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VALERIE HANS: Good morning, everybody. My name's Valerie Hans, a social psychologist by training and a faculty member at the law school here. And I'm co-chair with Dan Leitzinger, who many of you know as head of the Institute for the Social Sciences.
He and I have been co-chairing this year's provost Ideas Panels Committee. And the provost assembles the committee to develop forums at which Cornell social scientists and others could offer their ideas for radical collaboration across the departments. They have colleges and indeed campuses at Cornell University, in turn, the ideas expressed by the panelists at this panel and have the two proceeding ones for going to form the basis for strategic investment within the social sciences and across the social sciences in the next decade.
And so Dan and I, as we start this panel, wanted to make a couple of comments about them and their place, like both of us might think that maybe Emma Provost see that this is really intended to begin the conversation here at Cornell about the best ways to position the social sciences for future excellence not the end of the conversation and to that end, we are going to hear today from 14 panelists, 13 of which we're able to squeeze onto this slide and Mildred Warner, who you will see was accidentally left off, and we apologize for that. But nonetheless, we're going to have her speak. We're going to get her up here. Anyway, where these panels come from are committee, the deans other people gave us suggestions about people who would be in a good position to talk about the theme that we identified for today, which involves policy, planning, translational research, and the social sciences.
So again, we think these individuals represent some of the exciting areas of strength at Cornell that could be the basis for future collaborations and [INAUDIBLE] basis of existing collaborations. But of course, these are only a fraction of the outstanding civil scientists here at Cornell. And on behalf of the committee, we welcome contributions from you, and from others who might have ideas for how to position social sciences in the future. So again, this is the start, not the end of the conversation, and we look forward to hearing from all of you. Ken will now say a few words about the substance of this particular forum.
KEN: So thank you all for coming. This is our third forum [INAUDIBLE] where we identify different areas. We've got a little bit of discussion for faculty also have one on health and related themes.
And last time, some of you were at that one dealt with democracy and equality-- things of that sort. So thank you all for coming. I know it's a very busy time of the year, but I think this is an important task. And we're looking forward to everybody's input on this thing.
Today is in some way a reflection of the kind of things we talked about on our committee. It's a little bit different from the other two, which were more substantively focused. I think in this particular case, we're not talking about structures here. We're talking about ideas that might be infused with a translational component, a public policy component, an intervention component, and so on.
And I think this is an appropriate topic because Cornell is one of the premier land grant universities. We have several departments that have a very large policy component to it. We're talking about policy analysis in management. We're talking about Aim or what used to be Aim now in the business college.
We also have a city and regional planning and so on. So we have a number of-- Bronfenbrenner's Center for Translational Research. So there's a number of organizations or units here on campus I think that serve that particular purpose.
So we've invited a lot of different people here, representing different parts of the university. We think that public policy areas or translational research can be in service, not only to the public but also to the basic social scientists across the university. So we're anxious to hear what people's ideas are.
So what we're done is we've invited a lot of people. Everyone has up to four to five minutes to speak. So I think I've characterized this as kind of speed dating. And then where we're done with everyone-- and we'll have slides that actually do the introductions-- people just come up here, give their little spiel.
And at the end of that at the end of the 14 short discussions, we'll have a more general discussion, related to the topic. So do mark down your ideas or thoughts, and then we'll just proceed right through this very quickly. It's worked in the past. We hope it'll work this time too.
VALERIE HANS: So we'd like to invite this first speaker to come up.
[SIDE CONVERSATION]
NATALIE BAZAROVA: I'm Natalie Bazarova, and I'm in the department of communication. Thank you for inviting me to share my perspectives. And today, I would like to draw on my experience of working on a translational research project called Social Media Test Drive. I will reflect on the steps that have been important in our work and what I think of as doors of opportunity for promoting research practice policy partnerships at Cornell University.
Over the past year or so, the Social Media Lab has been working on feeling a major gap in media literacy and digital education for young people. With the support from the Brunton Brennan Center for Translational Research, and Program for Research in Youth Development and Engagement pride, we'll be developing an educational program that teaches children about appropriate online behavior and media literacy, including lessons on online safety, cyberbullying, and digital literacy. For example, how to identify fake news and credible sources online. What's unique about our program is that our curriculum is offered in an interactive and hands-on manner, using a social media simulator that we call Test Drive-- Social Media Test Drive.
So instead of simply lectured on how to use social media or interacting with strangers on the open internet, youth can learn and practice social media skills in an environment that is realistic but yet completely safe and secure. It is safe and secure because, in Test Drive, children interact with what essentially are bots. They are preprogrammed simulated users that act and respond in a realistic way. Like a novice driver in a driving simulator, children can explore, make mistakes, practice their skills in a way that's safe and empowering.
So right now, we're currently testing this program in several counties in upstate New York. And we've been working with 4H leaders and extension educators to deploy it in other places across the state. There is also an exciting potential for a partnership with the National Media Literacy Organization that would allow us to significantly expand a scope, reach, and sustainability of that project.
So now I would like to draw from this work and highlight several key factors that I think have been really key in taking this project off the ground. So first, organizational structures and incentives that encourage translational work. Second, interface in between researchers and practitioners and third, support of centers, dedicated get to region research policy and practice.
So as was discussed, I believe at the second panel, academics are more about knowing than they are about doing. And I believe there is a need for the organizational structures and incentives that promote and reward public engagement, as well as a need for more educational opportunities to train both researchers and grade your students in doing translational work. There were several structural factors pivotal in our approach.
First, I would say been as a department in college that emphasize knowledge with a public mission, with a public purpose. Second, applying for federal grants, such as NSF, USDA, that may grow the implications of research and real-world impact and priority. And finally, interdisciplinary collaborations that were built around these funded projects.
The second factor is interfacing between researchers and practitioners. Translations requires thinking about dissemination and working with 4H leaders and extension educators has been critical for a dissemination of the Test Drive project. So the whole idea of a social media simulator was actually born out of a discussion between researches and extension educators.
At the last years, youth research of date organized by the Bronfenbrenner Center for Translational Research whereas we envision this platform originally just as an experimental tool around social media experiments. Existential educators brought to our attention a gap in interactive educational tools that would allow children to practice social media skills before they get online on their own. And that dialogue between researchers and practitioners give us an idea of what has become eventually Test Drive. And finally, successful translational research requires support from centers and programs that link research, practice, and policy. And then all our work-- it was the BCTR and pride with whom we found the synergy around advocating for digital citizenship and media literacy skills.
So to summarize, I believe that a successful translational work requires first organizational structures that incentivize community engaged research. Second, interface in between researchers and practitioners to facilitate a two-way research practice dialogue. And third, support of centers dedicated to creation and dissemination of knowledge that matters and makes a meaningful difference in people's lives. Thank you.
[APPLAUSE]
PARFAIT ELOUNDOU-ENYEGUE: OK. I need no introduction. Just kidding, I'm Parfait Eloundou. I'm a Professor of Development Sociology. And I think what I'm going to say it really has nothing to do with what is written there. I thought more about what the purpose of this was, and I just modified my text accordingly.
