 and I'm chairing this session and this session is focusing on research and the ability of research to influence policy. Now earlier this morning we heard from Her Majesty Queen of the Belgians about the critical role that research and universities need to play if we're going to deliver on the sustainable development goals because we are not going to achieve the goals without having the best evidence and the best research from a range of disciplines, science, technology, the arts, social science. But I would ask all of you, is research currently really having sufficient impact on what governments are doing? And I think the answer is no, it's not. I've spent much of my working life as a politician. I was a minister in government in Australia working in many areas of the sustainable development goals in health, in water, in climate change. And I have to say when I was a minister I was pretty shocked at how rarely government sought the advice of researchers when policy was being made. And usually we went to consultants and usually what we got was what had been done before. And if we're going to achieve the sustainable development goals we need, we know that we need big changes and we can't do just what we did before. So in this session we're going to explore some solutions to this problem. How we get research, the best evidence utilized by the politicians and the policy makers. We've got some great speakers and interestingly I think all of them have had experience in both camps, both in academia and in policy making of various sorts. And before hearing them I want to just highlight what I see as four key challenges for researchers as you seek to influence the political process and also give three possible solutions. So first what are these challenges? And the first one is that politics and research operate to completely different timescales. You can't believe how busy you are as a government minister. I'm sure Murray and Pangestu could attest to that. The timescale that policy makers are given by politicians is measured in days and weeks. Not the months and years that research generally takes. And so I think the key lesson here is if researchers are to make an impact their research has to be available when it's needed. The second big challenge is that researchers usually focus on one issue or one area. Whereas politicians and policy makers are dealing with multiple issues at the same time. Many of them complex. And so the hard thing for researchers to understand is that in many cases their issue is not the issue that the policy makers are really concerned with. And it also highlights why if researchers are to have an impact they need to be coming in a team that involves many disciplines and many different areas of government. Third and I think this is probably stating the obvious that most policy makers don't spend a lot of time reading academic papers. Research papers are not usually written in a user-friendly way. And academics actually lack expertise in talking the language of decision makers. And the final challenge is the difference in culture. As a good friend of mine who was one of Australia's I think great environmental scientist Peter Cullen said, researchers seek the truth whereas politics is driven by values and by interests. So evidence isn't the only factor in a political decision. Other factors such as emotion, local opinion, political interests all have a big impact on the final policy that's agreed. So there are four challenges and I think there are some things we can do about it though. There are three potential solutions that I've seen work in different ways. And the first is to design better ways to bring researchers and policy makers together, not just once but over a long period of time. And that really involves networking and what I would call embedded policy networks where researchers, professionals and policy makers are part of an ongoing network to deal with a particular issue. And we've done that at my university, Monash University in urban water management where over the last 15 years we've had a large policy group probably over a hundred people, academics, policy makers and water industry professionals working on the problem of having more sustainable urban water management. And that means co-designing research together looking at possible solutions to the problems and designing the policy together. And that's been very effective. The second thing I think universities could do better is help train their researchers in the art of policy making and the understanding of politics. The institute that I'm part of, Monash Sustainable Development Institute, we've actually conducted those training sessions for our researchers in water where we've put them before a virtual cabinet. People like Marie Pangestu, former ministers, and made them put a presentation to the cabinet. Quite a fascinating exercise. And then we've asked the researchers to go into a media interview with a journalist and recorded that and played that back to the researcher. And then the third solution I'd like to highlight is to help the politicians and the policy makers themselves better use research evidence. And there are millions of research papers out there. They're not accessible for most policy makers. So we need a way to translate them into something that's understandable for policy makers. And that's something that John Lavers from Master University is going to be talking about as well. So they're just some preliminary ideas. We're going to hear from a great group of speakers