concrete example of what you're talking about and how does it differ from what your multidisciplinary team members are talking about, really helps in moving a project forward. So one example that I've had over the last two years with IFPRI is with a USAID project focusing on drivers of food security policy change. Why do certain policy issues get on the policy agenda in some countries and not others, particularly looking at fertilizer subsidies? Why have some countries chosen different designs to their subsidy programs rather than others, et cetera? So our project kind of consists of an array of kind of livelihood specialists, agricultural economists, of course USAID practitioners, and then myself as a political scientist. And when we started doing this research, we said, oh, let's just do a stakeholder mapping. Yes, let's look at the interest groups. And then USAID said, yes, let's look at who are the policy champions. And I said, yes, let's look at who the veto players are. And we realized, are we all actually talking about the same thing? They sound like they could be synonymous. And what we basically did is we wound up taking a kind of what's called a circle of influence graphic. I think Marilyn Grindel at MIT has come up with this just kind of graphic presentation. And this is just an example focusing on Ghana's fertilizer subsidy program. And we were just trying to kind of place the different actors involved in discussions of the fertilizer subsidy rate in Ghana. Who supported it? Who didn't support an increase in the subsidy rate? And who just kind of wanted more technical improvements to the program by having more appropriate fertilizer for agroecological conditions? And when we put this up, we realized that, of course, not all stakeholders are interest groups. Of course, there's poor people who are stakeholders in this policy, but they're not even on our diagram. And then not all interest groups are policy champions. So of course, the donor community is a big interest group, but they're not a champion of the subsidy policy. And then the kind of gray area in the middle was focusing on veto players who are the main decision makers who at the end of the day determine this policy. And then recognizing that not all policy champions are the veto players. So this kind of helped us just disentangle that, well, we were all actually talking about similar things in some regards, but the language actually does make a difference. Secondly, humbly justifying your value added, and I think this again plays on another point that Haroun made about kind of delving into other literatures. I think we've all kind of, so we're sometimes often a little bit derisive of other disciplines. I've been to many, particularly African Studies conferences. We have many different disciplines. And you have kind of political scientists roll their eyes when historians just kind of read their paper word for word. And then you have economists, they get upset that anthropologists engage in this kind of rich description, but no kind of rigorous, quote unquote, hypothesis testing. And then there's also kind of the feeling about economists becoming kind of so obsessed with testing endogeneity that they really might lose sight of what's the bigger topic or issue that they're looking at. So we're all kind of used to this kind of rolling of the eyes at certain instances. But I think it's really important to stay open-minded and self-reflective of your own discipline to gain credibility with other disciplines. And so one example of this was with a UNU wider project that's just actually recently concluded, where we're looking at Africa's emergent middle class and the political economy of the emergent middle class. And of course, a lot of economists have focused on this a lot recently. African Development Bank a few years ago kind of reinvigorated attention to this issue. And then we have many economists, Martin Reveillean, Nancy Birdsall, William Easterly, focusing on how you measure the middle class. And I think what got lost sight of what we realize kind of doing this project is that there's been a huge kind of historical and sociological literature on Africa's middle class back to the 1960s and 70s. So this is not a new phenomenon. There's been a lot written on it already that was kind of ignored by more kind of contemporary research on the topic. But at the same time, there wasn't much on the political science front. And so one of the goals of this work was to kind of show what these different disciplines were showing us, the lessons learned, the importance of those lessons, but what was the value added of applying also a political lens to the work. I think thirdly, avoiding the lowest common denominator. I think that one of the biggest challenges, I think, with multidisciplinary work is that we tend to kind of sacrifice the depth because we're trying to get the breadth from the work. And results in a lot of kind of essays and X fill in whatever the X is, essays in gender, essays in youth, or whatever topic you want to fill in with the X, which kind of concludes usually with the point that context matters. Or I kind of read two days ago about a very large multidisciplinary project where the conclusion was context matters, but only within certain contexts. So you kind of get these kind of somewhat vague conclusions in some cases. And so I think one thing that we learned from a project we recently did on African youth, also a UNU project, was that you really need to have a very clearly defined issue upfront from which a bigger message across all disciplines can be derived, but then giving the space for each discipline to then derive different subsets of issues. So in this project, we had urban anthropologists. We had education specialists, political scientists, sociologists, labor economists, a whole wide range. But we asked them all to focus on what's kind of the conventional wisdom that you're trying to test. Is it about that all African youth are apathetic? Is it that they're all violent and preventive protest? Is it that they could benefit from more of a focus and changes in educational curriculum, more towards vocational education? Is it about having more kind of learnership programs or apprenticeship programs? And so they all kind of started out with these types of conventional wisdoms, and then they were kind of testing them with their own methods drawn on their own literature. So at the end of the day, they could still kind of stay in their comfort zone with their work, but then we could have kind of a bigger message that came out of the work. And then I think, lastly, just being cognizant that we certainly all do have different objectives in our work. And we all have different metrics for gauging, as researchers in particular, our productivity. And we prioritize different publication outlets. So oftentimes, we prioritize our own disciplinary journal, for example, than maybe kind of a development studies outlet. So I think one option is to anticipate kind of a two prong strategy upfront for your research outputs that ensures team building, ensures everyone's kind of working towards a common end. But then without sacrificing personal objectives, particularly on the publication side, and discussing these well in advance with project members, some of the kind of worst projects they've been involved in is when it's kind of a month before completing, when people say, what are we going to do with this research? And everyone has a very different opinion about what they want to do with it, because they all have their checks they need to cross in terms of their own career objectives and publications. So I think, and Francie was just eluding this as well, I mean, I think one of the issues is finding out ways that you don't just have kind of co-authored projects, where you wind up having each person writing their own section of the paper or the book, and then someone else needs to kind of bring it all together and see what the common thread is. But really kind of working more towards kind of co-authored papers and chapters that show how the different disciplines can strengthen each other. So I've put up just a few examples here. And these are, of course, all deriving from you and you wider work, which I guess is appropriate since we're kind of celebrating you and you wider. But one is from Rachel and another colleague, Miguel, a political scientist and economist working together to kind of see what this kind of new wave experimental work in methodology, I mean, what are the strengths and weaknesses of using this particular methodology in terms of deriving insights for good governance and for development economics. Second one, focusing on the political economy of green growth is where political scientists and economists came together to look at what the economic implications of green growth, whether the implications of the green growth agenda that's been quite popular for the past few years, was the political feasibility of actually implementing that agenda and finding that there were quite a few kind of political caveats of having kind of a green growth approach to development. And then thirdly, as part of a project that I think is still ongoing, the development under climate change projected wider, is really bringing together economists and natural scientists to think about policy implications for climate change and for cutting carbon emissions and showing how kind of economic modeling and energy modeling, which have not been brought together often in the past, how they can actually be sequenced and give kind of a bigger bang to the policy advice. So I think, luckily, you and you are very good at promoting this with the caveat of when they have the right balance of staff and they can draw on a network that includes all of us as sociologists, political scientists, economists, anthropologists. So I leave it there. Thank you.