And so what I want to say at the outset is that I see this panel as being drastically different from the other panel. I mean, whereas the other panels where involved collaboration that is meant to produce research, this is different in the sense that you assume that you have the research. And the goal now is to move it to the next level to take that research and embed it into policy.
And so assuming that is the goal-- that is, to take research and bring into policy-- what are the criteria? What are the factors that we need to be successful at this science policy interface? And so I have identified four main factors, and I try to think about the kinds of radical collaboration that we would need to be able to be successful along these four criteria.
I can also tell you a little bit about the work that our department is doing in that area of translational research, as Dan said earlier. You cited Aim, but the Development Sociology Program is also a program that is very much invested in public policy, especially at the international level. We have faculty who work very extensively with the UN, with Malawi, with Ethiopia, with different countries in a variety of areas, including food, youth, inequality, food production and so forth.
And so this is just, as a way of background-- in terms of just the meat of the criteria that I wanted to discuss, I think in order to be successful in this science policy interface, you need four things. The first is more or less internal validation by colleagues. Suppose you are sort of a good psychologist or sociologist, and you come up with a good research study that suggests that school lunch is a very good way to reduce obesity among children. You can benefit from a conversation with colleagues.
Economists, who would give you a sense of the price tag-- how economically feasible that solution is. You can discuss with cultural anthropologists who would have you think about the cultural acceptability of your programs, and other scientists who may bring to your attention other innovations that can be useful to drive down obesity. And that could actually be more effective than what you have done. So just the first test is within colleagues to see whether your solution makes sense, whether it's going to be received, whether it's economically feasible, and politically feasible.
The second step is the communication, and we've talked quite a bit about this. And I think it's a fundamentally important question. Most of us are not trying to be a good communicator, even though we teach on a daily basis, and we get a chance to prove how bad we are at communicating. And one model in addition to what has been discussed here is the Public's Voice Fellowships, which I think Cornell instituted a couple of years ago. I think it's terminated, but it was a very useful program to get scholars to talk about their research integrated with other research but also with current date events.
And so that, in my view, was a very useful exercise. A third would be a better understanding of the policymaking process. The naive assumption is that you have good ideas, and then you somehow [INAUDIBLE] to a policymaker, who just takes it and runs away with it. That doesn't happen.
You need to understand the policymaking cycle. There are times in the year or in the process-- that policymaking process-- where you can be actually, where you can enter the process and be effective. So that's the first criterion.
The fourth criterion is really a more intense engagement with the policy world so that you can involve them, even in the early stages of research so that you can co-produce the research but also think together about the kind of research that is needed. So there are different levels of engagement and the kinds of collaboration that we need at all these stages are different. And so I'm going to just bring to your attention two events or two things that our department is doing now. One is an internal mapping of our engagement practices.
Different colleagues have been trying on their own to do some kind of public policy engagement. And so what we're doing systematically is have sent a colleague and a communication specialist to just interview each faculty member and to gain intelligence about what they are doing and how have they been able to address their communication problem, their various interfacing parabola. And then we are going to synthesize that evidence and hopefully, share it with everybody who is interested.
The second thing is a person symposium that is being held in two days and is going to bring together people from all over the world, who are going to talk precisely about this interface between science and policy and how these different institutions research, et cetera, have negotiated this interface and what kind of take-home lessons or best practices we can draw from these guests and participants. So you're all invited. Thank you.
[APPLAUSE]
IRENE BLECKER ROSENFIELD: I took my task to be to identify some area of scholarship that is most ripe for bringing all of the different social scientists together to work on the problem. And in thinking about that, one current aspect of modern life and future life just stood out among all the rest, which is because of current and near future developments in robotics and artificial intelligence, we're all going to be richer than we've ever been. The world as a whole is going to be richer. We can produce more goods and services more cheaply than we ever could before, which means we're richer, which ought to be a great thing that we ought to be celebrating.
But I think at the back of many of our minds is this fear that we're going to screw it up somehow. That even though we're richer, it's going to create as many or more problems as the goods that it provides. And when bad things happen, if they're not so bad, we say, oh it's a misfortune. It's really bad, we say, oh, it's a disaster. And we reserve the term tragedy for those things that needen't have happened.
And if we're getting richer and we screw it up somehow, that's just something that needn't have happened. And we've seen a little bit of a pretest of the kinds of problems I'm hinting at at this. That is to say, the expansion of neoliberal capitalism has made us all richer. Milton Friedman was right. Comparative advantage works.
We are richer now than we've ever been, and that's kind of undeniable, even though the Steve Pinker thesis remains controversial. It gets a lot of pushback. So that's been a good thing. But as we see playing out in our politics worldwide, there have been some downsides. We haven't managed that increased wealth that well.
And if we had of tended to it better, we'd live in a better world right now. Whenever I've dealt with this problem with social scientists before, the room quickly divides into two camps that you could call the optimists and the pessimists. The pessimists are people like me who think work really is going to disappear because of our ability to produce goods and services so cheaply. There just won't be enough work to go around, and having a bunch of idle people is not a good thing.
And the pessimists get a lot of pushback from the optimists who say, everybody's always worried about that. And they mentioned the famous examples of blacksmiths that got put out of work or were replaced by all the people working on our cars today. Fine-- hopefully, the optimists will be right, but there's a reasonable chance we ought to prepare for a future in which they're not right-- that there just won't be enough work to go around. And that seems like the kind of job that all of us-- all social scientists-- have something to say about.
Economists, obviously, in terms of thinking about distribution. Capitalism gets an A or A-plus on the production of wealth. What grade you'd give it for distribution, that's probably controversial. Some people would give it a very high grade-- some people, a low grade. But if in fact, work disappears or diminishes on the scale that many anticipate, we've got a more complicated distributional job.
We have to think seriously about guaranteed incomes. If so, what kind do we have, et cetera? How do we keep incentives? Maybe more public sector in employment. How do we manage that effectively?
If this does happen as anticipated, it creates, in all likelihood, more winner take all markets, which is going to increase income inequality even more, which is a great job for our sociologists to help us think through. And then for psychologists, anthropologists, really for every social. If there's one core idea uniting all of the social sciences-- maybe not economics-- but all the others-- and maybe even economics-- is the idea that people don't respond to the stimuli that they encounter. They respond to the meaning that they attach to those stimuli.
And what does it mean to be a part-time worker? What does it mean to be out of work? And thinking about the meaning that people attach to it is going to make all the difference in whether it's a positive thing or a negative thing. So I think there's lots of room here for all the social sciences to come together, talk together about trying to head off a tragedy.
[APPLAUSE]
MIGUEL GOMEZ: Thank you. in the Dyson School, we see three ideas of opportunities for radical collaborations in the areas of economic development, in the areas of environmental resource, and energy economics, and in the idea of the economics of food systems. And I talked to several colleagues, and we identified four things or area that are opportunities for radical collaboration.
One is global food insecurity. We know that in spite of all the environmental challenges that climate change is being in, we have no food to feed our growing population. Problem is that our distribution system is failing to provide adequate and healthy diets to everybody-- both in developing and developed countries.