now about some of their experience. But I'd like to just conclude to say that this is such an incredible challenge we've got to achieve the transformations necessary for the SDGs that we simply have to use the best evidence and the best researchers available. Thank you. And now I'd like to ask Marie Pangestu to speak to us. Marie is a former Indonesian minister for trade and for tourism and the creative economy, as well as being professor of international economics at the University of Indonesia. Marie. I forgot I have a mic. Good afternoon, ladies and gentlemen, friends. I know we're sitting between you and lunch. So I hope that we can at least excite you enough to forget your hunger pangs. I'm going to talk about something that's actually happening within the Indonesian government, which is using research to inform them as to how they should be planning the climate change targets, the NBCs, as well as the SDG 2030. And basically it's called the low-carb development initiative. And it comes actually from the new climate economy research that came for the whole issue about climate change. And the main message that the new climate economy is trying to impress on countries with regard to the NBCs is that dealing with climate change is not a trade-off. It's not like you're going to be trading off lower growth while you're addressing climate change. And that has been that kind of mindset is very important to have the, you know, for politicians as well as for policymakers. So in October 2017, Indonesia volunteered to be the first country to be implementing this research-based approach, model-based approach of the low-carbon development initiative. The other countries are Ethiopia and Colombia. But Indonesia was the first one to roll out this model and integrate it into its long-term plan. And the fact is that it's embedded also with the NBC targets of 29% reduction in greenhouse gas emissions without any complementary help from outside and 41% by 2030 if we had outside help. That's the way our targets are framed. And it is intended to identify specific policies that the government should be able to do. And a tool, basically, for the policymakers to approach stakeholders and help communicate the benefits of climate action and communicating to the public as well as to politicians is one of the intentions of this model. And the basic academic research comes from a system dynamic model, which I think you mentioned earlier, researchers tend to focus on one issue. So the intention is to look at the inter-relationship between sectors, resources, and individuals, which is exactly what we're trying to do with climate change, to know that if you do one thing in one area, it can have an effect in another area. And the model builds on historical data and analysis, but it allows you to add new information and update the model. And it also is very adaptive in the sense that this is where the importance for policymakers is the fact that you can actually simulate scenarios. And if I did this in this particular system, whether it's energy, whether it's land, what would happen to the greenhouse gas effect? What would be the economic effect? What would be the employment effect? What would be the effect on pollution and so forth? So it's intended to be research based and each system has information, has research behind it that is continuously being updated. And I think this is one of the big wins for a policymaker to have. And I would say that just to show you that you can actually show sectoral models that can demonstrate growth in the emission bisector. So that allows the government to focus in which area. Indonesia, of course, at the moment, it's forest fires and peat and land use. But we are beginning to address that, but in the near future, it's going to be energy and transportation. So that allows you to focus on what is the priority right now and what would it look like in the future. And this is probably the most important, I think, output. I really love this picture because it allows the politician, the policymaker to use this. And the research is demonstrating that you can achieve both. This is the important, most important message that you can have low carbon path, but you can also have benefit at the same time on economic growth, on the society, and on creating new jobs and so on. So we can demonstrate this actually in a very numerical way. Politicians need numbers. They need to know how much jobs are being created. Growth is one thing, but about jobs. And we can even show if you didn't do, if you pick the business as usual scenario of not doing anything, what's the pollution going to look like? And what's that going to mean for the quality of life and the health costs? So you can do a lot of simulation and you can also show that you can have this low carbon policy and if you did the 29% or the 43%, what would it look like in terms of growth? In fact, you get a higher growth. The more you do the low carbon path, you actually get a higher growth. So the more ambitious you are, you actually get higher growth. And you can also show what the effects are on employment and so on. So this is really evidence-based modeling which allows scenarios and it can be continuously updated. And in fact, it can also be localized. You can do it by region. So I think I won't go through all the scenarios, but basically you have a base case, you have a moderate case and then you have a high case of 41% target. This is our actual NDCs. But we're all, as we know, with the recent IPCC report, all countries are being asked to be more ambitious. So by 2020, we're all supposed to have come back at COP in Glasgow and come back with more ambitious targets. So that would be the LCDI plus scenario. And the policymaker will allow you to pick, what does that mean in terms of the things that you have to do in each system? And what are the policies that you need to do more importantly? So these models are integrated into our long-term plan. I think my time is up, so I'm going to just conclude with the important policy messages that are there. I think this has been a really neat solution as a former policymaker. It's a very useful tool. As I said, there are moments when you want to scare the hell out of people, scare the hell out of the technical ministry, scare the hell out of the politicians. If you don't do this, this is what's going to happen. Lower growth, pollution, and we all know what pollution, right now pollution and climate change has become a big political issue. So that's one thing that has happened. And why has it been successful? I think it is because the technocrats in the Cabinet, the planning ministry and the finance ministry were very much on board and they wanted a tool to be able to use to their other Cabinet colleagues. This is one thing I would share with you, John, that my biggest battle, first biggest battle is always with my other Cabinet colleagues to convince them of what needs to be done. And this kind of scenario setting will help such a case. And it provides a compelling case for the fact that you can achieve both low carbon development, low carbon path, as well as development growth with all the benefits. Oh, sorry. I don't know what happened. Yeah. Okay. The last slide was actually on the policy implications, which I think are important. So you need the tools and the framework and they can be continuously updated. And the next stage, we want to localize it. We're going to identify where the hotspots are in terms of climate change by province, by district. And then we can have it at the district level because local government called political and policy commitment is important. But of course, we are at the beginning. You have the tool, you have the framework. But the politics, as you said, short term, long term is a big issue. So we need to have the long term political and policy commitment. And this is really the biggest challenge. But I think if we can at least agree on the baseline, and using this to have the scenarios and then have a discussion with all stakeholders, what would be the political trade offs on whichever path you choose. And finally, that I think this tool could be very useful to be used with the parliament, with private sector, and so on as a tool to disseminate what needs to be done urgently. And now, thank you. Well, thank you very much, Mari. And now I would like to hear from John Lavis, who's the director of the Master Health Forum at McMaster University in Canada. And John has been a key advisor to health policy makers in Canada, but actually, in many countries of the world. John, thank you very much. It's funny, you know, I've been in this business of trying to support policymakers for 30 plus years. John just gave the best five minute summary of the lessons learned that I've heard in all of that time. So I think I'm a very slow learner, but I'm going to dial back the clock to just tell you how I got to a very similar place to John. So 30 plus years ago, I was inspired by a bunch of prep professors in the government department at Harvard, where I was studying and they were focused on the role of ideas in policy making. And with my clinical hat on, I was hearing all this talk about evidence based medicine. And I was trying to figure out how do we harness these insights from political science to try and drive evidence as one of the sources of ideas that can sit alongside interests and institutions to drive policy making. And for a decade, I studied that. And then I started to get comfortable enough, I guess, in my career that I felt I could start taking risks. And so I thought, well, let's go out and actually try stuff because the field was stuck in endless observations about the challenges and people weren't testing solutions. So we went down a very long path of testing what I call packaging and push. We put together all the best evidence and we give it to policymakers and we cross our fingers and we hope for a dramatic shift. But the chance of us arriving on their doorstep with the evidence, given the 50,000 other things they're dealing with, is almost zero. So in 10 years, we had a couple of wins, but boy, were we demoralized. And we realized that we were not just not having an impact, but in any given year, just in the hell space, there were hundreds of times where political windows of opportunity arose and savvy politicians were making the case for a compelling problem, a viable policy and conducive politics. But they were making it without evidence. And we weren't there in the hours and days and weeks that they needed us to be there saying, here's the evidence about the problem and its causes. Here's what we know about different options. Here's what we know about implementation. We know evidence isn't going to triumph, but surely it has to be alongside those considerations. And where are, as we heard from Eddie earlier today, where's the citizen voices in this, informed by evidence, but also bringing their lived experience? And where are the stakeholder insights informed by the evidence? Where are those deliberative