So how can we fix the post-harvest food distribution system to eliminate food insecurity locally, domestically, and globally. That was the first one. The second is the interface between the food system and the environment.
Society, as a whole, is demanding better environmental performance of the food system from farm to table. And at the same time, agriculture and the food system faces more and more limited resources from water to land to labor. So the key question here will be, how can we design resilient food supply chains, food systems that at the same time, we achieve environmental goals and society goals.
The third topic is the issue of a very fast urbanization in developing countries. These warrants careful examination of the various aspects, including economical, political, and social phenomena. So how can we fix emerging problems resulting from urbanization related to environmental pollution, traffic congestion, migrant workers, infrastructure investment, and housing market? And the fourth topic is related to the opportunity that advisors in computational sciences are given us a social scientists to understand to use big data to develop more ways that integrate natural systems and the behaviors of humans.
So for example, there is a big push for citizen science. One of the problem with citizen science is that there is a natural bias in the places, for example, where birdwatchers go to observe bird populations. So our department is working with computer science to develop agent-based and to develop systems that allow us to have an unbiased observational bird populations all around the world, for example. So these are the four topics that we see in the Dyson School that are important. Very, very strong involvement with our Cals college with engineering, and with behavioral sciences.
[APPLAUSE]
JON KLEINBERG: All right, thanks very much for the invitation to come speak here. So I'm John Klienberg. I'm from the Computer Science and Information Science department.
So I'm in part here I guess representing the interaction of social scientists with a lot of questions that have been arising from computing and from technology. I think this is an area actually in which Cornell has a long and very successful history. And there's been a lot of engagement on both sides of this interaction and a number of things that we can point to over the past two decades, certainly. The creation of the Information Science Department, which had a huge amount of influence from communication, from science and technology studies, from economics, from sociology, psychology, the Johnson School Linguistics, and a number of other areas. And so I think that's only just because of the social science side of the interaction on that.
And then also I think some of the educational initiatives, some of the research initiatives, I've certainly benefitted enormously. Personally, David Easly, who's in the back row, for example, and I created the undergrad networks course in 2007, which I think was also trying to blend some of this technical and social. So both on the institutional, on the research, and on the educational fronts.
There's been a lot of interesting things going on on campus, and I certainly hope that we carry this interaction forward. I think one thing that's interesting-- think about the interface between the social sciences and computing, in particular, is that there have always been this tension in computer science between two basic forces. In some sense, two basic views of what computer science is as a field.
One is computing as an enabler of human capabilities and human potential. So this is the view that says if we create platforms, like Facebook, like Twitter, like eBay, then it'll be able to bring people together. It will be able to amplify what they're able to do with the help of technology. The other big theme in computer science is the idea of automating activities that we think of as human. And this idea of automation is not just about bringing people together to work on problems, but it's about taking routine activities that human beings have always done on their own and thinking about ways of automating them through creative use of technology.
And in this dimension, I think there are a lot of new developments happening right now in the automation theme, where I think there's a lot of potential for engagement with the social sciences because what we're seeing is the introduction of algorithms to make decisions in a lot of settings, where those decisions have traditionally been the province of human beings and human experts. So I'm thinking of settings like employment, education, finance, criminal justice, and many other settings where the traditional template has been that in individual human experts, or a collection of human experts, evaluate situations using their domain knowledge, and they make extremely consequential decisions. And the question has arisen, can we use algorithms to help with this?
Now I think that's going to be a conversation that's going to really have to involve people on the technology side and people on the computer science side. It comes with a large number of risks. The question, where are algorithms appropriate in these situations? These are decisions that impact people's lives significantly.
Second, when we go to design algorithms for these settings, we need to formalize what question it is that we're solving. And I think a lot of these settings-- the decisions exist in this state of semi-formalized and ambiguity. When I make a decision on a particular case, I don't actually have an exhaustive first principals list of all the criteria that I'm considering. If we're going to introduce an algorithm, we're going to have to routinized that. We have to systematize that.
And in the process, we may make decisions that didn't actually reflect the informal practice that we actually had in mind. And third, the introduction of algorithms can have consequences that we don't necessarily intend. If we change a very complicated system, we may do things that we weren't expecting.
Certainly, to think of an example, the introduction of algorithms into the political discourse on social media, although it's been the subject of a lot of investigation over the past 10 years. It's been very hard to predict each new twist and turn in that storyline. I mention these risks because they're so salient, but I think there are also a lot of opportunities here.
In the end, human beings make lots of errors in their decisions. There's a lot of inefficiency in the system. There's a lot of bias and discrimination that creeps into our decision making. In principle, these are the kinds of things that algorithms may be able to help with.
Algorithms are, in fact, good at making predictions from past historical data quite accurately. Algorithms have no a priori interest in making biased or discriminatory decisions, but they come with the risk that if they're trained on historical data that contains the traces of a lot of bias and discrimination, there's the danger that they'll build us into them all.
And finally-- and I think a further use of optimism is the introduction of algorithms does not have to be an all or nothing decision. It's not about replacing people with algorithms. It's really about finding the way in which these two sides can be brought together and using insights in the social sciences and the behavioral sciences and how, for example, to present information to human decision makers in a way that, ideally, we can actually get the best of both worlds-- leveraging the strengths that humans bring to the problem and the strengths algorithms bring to the problem. So it is a huge opportunity for this kind of conversation, and it's really going to involve I think researchers and students who bring perspectives from both areas. Thanks.
[APPLAUSE]
BRUSE LEWENSTEIN: Thank you. So I'm Bruce Lewinstein. And the label says, I'm from communication and from science and technology studies, which are in two separate colleges.
There are times when I feel like the best way to do radical collaboration is just to do it yourself and just be in two places at once. The more optimistic way of looking at that is that we already have a culture at Cornell that lets us cross boundaries very easily, and I want to take advantage of that. What I actually want to do today is question our topic of policy planning and translational research. To some, that means doing research on critical policy and planning issues-- doing research that's the boundary of foundational and application.
In the biomedical realm, where the term translational research really developed, it's sometimes called bench to bedside research. The point is to promote research that focuses on solving real problems in the real world, rather than research aimed at fundamental understanding of how the natural construct of their social worlds operate. But I think a key challenge for translational research is the research practice boundary itself. What kind of translation works? Is it about choosing the right problem?
Is it about setting different standards of proof, better communicating to research results? Turns out, we might not know. Turns out we need research on translation itself. We have lots of opportunities on campus, obviously. We have the extension system throughout the state-supported side of Cornell.
We have a risk communication community that crosses multiple colleges. We have a number of very active and superb science communicators that are natural communicators in many departments and research centers. All of these people engage with diverse audiences. And through collaboration with them, we can learn much more about their processes and products.
But perhaps most important, we can ask, is translation even the right word to be using? I work mostly on public communication of science and technology, where scientists often talk about disseminating their work or translating it for the general public. They-- or that I really should say we-- are so conditioned to believe in facts and the value of evidence that we just assume that if people knew more, that if more people knew about the reliable knowledge that scientists, including social scientists, produce, then everything, whatever everything is, would be better.