processes? So we ended up saying, okay, for a while, let's try this approach of timely, responsive, but the moment we started to do it, every time a new question came up, one day it would be recruiting health workers to underserved areas, the next day would be governance arrangements for accountable care organizations. We'd do searches and we'd find 30,000, 50,000 hits and we couldn't pull stuff together. So we had two ahas at that stage. One is we were focusing on the wrong units of research. We should be focusing on systematic review. Someone else has gone out and found every study, selected the ones that address the relevant question, appraised their quality and synthesized them. Because on any given policy issue, there might be 20 questions that need answered. And there might be 40 reviews that answer different pieces of it. Second realization was we couldn't be searching for these reviews every time we needed to put them all in one place. So we built out a database called health systems evidence. It's now grown to 7500 plus systematic reviews about how to strengthen health systems, get the right program services and drugs to people. And it's used every day in dozens of countries around the world to train policy makers on how to work through problem options and implementation considerations and pull in the evidence. It's used in rapid syntheses, 3, 10, 30 days. Here's what we know. It's used to inform citizen panels, stakeholder dialogues. And in some jurisdictions, like my own home province, you can't get to the Minister of Health or to cabinet on a health system issue without showing that you have searched the database. Because otherwise, the politicians are saying, how do we know we're not missing key synthesized research evidence? So then we started to about three years ago have people knocking on our door saying, you're doing all this stuff in health. Why aren't you working in the broader SDG space? But the moment we started to work in education, other spaces, we came upon the same problem. We couldn't find the systematic reviews, the economic evaluations efficiently. So we built out social systems evidence to cover all of the non health SDGs. So with SSE, we harvest all of those systematic reviews. We we appraise their quality. We provide links to the single studies. So if you only want to zero in on the studies from Indonesia, we can. We link to the user friendly summaries when they exist. So they're in plain language, all in one place. And then a year ago, two other things happened. One was we built out a partnership with the Monash Sustainable Development Institute to bring in all of the reviews in the spaces we don't know. Well, climate action, environmental conservation and everything. So it's now a comprehensive database that will keep growing over time and be continuously updated. The final thing we did was build out a partnership with 14 countries spread around the world to try the same approaches in health that got us such traction in the health space. Using social systems evidence, rapid synthesis in 310 or 30 business days, the evidence brief and form stakeholder dialogues, the citizen brief and form citizen panels. And already just within that limited period of time, huge wins directly informing the land reform commission in South Africa, directly informing justice reform in Brazil, directly informing the province of Antioch in Colombia's approach to revamping its child welfare policies. In Ethiopia, directly informing the approach to deal with stunting. So huge impacts. But the precursor to this were four things. Realizing we needed to respond in timely ways to windows of opportunity. Second, realizing we needed to be able to add systematic reviews alongside local data and studies to really inform all of the questions policymakers had. Third, we had to have a knowledge platform we could draw on and that is now social systems evidence. And fourth, we needed a variety of ways to package the evidence and contextualize it and put it alongside citizen voices and stakeholder insights to actually drive change, to get politicians to that magical place of a compelling problem, viable policy and conducive politics all informed by the research evidence. Thanks. Thanks, John. There were certainly some great lessons there. And now we've got a chance to hear from Beth Novik, who is the director of Gov Lab at New York University. Also, former United States Deputy Chief Technology Officer and Director of the White House Open Government Initiative. And I understand that's not under the current White House, it was under the Obama White House. Beth. Thank you. Thank you very much. And it's really such a pleasure to be here. Back in 2015, I got a call from a policymaker sitting in Quito, Ecuador, explaining to me why she was late on something we were working on together. And she said, but I apologize. But the Koto Paxi Volcano, which has not erupted in over 100 years, is now spewing ash. And we have the very urgent problem that we have tens of thousands of people living within a 12-minute area of the blast radius. And she said, you have any good ideas for us? I said, well, that's a pretty urgent problem talking about the different scales between policymakers and research culture that John alluded to. I said, I may not have all the best ideas, but I know a lot of people who actually do. And what we can do is we can reach out to those people. Again, as you talked about interdisciplinary people, researchers, people in industry, people with experience, and we can formulate a process that we've come to refer to as smarter crowd sourcing, in other words, reaching out to people who have a wide variety of expertise to help develop quick solutions to the problem, to get folks together online, not only to share the evidence that they were aware of, to share both experience of what works and then experience of what might work. In other words, both the innovative and the effective that you referred to, and to share that in a quick way, packaging it in a way that the city of Quito could then use. This is emblematic, I think, and we've repeated the process for a number of different issues that range from big thorny issues, not just the explosion of a volcano and disaster management but corruption and the Zika health scare in Latin America the year later. I want to put to you that it's extremely important that we solve the challenge that all three of my predecessors have referred to in terms of making it possible for governing institutions to use expertise more effectively and to do so to come up with solutions that work. We have to do so because we're experiencing a trust deficit right now in our institutions. This is not just an American phenomenon, it's a global phenomenon, where there is the sense that our institutions are not working as well as they ought to to address the challenges that we are here to discuss. We are facing problems that even in our most effective bureaucracies, even in places like the United States where we have a competent civil service, we are not able to do as good a job as we need to to address the challenges of our time. So whether it's an outright explosion of trust deficit or whether it's a creeping crisis, the fact that we are not able to do as well as we ought to, means we have to do a better job at how we come up with solutions. And that means we need to look at how we get expertise. I would put to you expertise understood very broadly, the credentialed expertise that academics provide to us, as well as the lived experience that you've heard talked about earlier. All these forms of expertise are extraordinarily important for doing what we need to do. That is, however, a great challenge if you think about the fact that today when it comes to if we think about now data and expertise are not the same thing. But if you think about the fact that data is a strong component of expertise, that in our public policy schools in the United States, in the top 25 public policy schools, not a single one requires all of its graduates to learn data science or to take a course in data. And that's the same for law schools, the typical training grounds for people who go into government. And what does that result in? That results in a civil service that doesn't know how to use data and evidence. In a 2014 survey of federal employees, 78% responded that data is integral to doing their work. But 60% reported that their agencies did not actually know how to use data. In a recent survey that we conducted, GovLab and the Monash Sustainable Development Institute, John's Group, my colleagues and I further surveyed both civil servants at the local level in the United States and in Australia. And we found even worse numbers. In other words, we're talking about a third of people, only a third among civil servants who'd said they'd even tried to use data analytical thinking. And among that third that we asked, when we further probed them, whether you could formulate a hypothesis, define a problem to which evidence could be a solution, only a small fraction said they knew how to define a hypothesis. So I want to suggest to us that as important as creating the supply of evidence and hats off to John and to his colleagues at Monash who have developed this phenomenal resource, both in terms of health systems evidence and social systems evidence. That has gone, as you've seen in the jurisdictions where you've worked, a long part of the way by creating the supply of expertise to generating the demand for expertise. But I will just add with my remaining few minutes the suggestion that we also need to cultivate and train up that demand. I love the idea of having academics do moot, moot, moot, moot cabinet exercises. But we also need to make sure that on the other side, the people that we're talking to are responsive, that they're demanding that there's a request for the supply of expertise that we can provide. So that means we need to be able to cultivate what I would call the skills of the public entrepreneur. We need to train people in new ways of working and thinking which start first and foremost with that ability to define the problem. It's a crucial skill that I don't have to tell you is important because whether you do project management or any kind of process oriented project or research, you know that you have to start by defining the problem and defining the hypothesis. Writing problem statements is a widespread practice that people learn in a variety of disciplines. But today we can't do it the way we've always done it, namely behind closed doors. We need to do it in an open and collaborative way, the way that PDIA does, the Building State Capability Program at Harvard, this is a recent blog post from them just yesterday, about the way that they're engaging again with experts, with citizens, with other stakeholders in defining the problem collectively so that we're identifying a compelling problem that we want people to solve. So that means retraining and rethinking about problem definition as something that we do open and