But research in the last generation has shown that more information isn't the issue. People with higher levels of science literacy, for example, are sometimes more likely to question the value of scientific evidence. Perhaps because they understand some of the uncertainties associated with scientific findings. But notice that I said, perhaps. We don't actually know why that happens.
Or consider that people's judgments about risk on specific topics, like climate change or gun control, may vary dramatically from their overall science knowledge, and those variations correlate extremely well with partisan differences. The partisanship isn't always a predictor. Assessment of risks associated with fluoridation or GM foods or synthetic beef hormones or nanotechnologies, they don't show a partisan bias.
So some evidence suggests the translation, without considering at least one kind of social value political identification, doesn't work, but other evidence isn't so clear. We need to know more about what factors are relevant to how people use information, as it moves from research to practice. All of this raises another question.
Does knowledge change as it moves when it is expressed in different contexts? I gave the spoiler alert in my abstract. I think so. Substantial research over the last generation questions the linear model of knowledge production in which we do lab or field work on foundational issues, and we publish it. That's when we call it science.
And then, only then, do we push it out to translational or policy or planning in other public settings. But instead, there's a lot of research from rhetorics, science studies, public opinion, communication, and other fields that suggest that knowledge exists only insofar as it is expressed. And so every expression in different form is in fact, creating new and different knowledge.
The research paper literally says something different about the world than a policy paper or a planning paper. Translation is the wrong term. I'm not sure what the right term is-- knowledge production, knowledge expression, knowledge development. But most of the work I'm drawing on has been about knowledge development in what we traditionally call college knowledge development. How did that sound?
In what we usually call the hard sciences, how is public communication different for economics or sociology, or communication or political science or psychology or any of the other social sciences? What formats work? What do we even mean by work? How do we evaluate what works-- and so on? I think to be a leader in social science research on public policy planning and knowledge development research, we need to commit resources across the university to how we connect research and practice. Thank you.
[APPLAUSE]
MICHAEL LOVENHEIM: Good morning. I'm Mike Lovenheim from Pam. I actually find it somewhat difficult to prepare my remarks for this panel, as many of you may have found the same thing.
So the natural inclination, when you ask academics, where should we invest in. Is to say me-- whatever I do. And I'm very happy to hook myself up to the gravy train, as I'm sure all of you are. But I think ultimately, would be unproductive, at this point, for the university to be picking topical winners and losers.
I also think it's hard not to get distracted by some of the arcane terminology that is being thrown around, like radical collaboration. I don't think any of us knows what that means. I certainly don't. So rather than argue you for investing in my own work or parsing out exactly what all of the terminology means, I want to articulate a more specific vision of what I think could be done to support the social sciences in terms of the infrastructure for research.
And my motivation for these ideas are kind of twofold. The first is that in my view, the returns to interdisciplinary social science is rather low, and this is particularly true, I think, for junior faculty. And if we're going to make social science as great as it can be at Cornell, we need to invest in junior faculty and retain good junior faculty. And the way to do that isn't to be doing lots of interdisciplinary social science.
And the second motivation is that-- Tom Pepinsky said this last week-- that a lot of interdisciplinary social science is already happening at Cornell. And so people are going to do it when it makes sense to do. And a lot of people have talked about that today. I don't think we need special incentives or added incentives to do that.
People are going to do it when it makes sense to do it. So I think a more productive use of resources would be to invest in research centers that are multidisciplinary, rather than interdisciplinary, insofar as they're allowing for very high quality, disciplinary research, across multiple disciplines. And so such centers, as I imagine them, would have several defining characteristics.
First, they would-- as I just said-- involve researchers from multiple disciplines in a way that would allow them to do disciplinary research of the highest quality. And that could also lead to interdisciplinary research but can use any specific reason to force that upon us. Second, they would exploit and build upon Cornell's comparative advantages. We are good at certain things, and we are relatively better at certain things than other universities.
ECON 101-- those are the things we should be investing in. And I think I'm an economist, so I think that's important. And it makes a lot of sense, given that there are binding resource constraints.
Third, there would be an explicit plan for the centers on how to make them self-sufficient financially within a set amount of time, for example, five years or so. And I think it's very important that something like this that these be used to grow the size of the pie and not just be used to redivide the pie. If we're going to have these be engines of growth in the social sciences, they need to actually be growing the social sciences.
Along similar lines are defunding for PhD students, postdoctoral researchers, maybe new faculty lines. Again, growing the size of the pie to be able to support the social sciences. And then last, there'd be a translational component, which I think would follow naturally, in many ways, from a lot of the other components of this.
So what are some examples? And the idea here is the specific centers wouldn't be up to someone like me. People could determine this for themselves.
But one example would be a New York state data repository for administrative data. So bringing together administrative data sets from throughout the state that could support social science research across multiple disciplines. And I can imagine almost everyone in this room benefiting from such a center. We have a great data infrastructure here through [? Sizor in Craddick. ?] This would also help support them.
Another idea would be a center on rural populations in communities. Cornell is uniquely situated in a rural community. There's a lot of really important issues going on with rural populations that Dan knows infinitely more than I do about. But bringing together academics and business leaders and policymakers to talk about these issues and build strength in this important area that again, I think we have a comparative advantage in. And so funding for some something like this, initially so you can think about this as like a seed funding for the university, with an eventual plan to be self-sufficient, could be determined through competitive process that would involve both internal and external reviewers.
Peer-review something I think we all kind of buy into at some point, to some degree. And I think these centers would provide new and needed resources for researchers across multiple disciplines that would bolster the social sciences through the production of strong disciplinary research. And if the university really wants to find a productive way to invest in the social sciences, I think the direction we should go. Thanks.
[APPLAUSE]
HIROKAZU MIYAZAKI: Good morning. I'm Hiro Miyazaki. I am the Director of the Mario Einaudi Center for International Studies. I'm also Professor of Anthropology in College of Arts and Sciences.
So I'd like to talk a bit about what we do at the center and its implications for this panel. So globalization, as you all know, has created an interconnected world in which visions and values arising from all kinds of things from historical, cultural, religious, linguistic, and ideological differences collide and compete. Finding solutions to global issues in this context requires a deep understanding of these diverse visions and values. At the same time, many of the global issues we confront today, from climate change to cybersecurity, are highly technical. Finding effective solutions to these sociotechnical problems demands substantive costs, disciplinary collaboration.
The Einaudi Center has set up all the infrastructures and funding streams to enhance our capacity to serve as a collaborative space in which experts on technical issues and experts on international affairs, cultures, languages, and regions of the world can work together. Saying this is easy but doing it is really difficult, partly because we are not truly global yet. Key challenges are languages and people. So when we talk about collaboration, we don't necessarily always talk about global collaboration.
And some of these global issues actually require transnational collaboration. That means we need to engage influential scholars and union leaders from all parts of the regions in our collaborative research. And some of those people do not speak English. And even if they speak English, but they do not have time to publish and engage in English speaking conversations.