collaboratively differently than we've done in the past. The second set of skills though is equally participatory. It's not just about identifying problems together, it's also about coming up with solutions to problems, identifying what are those compelling things that might work where we can actually do so engage with a wider group of people. Now, a lot of agencies, including the ones that I work with now and John kindly under instructions did not refer to the fact that I am currently in government, I can say it out loud. I'm the Chief Innovation Officer for the state of New Jersey. It's okay. We do a lot of sitting with citizens and post-it notes now trying to understand from real people what are the problems as they experience them. And when you do so, you can really come up with better solutions to problems, but it's not something that we're necessarily trained to do. It's not something that we know how to have these conversations with people so that we can come up with good ideas faster. I'm out of time, so let me just conclude with one final skill, which is the ability to use both data and evidence as has been talked about here widely in the way that they've done in San Francisco, for example, and in countless other stories I could give you. There were many bike collisions with automobiles in San Francisco that are killing people. What do they do? Of course, they look at the data and they're able to pinpoint that the collisions are happening on one particular intersection. In the UK, what they're doing when before they formulate a policy and select instances is they're putting up the evidence online and they're saying this is the evidence on which our policy is based. Is it the right evidence? You tell us. In short, it's important that we develop these skills for working together, again with expertise understood broadly in the way that they're doing in Brazil to go out and not ask just adults but ask children. Is the policy that we're making to improve the conditions in your schools working? If it's tell us about the infrastructure, tell us about the meals, tell us whether what we're doing is working or not. We need this continuous cycle of conversation both before and after to enable us to create the demand for evidence to use it well and to know what's working. Thank you. Well, thanks, Beth. And finally, we are very fortunate to hear from David Smith, who is the coordinator of the Institute for Sustainable Development at the University of the West Indies. And David was also one of the independent group of scientists that were appointed by the UN Secretary General to prepare the 2019 Global Sustainable Development Report, which has just been released and I urge you to look it up on the internet. Significantly, that report has framed the discussion at the UN about the SDGs this week. David. Thanks very much. I was part of a group of 15 scientists from around the world asked to look at this scientific take on how well we are doing in terms of achieving the Sustainable Development Goals. And we found that progress has definitely been made. We are moving forward on several of the goals. However, there are many goals where we're not moving forward as well as we would like. And unfortunately, there are a large number of goals and targets where we're moving in completely the wrong direction. We looked at why this might take place and essentially, rather than doing original scientific research, we reviewed reviews. We figured out what scientists had been doing on the different issues and we took reviews of those and we put our consensus on that and tried to figure out exactly what they were saying and how that related to the Sustainable Development Goals. Couple of things that stood out. One was inequality. Inequality between nations, obviously. And inequality within nations between the rich and the poor in those nations. Inequality in terms of access. So there's inequality in terms of that may be based on gender. There's inequality that may be based on social class. There's inequality based on things like disabilities and so on. A lot of those aspects are affecting our ability to reach the Sustainable Development Goals and affecting our ability to leave no one behind. Another aspect which came out as being very, very important is interlinkages. All the goals are interlinked in one way or another. And if you simply pursue the goal which is most important to you, it's very likely that in pursuing that goal in a single-minded fashion, you are going to create trade-offs and problems with all the other goals. And we could see that happening in many, many different goals. And as a matter of fact, within the next two weeks, we'll be putting up a website so you can click on the different goals and targets and see how those interlinkages work and which goals work together and which goals work apart. So what we said was, well, with all these interlinkages, the inequalities and so on, we cannot therefore be continuing to pursue single goals even if those seem to be the most important goals. We said, well, let's look at ways of grouping those goals. So we came up with maybe six what we called entry points for transformation. And the idea was, well, well-being is very important. Human well-being is the whole reason why we have the Sustainable Development Goals in the first place. Economics, just and fair economic systems, cities and communities where people live, food, energy and the global commons because of course the global commons is where we're going to be getting everything that we need in order to support human life on the planet. And we said, take those entry points, those will touch on a variety of different goals at each entry point and work along with what we call the levers and that would be science and technology, individual and collective action, governance and also economics again. And use those levers in every single case to come up with different ways of creating pathways for each country. So it's not a one size fits all, but we try to merge the levers and the entry points together to come up with unique pathways which makes sense for each country. This is not supposed to sound simple. Life is extremely complex and getting the Sustainable Development Goals to work is extremely complex and extremely complicated. But we think that if you follow these four levers and the six entry points, it'll at least make it successful. One of the things though that we came very close face to face with is the large inequity in science and the irony I suppose that the best data are in the countries that are doing very well and those countries which are likely to be left behind have the least data that can help them make database decisions in terms of policy and implementation. In addition to that, they are the ones that have the least number of scientists and the least funding for doing research that could help them solve their Sustainable Development Goals problems. Much of the best science that can help move the world forward is hidden behind paywalls. As an example, sitting at my desk in the University of the West Indies, which is one of the top 5% universities in the world, I can Google all kinds of stuff using Google Scholar and I can find all kinds of interesting papers and when I start to download them, Taylor and Francis and Elsevier and all the rest will tell me you can download this if you pay us $30 or $40 or $50. Just recently, a big publication came out on adapting to climate change for the princely price of 1,100 euros. If I take a plane, fly to JFK, take the subway and get off at the subway station outside the front door of Columbia University. I don't even have to walk into the University and take out my computer. I can download immensely more scientific information standing on the sidewalk than I can in my office in the University of the West Indies and that would be true for nearly every developing country scientist on this planet. That will not allow us to hit the sustainable development goals. Unless we can get open access to good data, unless we can share scientific information, unless we can share scientific practice and not have to scale paywalls every single time, we will not achieve the sustainable development goals. The last point I want to leave you with, Hurricane Dorian hit the Bahamas two weeks ago. It's going to become the new normal for many of us in small island developing states and the least developing countries in the tropics to be profoundly affected by climate. Work done by the University of Hawaii points out that those in the tropics will be hit with new climates much earlier than those in the higher latitudes. We are also those countries which are least able to deal with those problems. I'd suggest to you though that regardless of where you come from, if your home was subjected to 185 mile per hour winds for over 48 hours, there wouldn't be much left of your home after that and you would not be thinking about achieving the sustainable development goals. Unfortunately, that is the reality for many of us in least developing states and in SIDS and we need to be able to get around that not just because climate is a problem but development and development science is a problem. We need to improve the way in which we do science and improve the access of countries to good science and good development practice. Thank you. Well, thank you David. We've got time to raise a few questions and I'd like to take up the point that David made before which is that developing countries need access to research but in many cases it's behind a paywall. And I'm wondering if David or Mari or any of the other panellists have some views on how we can overcome that particular problem. We're seeing some movement towards that. I know I think it's the Bill and Melinda Gates Foundation said that work that they finance when a scientific paper comes out of that it must be made free and open access. And bit by bit you're seeing publications having a window for open access but it's not nearly enough at the moment and we do need to figure out a way because we need to make sure that there are good authoritative places where you can get scientific information and that costs money but you also need to make sure that the people who need it aren't held away from it because they have no money and that's something which is above my pay grade. I think at least in Indonesia there is an effort. It comes from the education and research ministry where the university is the one that subscribes to these access to journal kind of processes but you have to be in the university and you have to have the edu, what is it? In your email, right? So I think it's not perfect but it's the beginning but I totally subscribe to the view that more should be made accessible. John and Beth? Yes, I guess three quick comments. So one is that at least in the health space there's the HINARI initiative specifically designed to improve access to the health literature. So if you're in a low income country you do have that direct access. Second, with platforms like social systems