Second, when we talk about impact, we tend to talk about the national impact, but we don't necessarily talk about global impact. In order to enhance the global impact of research, we need to actually develop a capacity for multilingual translational research. So here, a translation has a double meaning.
Finally, not all of us are good at collaboration. Some of you may be geniuses, but you may not be collaborative geniuses. So I propose that we invest all our resources in faculty and international partnerships and infrastructures for multi-lingual communication to enhance the global impact of what we do. Thank you.
[APPLAUSE]
SUZANNE METTLER: Good morning. I'm Suzanne Mettler. As one of the original land grant universities, Cornell was established at a time of extreme crisis in American history. The nation was in the midst of the Civil War, when President Abraham Lincoln signed into law the Moral Act in 1862. It commenced a new approach to higher education that united the traditional study of the liberal arts and sciences with practical training in fields that would help grow the economy.
The spirit of the law was democratizing, aiming to bring more people into the ranks of the highly educated and endowing them with training that would help foster regional and national development. In 1865, Ezra Cornell and AD White joined their vision with that model to create a university that aimed-- as Cornell put it-- to do the greatest good. We come together now at another pivotal time in American history that we do not face secession of one part of the country. The United States is deeply divided.
Partisan polarization has reached levels not seen in a century. It is paired with profound social divisions. Economic inequality has been growing for decades. Racism and nativism, each with its long history in American society, have once again been sanctioned by public officials in a manner that it seemed, in recent decades, to be on the wane. And scholars who study the deterioration of democracy around the world find that these conditions make a nation vulnerable.
Recent years have also given rise to anti-intellectualism-- the antagonism against experts and elites. We are a university of experts situated in a region that has suffered long-term declines in opportunities and stagnating wages and workplace benefits for many people. We can easily seem out of touch with the needs and concerns of those who live in upstate New York, in its towns, rural areas, and rust belt cities.
So how can we foster collaboration in the social sciences in ways that accentuates and develops our greatest strengths and responds to great needs in American society and the region in which we dwell? I do think that's a question. I propose that we need to coordinate our strengths in public policy and in inequality and democracy to promote the greater good. None of these are new areas for us to think about or build in.
And in terms of public policy, I served on the provost committee several years ago to consider how Cornell's strengths could be coordinated, aggregated, and showcased. I still think that's an important goal.
There are numerous hubs of excellence in public policy around campus, but they are underappreciated and underutilized because of their separation, on inequality, the Center for the Study of Inequality, directed by Kim [? Wheaton, ?] has done an excellent job of coordinating expertise in this area on campus, and it's deserving of more prominence and to be part of broader efforts. Concerns about democracy are more concentrated than these other topics, featured mostly in the government department. But certainly shared, by many others around campus. We have scholars, who are experts in the decline of democracy and the rise of authoritarianism around the world and several of us, who study democracy, here in the United States.
I think that all three of these areas could be showcased and utilized in efforts that are rooted in the original public-serving, outward-looking focus of Cornell, while also building on our strength and visibility in the social sciences. Here in upstate New York, Cornell could contribute policy expertise to thinking about how to develop the regional economy, exploring new ways to create job opportunities and to promote more college going in the pursuit of advanced training. We could offer practical training to local public officials from across the region, who are on the front lines of democratic practice. And we could facilitate conversations across social and political divides, providing opportunities for people to listen to each other and for us to listen might be valuable in and of itself.
By drawing on our collective strengths in the study of public policy, inequality, and democracy, we could advance the social sciences at Cornell. And by reconnecting to the universities land grant mission, advance the greater good. Thank you.
[APPLAUSE]
KELLY MUSICK: Thank you. Thanks, Dean and Valerie about organizing these panels today. I'm Kelly Musick in policy analysis and management and full disclosure-- I'm also Director of the Cornell Population Center. Some of my remarks will be relevant there.
So I have four points I'd like to make that have been important in my thinking about the next steps in collaboration around the engaged social sciences. And maybe I'll say, first, before I launch in that I've thought a little bit about the term engagement, as we all have. So I think that most of our work-- if not all of our work in the social sciences-- is engaged in the social world, how better to understand it.
Ultimately, how to make this social world a better place. And so I guess it's another step toward public engagement-- sort of as Bruce's comment suggested maybe-- it's a big step toward public engagement. And I think there's a growing call for more work on the part of the sciences-- social sciences, sciences more broadly-- to translate or to pass on knowledge and our knowledge in the service of public good So it's an important set of points to think about. So on to my four points.
First, I just want to say that I think we have critical areas of interdisciplinary strength to build on and engage social sciences at Cornell. And many of my points really have been made by others, or they intersect with points that have been made on other panels like previous speakers today. I see work at the intersection of population, social policy, and inequality as one area of strength that spans the social sciences units across campus. I'm just back last week from the Population Association of America meetings, where we had 49 faculty post-doc and student affiliates participating, presenting work on pressing social issues-- so issues at the intersection of population and social policy and inequality on fragile families and child being, the impact of the prison boom on families and communities, gender equality at home and at work, child health and later life outcomes, immigration enforcement and deportation, and the spatial dimensions of an inequality.
Second, I think we have structures in place that we can further leverage to promote crossdisciplinary collaboration and engage social science. For example, the ISS, the Cornell population center, the Bronfenbrenner center for Transitional research, the Center for the Study of Inequality. These were all named in the recent internal structures report of the social sciences.
These centers foster ties across units and disciplines, offer support for grant getting, trained students and post-docs, and disseminate research to the broader public. These centers already collaborate on many initiatives, and there is room to do more. And I really appreciated Mike's ideas here on data and world poverty.
Third, we can further excellence by embracing what's distinctive about Cornell's social sciences. These points have been mentioned by others. The external committee that reviewed the social sciences at Cornell highlighted the field system, multidisciplinary units, and our long history of public engagement as powerful seeds for credit for cutting-edge problem-focused research. The sciences are moving in the direction of multidisciplinary problem-centered research and leveraging what we have on campus could put a step ahead in this regard. So finally and relatedly, the external committee recommended a public policy initiative that would provide a visible institutional home for Cornell's policy scholars, a policy initiative has potential to bridge disciplinary and multi-disciplinary units so bridge the land grant and the endowed colleges.
And play on Cornell's strengths-- distinctive strengths in engagement and multi-disciplinary. I'd add two distinctive strengths at the intersection of population, social policy, and inequality, Suzanne's comments policy, inequality, and democracy.
Many ideas big and small, have been talked about in the 10 years that I've been at Cornell-- new ideas are percolating now. I think ideas about a policy initiative have been raised in all of the three ideas panels that I've attended. So maybe this is the right time to move forward with some of those ideas. Thank you.
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JED STIGLLITZ: Hi, my name is Joe Stiglitz. Thanks to Valerie and Dan for organizing this and for inviting me to participate. We were asked to think about what makes a successful translational-- and I use that term loosely [INAUDIBLE]. Translational research collaboration-- well, that's the big question. Like many others, I've decided to break that question into a larger number of smaller questions.