evidence that link to user friendly summaries that often give you all of the policy relevant messages and a whole set of additional information free of charge you often don't need to go to the full text. So that's also a critically important thing. And third, we have limited resources and to be honest if I was gonna prioritize on open access I would prioritize open access to systematic reviews because that should be the first start point. Someone else has pulled together every study in the world on the question appraise the quality and then you're looking at the top of the iceberg what really matters. Here's the actionable evidence that you can use. There's tons of science out there that will never see the light of day. It's not actionable. It's not high quality. It would be great if everything could be free but at least we need our systematic reviews to be free. And Beth? I'll be very brief though. This is I could get on a soapbox for a long time about this and to say that we're in the middle of a university. This room is full of faculty and students. It's incumbent upon each of us to stop and ask do not publish anything in a journal that demands copyright from you. Just say no. It's as simple as that. Publish in open access sources. Don't put your stuff on SSRN. Put it on the platforms that are created by the center of open science. I've had the privilege to serve on their board for the last few years. Instead of publishing on SSRN I've taken everything off of there. Put it on archive. Put it on SOC archive. Put it on one of the open resources that provide open access both to the data and to the publications and to the underlying data. There's lots we can say about the policy frameworks both universities and funders and governments that are refusing now to publish work and to fund work that isn't openly published and where the data isn't openly published. But it has to start with each of us by saying, no, I don't have to assign my copyright. That's it. Well, that's amazing. Thank you very much. Thank you. Murray, the Indonesian government has taken on, as you said, the new climate economy research. But one factor I know about Indonesian governments and ministers is that many of them like yourself have had quite distinguished academic careers, more so than in a lot of other countries. Do you think that makes it easier and is there some way to encourage more people from academia in many countries to join the political fray as you did? Yeah, I think of course in our case, it happens that the planning minister and the finance minister who are both technocrats and in fact our finance minister was the MD of the World Bank where the new climate economy was initiated. And she's very, very pro-sustainable developer. So of course it helped that there was buying from the top. And so a short of universities working with the ministers, it really helps when the minister has a technocratic background. But what do you do if they don't have the technocratic background? Then you need to be able to put it in plain English. This is really useful for you that you can actually tell a compelling story that is politically very attractive. And in the case of climate change, developing countries have always taken the view, this is a cost to us. If we deal with climate change, it's gonna be a cost to us that the developed countries didn't have to pay and if the cost is growth, we wanna turn that argument back, turn it around and say, look, this is important. And this is going to deliver you politically a win because it's creating jobs. And by the way, if you really have an aggressive renewable energy policy, it's creating jobs. It's new industry, et cetera, et cetera. So if you didn't have a technocratic minister, then you need to have a way to use the technocratic research to translate it into political language. And that's probably what you were saying earlier, how academics and researchers need to understand how to translate their work into what makes policy relevant and politically palatable, right? Or politically attractive, I should say. And I've also taken the view that not only do you have to influence the ministers, you have to influence the parliament because there can also be a force of change and a very important force of change and all the other stakeholders that you have out there. John, just a quick point because it's not always the case just because you have a technocratic background that you have the right skillset to inform policymaking. So you, John, talked about the political analysis skills and Beth talked about what I would call the policy analysis skills, being able to understand a problem, frame co-design options, think through implementation. And you also need the systems analysis. You're working these out within food systems, within health systems. And then you also, as Beth said, need the data analytics skills. I would say you need the evidence synthesis skills and you need the stakeholder engagement skills. So there's a lot of things there that we do a shitty job of training people in. So you can go through a PhD program and never be exposed to those six things. And yet that's what you need if you want to influence policy and you either need them yourself or you need to work with allies who are very well positioned to do that. Great, well, I'm afraid we're out of time because it's now time for lunch but it's been a fascinating discussion. I've certainly learned a lot today. I'd like to congratulate David for that report and I'd like everyone to thank our speakers.