So in answering those markers is what makes successful research collaboration? To me, it has three elements. First, it combines faculty with complementary skills. Second, focuses on a well-defined problem, where, third, research might meaningfully affect policy choices or lived realities. So this means, first, that successful collaborations most likely combine social science faculty with non-social science faculty, work [INAUDIBLE] from different disciplines within the social sciences.
Those are the collaborations that promise the greatest complementarities. It also means, second, that the research will tend to focus on a well-defined problem. An example of a well-defined problem is a rising murder rate, increasing traffic jams, declining voter turnout, child obesity, somebody mentioned. Examples of less well-defined problems are decreasing human well-being or happiness, perhaps welfare, or perhaps the loss of dignity in the workplace. Those problems I would submit are not very well defined.
Finally, it means that, third, that the problem might plausibly yield to new information or research. Many problems of academic interest just cut too broadly or were not plausibly affected by any particular collaboration. For instance, the problem of rising sea levels is well-defined, but I would submit not the right place for transmissional collaborations because it's not clear how that problem would yield to any new research.
So what are some successful collaborations? Let me give you some examples. One example is, here at Cornell, one between the law school, Pam, and communications. It investigated the effect of graphic warning labels on the weight of tobacco use. So many countries have really grotesque pictures on cigarette labels, on cigarette packages that here we don't have that. We have a sort of fine print approach to warnings on the dangers to your health of smoking.
And [INAUDIBLE] in 2011, the FDA issued a rule that said now cigarette companies, you have to use these graphic labels like, in many other countries. In the DC circuit in 2012, set aside that rule on the grounds that the government had not provided sufficient evidence showing that those levels actually decrease likelihood of smoking or tobacco use, and that they therefore impermissibly burdened first amendment rights. So the evidence produced by that collaboration, which focuses on just that question, we're very plausibly effect the legal viability of this kind of important regulation. Though it has stalled for the moment, in the future, it's very likely that that kind of research could be very important.
Another example of a collaboration that was funded by another university was, again, [INAUDIBLE] with law professors and social scientists. They developed a new and intuitively tracked measure of the partisan skew what is known as gerrymandering, and the lack of such a measure had prevented the Supreme Court in earlier efforts from pursuing claims of unconstitutional partisan gerrymandering. The Supreme Court is currently considering a case in which in which the lower courts successfully heard a claim of unconstitutional partisan gerrymandering for the first time.
So with these efforts, first, combined people with very different skills but common interests, focus on a problem is well-defined, and plausibly would yield to new research. So my comments naturally focus on the interface between law and social science. That's a good place to start. Not only because that's the area that I know best but also because the viability of litigation or regulatory efforts often turns on the quality of social science evidence that can be produced.
These are also areas that tend to satisfy the second two criteria I mentioned. So these are areas that tend to be well-defined. And because they're the subject of regulation or litigation, they tend to be tractable. But there are other areas where you have these three components.
For instance, the rising sea levels-- I assume it may not be a suitable problem for collaboration. Understanding how people consume scientific findings about global warming, how they incorporate those findings into their preexisting views would be a very nice and important area to pursue in a collaboration between scientists and social scientists. Thanks.
[APPLAUSE]
LAURA TACH: All right. Good morning, everyone. Looking out at all these faces and having flashbacks to like early teaching times, which maybe some of you are still living, but slightly less bleary-eyed than the undergraduate. So that's good.
So I'm going to spend a little bit of time today talking about structures at the ideas panel, which it seems like other people are doing as well. But I am trained as a sociologist. So for me to think about fostering ideas independently from the structures that create them is like almost impossible for me to do. Karl Marx would be so proud.
OK, that's my one joke or today. So I want to spend my time advocating for a cross college public policy initiative. And I'll make three points about how this would elevate the existing work that's already happening at Cornell, help foster new collaboration, and also help enhance some of our external visibility.
First, on the first point, elevating the existing work, I think a lot of people have mentioned today and many of the other panels. It's become clear that there's a lot of really exciting interdisciplinary work that's happening, that's very engaged, very policy relevant, and that's an area of strength that we have. In my department, we live this every day. So what's the problem then?
To me, it keeps coming back to this quote that we've heard on the other panel and in other and the other aspects of this review, which is the whole is less than the sum of its parts. And to me, that's not so much about the quality of the individual parts. It sounds like that is going quite well. But rather, how it all aggregates together.
And to me, that's kind of a visibility problem-- an internal visibility problem and an external one. Internally, we don't have a structure for pulling together a cross college structure for are pulling together all of the publicly engaged social science research that's already happening on campus. These panels have been actually really exciting to attend for me because I've learned about a lot of the really great work that's going on, and it shouldn't have had to wait until this for that to be happening. I think many of us probably share that same sentiment.
Beyond just being exposed to the ideas of others in these kinds of settings, not doing this across colleges hampers our ability to learn about new ideas, about data, funding sources, policy connections that other people on campus have. As individuals, we try, and we try valiantly in the context of our own work or an individual project. But individuals alone and those individual efforts can't really solve what I essentially see as a broader structural problem.
So a cross college policy initiative that combines both the endowed and the contact sides of the university together would help curate this existing work on campus. If we don't know about it and can't develop a shared identity around it, we can't expect others external to the university to do so either. Beyond that, the visibility of existing work on campus, new centers like this could help seed research in areas of policy relevant strength with the university, like Mike mentioned, around population dynamics, information science, quality, health, justice, a lot of the topics that have been discussed with these panels.
It can also help coalesce around the data front as well in terms of coordinating access to administrative data and other data sources, training personnel, and I really see that as something that could complement and amplify the existing work of other affiliated centers, hoping to increase their policy relevance via communication, relationship building, a lot of the skills that Parfait and Natalie mentioned at the very beginning. But for me, the quote about the whole being less than the sum of its parts is also an external visibility and a reputational issue too. And this is something that I think a broader initiative could help them support as well.
Many of us engage with policy or with the public on our own for our own individual projects or sometimes for a civic center or department. But again, those do not add up together to a broader vision of public policy at Cornell that politicians, that policymakers, that the community can kind of gather around. I think there are two things that are crucial for supporting that more external-facing aspect.
One is I would call for some support for kind of the intermediary activities and people that it takes to do some of that external-facing work, as Jamila Michener mentioned at the last panel, and Natalie mentioned again this morning, we're really good at knowing as faculty and not doing as much. There are people who are good at the doing side, and that are good at doing both.
And so one example that I'll flag here, because she's in the room, is Elizabeth [? Dei ?] is a postdoctoral fellow at the BCTR. She helped us do a big event in Albany a couple of weeks ago that included faculty from CALS, from Human Ecology, and from arts and sciences around a research briefing for legislators and their staff around issues about vulnerable families in the state of New York. She brought her expertise from working in DC and her background as a PhD, and someone who actually does research on how policymakers use evidence to bring together an event like this.
It wouldn't have happened if just all the faculty in the room were like wanting to do this in their spare time. So intermediaries are important. They're these kinds of things that exist external to the university. We need them kind of internally as well and to do more research on how that works best, as Bruce mentioned.
Did you put the stop already? Not yet? OK, I was like, is someone flagging me down yet?
So then I have time for my final point, which-- oh, now, you're putting it up. OK, my final point that doesn't come up yet today, but I feel like I have to say it. As probably the most recently tenured person in the room, I can say I think we need to have some frank conversations about how to incorporate this kind of policy and engaged work in the tenure and promotion process.
We've been doing a lot on the front end around engage Cornell. Our students are asking for it. It's part of our mission.
But the conversation on the back end is less developed. So I'll just leave that there for now. But I also finally want to say that this isn't an either/or proposition. The engaged piece and the research piece can be synergistic. It isn't always, but it can be when it's at its best.
We have models for how to do that well around the university and nationally. And we need to elevate them and learn from them. And so that's why I'm really excited that our incoming interim dean, Rachel Dunifon just was awarded a really big inaugural grant from the William C. Grant Foundation that's called the Institutional Challenge Grant that is challenging universities to think about how to do just that. So I'll stop there.
[APPLAUSE]
MILDRED WARNER: Hi, I'm Mildred Warner. I'm from the Department of City and Regional Planning in the College of Art Architecture and Planning. I feel kind of like a contestant on American Idol-- sing for five minutes and then maybe you'll vote on us.
So I chose a topic that I thought would be embracing for all of us, and I called it urban intersections and regional equity. Notice I didn't say any inequality I said equity. Because I think engaged research has a challenge to solve problems not just analyze them.
That's the big difference is that we figure out a problem. We work on solutions. And then we work on trying to change practice and policy, not just policy-- also practice.
I'm running over. I've got my name tag on because we have about 80 city managers from across New York state are meeting on campus for these three days. They meet here every year. We work with them every year.
And I've been doing this kind of training of local government officials for 30 years, starting with Cardie. This is what we do when we have extension appointments that also involve research. It's not new. It's been decimated over the last 20 years, but extension is not new. And it does need to get reinvigorated.
So what I was thinking is that we take the disciplinary strengths that we have out in our departments, whether it's housing, transportation, infrastructure, environmental policy, social policy, and we look at the intersections. Think of a big Venn diagram or a big sunflower. And it's at the intersections where the neat problem definitions are going to come together, and it's at the intersections where we're going to come up with solutions. That's what's super exciting.
That's where engaged social science research should be in the 21st century. It's at the intersections. And I'm arguing that those should be focused at the urban scale. The world is urbanizing.
The majority of people are in cities already, and more are coming-- climate change, migrants moving to cities. We need to focus on the city, but not just the city as a political power because the city sits in a region. And in social science, we talk about a space of flows-- flows of water, flows people, flows of economic activity, flows of garbage. 300 garbage trucks come up from New York City every day, going through this county and building a garbage mountain at tops of Seneca Falls. So we need to think about these things in a comprehensive way.
And at that center of that sunflower is public participation, planning, and governments-- public alternatives. I'm kind of getting tired of market alternatives. They have their place, and it's been given too much place, and that's part of what's yielded us the gross inequality and the anti-democratic movements that we have today. So problem focused, yes, solution focused, yes, and then working outward to policy and practice change.
Now how do we achieve that part? Well, we've got to do it in partnership-- partnership with communities, partnerships with local governments, partnerships with NGOs. They'll even help fund it, but they will pay 58% overhead. They'll pay zero or 10 or 15, if you're lucky, but the university will tax you at 18%.
So if you do this work, your dean will be unhappy because it will be a net cost to your college. But we can fix that because that innovation was new with the budget model that came out of the crisis. The second thing that's critically important is the role of professional master's students. These are the students who are most interested in this applied work.
Sorry, it's not that interesting to your PhDs. It can be, and I have the rare one that is. But it's the master's students that are into this-- master students in planning, master's students in the Cornell Institute of Public Affairs, master's students in ILR, master students in international development in CALS. These students go out and run the organizations that put these solutions in place in the world, and we have an obligation and the honor to serve them.
And in fact, Cornell put in place a lower tuition rate a few years ago-- about 10 years ago. It's now $36,000 for these students. But in the new budget model, the tax per head is $8,200. So $8,200 on 66,000 at the Dyson School. It's 12%-- no problem.
On $54,000 at the engineering school, it's 16%-- no problem. But in the social sciences, it's 24%. That's a problem. So if we want to really do engaged research with community, we have to fix the structural impediments that have been put in place a mere 10 years ago, and they could be lifted so that we could actually do this kind of work and not be a net cost to our colleges. Thank you.
[APPLAUSE]
VALERIE HANS: So we have a remote participant, if the technology works. And it should. It's coming from Cornell tech. We're looking forward to James Grimmelmann.
JAMES GRIMMELMANN: Hello, I would start by [INAUDIBLE]. So can I still have audio?
VALERIE HANS: We have the audio, James, but we don't have any video from you.
JAMES GRIMMELMANN: Yeah, the video needs restarted on your end.
VALERIE HANS: OK.
JAMES GRIMMELMANN: OK, great-- there we are.
VALERIE HANS: Yay.
JAMES GRIMMELMANN: Sorry about that. Hello, everyone. Thanks to Valerie and Dan for convening this and inviting me to be part of it.
I'm James Grimmelman. I'm from the law school. I'm based out of Cornell Tech.
And I work in law, computer science, and technology policy. And the thing about tech policy is it requires to be informed both on tech-- in my case computer science-- and law. You simply can't intervene as an expert in these debates without a baseline depth of knowledge in both. And people bring more from one side or from the other, but everybody in those conversations has to know something about each side. I see my scholarly mission, which goes beyond just the policy side, is helping lawyers and technologists and legal scholars and tech scholars understand each other.
And these are fields that aren't entirely used to talking to each other, but they have a lot in common once they break the ice. One way I think about this is that both law and computer science are fields in which experts manipulate complex artificial systems to do things in the world. There's a certain use of language that's characteristic of h-- people study the intricacies and details of it. And they're both characterized by a mixture of austere elegance-- appreciation for the beauty of a simple theory with a certain ruthless pragmatism.
It [? disconcern ?] for the theory if one can get results. So effective collaborations at this frontier are often more a matter of arbitrage than anything else. You take well-known insights from one side, carry them across the disciplinary border, and sell them at a profit on the other by fitting them into recognized and familiar frameworks. And the difficult part isn't typically the translation.
Somebody who is appropriately familiar with the side they're translating to typically has a fairly easy time slotting existing ideas. And I've seen this done dozens of times in literature. And there's a certain amount of time in the chair to get it done, but it's actually not that difficult.
The tricky part is-- as in the joke about the plumber-- knowing where to hit. It's recognizing when people on the tech side or the legal side know something people on the other side don't fully appreciate and would benefit from. The work needs typically to target specific disciplines to be useful for scholars in society that they can write white papers and policy papers sometimes that are broadly drawn from both sides.
But the most useful interventions are often things that are actually targeted to one side or the other-- that you have computer science informed by economics, sociology, philosophy, law, et cetera. You have law informed by computational methods or simply to take as the subject fields characterized by new and important technologies. And the most important publication and inner outputs typically are framed within the genres and the rhetoric and the academic standards of one or the other. What makes it distinctive is that it pulls heavily on insights and ideas from the other side of the law/social sciences frontier.
And I found two things to be effective in spotting opportunities for fruitful exchanges. One of them is immersion-- training oneself in both scholarly traditions. This is obviously something that scholars themselves can do through detailed study-- both during their education and from a position on a faculty.
But I think, in particular, our graduate students, the PhD and JSD students, brought a great opportunity here. We should be recruiting students with interests that span tech and the social sciences and helping them assemble programs of study and special committees that immerse them in both traditions. They move more freely across disciplinary boundaries than we do. We should try to recognize that and encourage it. Cornell has a uniquely flexible doctoral structure, and we should embrace that fact-- something that gives us a real advantage in doing this kind of interdisciplinary work.
The other thing I think is really effective is regular conversation-- outside of a specific problems or goals or projects. Just building the institutions that get people with multiple expertises talking to each other. These institutions can be formal, like centers or colloquia or specific departmental lines. They can also be very informal just physical co-location, the opportunity for people to spend time near each other, things that bring people together, and get them talking.
And once they do, it's [INAUDIBLE] find interesting problems of overlap and places in which somebody can bring insights to bear in ways that are surprising and be very direct in collaborations. But bringing scholars from different traditions together and getting them talking together fairly naturally leads to great collaborations, in short order. So I see in some ways, the most important things we can do is building the structures to enable collaborations to emerge, rather than try to target specific ones upfront.
[APPLAUSE]
DAN LEITZINGER: So first of all, thank you everyone for your participation on the commentary inspiring in many ways. So let's give all the speakers a big round of applause.
So we have about 10 minutes or so. We don't have a lot for discussion, and people should feel free as they go back to their offices to send us comments or notes or other ideas about [INAUDIBLE] collaboration. This is, again, it's just a small share of the potential things we could do in terms of radical collaboration.
But people have thoughts, comments, reactions, next steps. Yes? Please identify yourself and your department so we can--
[INTERPOSING VOICES]
AUDIENCE: I noted four massages that I think are [INAUDIBLE]. One is the importance of a problem orientation of the work, rather than social science in the traditional sense. That's the grounding. That's why medical collaboration might be very helpful to problem orientations.
Secondly, structures are important for external visibility and for internal facilitation on the work. Third, incentives for faculty-- one person mentioned it explicitly, but it runs through everything. And fourth, budget model distortions, which, if we really want to have this work thrive, those need to be addressed. Thanks.
DAN LEITZINGER: So next year, there is another committee that's going to follow on these two committees [INAUDIBLE] the structured report and the IPS report. So we're going to focus here a little bit more on ideas. Jeff?
AUDIENCE: Yeah, it's a reflection, thinking about ways to invest here. There a lot of talk about research policy and practice. And I think flipping that is actually quite useful. One of the challenges are how do you scale this stuff up? Well, lots of policy and practice is not having the space but is done at scale.
And understanding how this play out in the real world-- I think is tremendously externally engage. The challenge is federal or even foundations are not very nimble in getting funds. NIH is nimble as nine months. And so there's a couple mechanisms around, like the Atkinson center has a rapid response fund. I think a real benefit with these in this discussion to consider having internal funds available for these rapid response kinds of projects that span social science disciplines but can react to things that happen in the real world and whether or not they have an impact.
DAN LEITZINGER: Yes.
AUDIENCE: Thomas [INAUDIBLE], not a social scientist but from the perspective of somebody who wants to see the impact of their work in society, which is what makes Cornell a special place-- so probably important to all practitioners that applying the best social science to those aspects of the problem is really what gives us a competitive advantage. So I think across the university, having said be the message. The collaboration is what make Cornell the best University-- having that message go to senior administration [INAUDIBLE] et cetera that's part of the message. It is something that the barriers are low. We heard they're high enough that it takes a lot of work, but they're lower here than in any of our competitors.
AUDIENCE: Lucinda Ramberg from anthropology in the college of arts and sciences. I just want to reiterate the point about-- from where I sit, anyway-- the impossibility of thinking about this big ideas, apart from the question of structures, in particular was spoken, I thought, very effectively by Laura and by Mildred. And this is where the conversation went in our department when we started talking about the structures committee-- report back from the structures committee. And the work of this project is that these are really inextricable to each other, and I realize that the charge we've been given is to do them separately, but I think we really need to respond strongly with the message that many of the faculty, especially in the social sciences, are saying that this is really not plausible to separate these charges.
DAN LEITZINGER: Yeah, I think that will be reflected in our report. I mean, we're working out what areas [INAUDIBLE] we keep thinking about this in terms of cluster [INAUDIBLE]. The structure side-- it's going to be hard [INAUDIBLE] from the structure.
MALLORY HANZ: Yeah and maybe we can say just a comment or two about our next steps. So we're co-chairing this committee, and we're fortunate enough to have Lucinda, and Parfait, and David. i think perhaps anybody else who's been on our committee here today. But all of the forums are videotaped. They were live streamed, and they were also taped.
So our committee will be reviewing them all and trying to somehow synthesize the incredible ideas, excitement, energy, and really phenomenal projects that we've heard presented over the three forums in a report to the provost about the next steps. But that would be an exciting report to write. I think we all feel that it's a pretty heavy responsibility. And to that end, I want to invite you, if you have some additional ideas, if you want to share with us, we can share them with the full committee, as we try to pull together the contributions that we've heard over the course of the last several months. Anything to add there, Dan?
DAN LEITZINGER: No, I think that's the main point. You guys are going to study or keep you guys in the loop so when I'm sure our report will be vetted by the university committee, as well [INAUDIBLE].
MALLORY HANZ: So thank you. We really appreciate it.
[APPLAUSE]
Organized by the Social Science Ideas Panel Committee, Daniel Lichter and Valerie Hans, co-chairs.
The public policy faculty—broadly conceived—provides a bridge between Cornell’s traditional academically-oriented departments and faculty and the public. In this regard, Cornell’s social science faculty from City and Regional Planning, Policy Analysis and Management, Industrial and Labor Relations, Government, and the Bronfenbrenner Center for Translational Research provide new possibilities for synergistic research and training—radical collaboration—across the various social science disciplines.
But public policy and engagement is not limited to interconnections among social science faculty and programs; it also involves programs outside the traditional social science disciplines. Social scientists are actively involved in research on the behavioral and economic consequences of climate change; changes in the digital environment and social media call for a better understanding of ethics, regulatory policy, and social and political impacts of new forms of communication and social influence (e.g., fake news and propaganda); on-going research involves new collaborations between transportation engineering and the decision-making sciences, including psychology, marketing, and regulatory economics; and social scientists are well-suited to address questions about the adoption and diffusion of new technologies (e.g., driverless cars).
Featuring: Parfait Eloundou-Enyegue, Thomas D. Gilovich, Miguel Gómez, Jon Kleinberg, Bruce Lewenstein, Michael Lovenheim, Suzanne Mettler, Hirokazu Miyazaki, Kelly Musick, Jed Stiglitz, Laura Tach, Mildred Warner, Natalie Bazarova, and James Grimmelmann.
