Lost in translation? Strengthening science–policy interfaces for evidence-informed decision-making

Good morning, everybody. Your Excellencies, distinguished delegates, colleagues, and friends, welcome to the Science and Innovation Forum, the third day of the forum today, and welcome to this really important session entitled Lost in Translation. strengthening science policy interfaces for evidence-informed decision-making. Every year, the world generates more scientific evidence on how to feed ourselves sustainably, equitably, and within planetary limits than at almost any other point in our history. And yet, in country after country, that scientific evidence It still struggles to find its way into decisions, into investments, and into actions that would put it to best use. So over the next 90 minutes, we're going to ask an important question. Is what stands between evidence and action really a shortage of evidence? Or is it something else, something more structural, and indeed something we could fix with existing resources? So with that, it is my honor to invite the Director General of FAO, Dr. Qu Dongyu, to open the session. You have the floor, Director General.

Good morning, everyone. I'm not used to this, speaking so high. That's the typical Irish style. First time I feel so high and so far distant from my fellow scientists and technical people. And now the vice president of the CAS is here. He never saw me speaking like this. So you see that's the diverse culture in IFU. You can't force him to change, follow my style. He was a very famous professor in Irish. at Irish University. Now I just warm me up. I know you wake up early. I also wake up very early every day, before 6 a.m. Ladies and gentlemen, dear colleagues, good morning and welcome to this technical session of Science and Innovation Forum. This session asks us a question, how... Do we avoid getting lost in translation? I mean, not only translation, it's also interpretation from the real basic science to the popular science to the extension science, so-called basic science, applied science, R&D, and the extension services, and to the farmers' field. It's a long journey. And if we know what the translation means, yeah, it's, I don't think so. If a lot of people didn't understand what it means, translation. They only understand the translation language. They don't understand translation knowledge, translation of the way of doing business from the headquarters to the field. So-called the decentralized office. I don't want to use that term. But these are the offices, still office. We should have from headquarter to the field. That's our end use or service customer we should work for. We work in many languages. We know that when we means not clear, we don't understand each other. Now it's with the AI translator, it's much easier. And also, even though there are a lot of languages not translatable, because some, like the crisis, English, but we translate with two Chinese words. So the complete change of the crisis, what it means in English, in Chinese, it's a damage and opportunity. You can see that all the business change here. Today, something happening is, for you it's a crisis, for me it's opportunity. Pandemic is a big crisis for you, English, I don't know, in Spanish or Arabic, but in Chinese, it's maybe once in my life opportunity. Without the pandemic, how this big compound, more than 100,000 square meters, is empty. So I asked, encouraged my colleagues, Rodrigo, our logistics people, to run the renovation, starting with the most crowded part, cafeteria. Because now you can't stop one day. All the ambassadors, the diplomats, people, NGO people, they come and complain if you manage. Why you didn't offer the food for your staff? You create hunger for your staff. They can make a lot of rumors. But that time, we can work about two months or three months to clean up cafeteria without any complaint. So science and policy also speak a different language, yes. That's some missing, especially in developed world, the politician. They make the love for our commitment, the slogans, scientists do their own silo scientists, the research, and they are missing the interface, dialogue. Some countries are good, so far I said that China, and also Ethiopia, and now Dominica also, and Vietnam. And some small countries like also Singapore, the politician always dialogue with scientists, formally or informally. Let's try to understand each other, because scientists need guidance from strategy and policy. Politicians need update by development, advancement of the science. how to lead the change of development of the country and regions. Without someone provide the translation, no, they can learn by themselves, among themselves. Translation as an old professional may be less and less important. I encourage my colleagues in CSC, you have to find the alternative. Also, training the people, traditional interpreter, or translator to be more capable, more comprehensive, skillful person to involve the change of the society. But often it's evidenced it is a farmer or consumers to be work together to get the common ground, no matter you are scientist, you are politician, you are business people. You come to the field, you have to talk with a similar language to the farmers. Farmers only understand their own language unless you can have them to improve the productivity, improve profitability, improve the efficiency, produce more with less. That's my humble 47 years experience. Any farmers in the world, you can say, I have a small solution. You can produce more, more flowers, more food with less input, less cost. They will follow you. No matter you are a scientist or you are a politician or you are an entrepreneur. Or you produce a promise you produce high quality, I can pay for you five cents more per kilo. Also they follow. Then, that's why the contract growers. It's a key player for transformation of agriculture in any place in the world. Contract grow. Contract grow, contract with the dealers, follow the standard. Maybe standard recommended FAO Codex, or maybe standard of national standard, or regional standard, or even the entrepreneur standard. Scientists, you have to follow standard of the technical support and service and the new varieties. You see, contract grow is the key players, best and standard. Standard best and science solution, scientific solution. That's a logic. And then politics just help us to translate the theoretical scientific evidence to the pragmatic outcome of profitable products. This morning, I hope each of you to contribute one idea how to improve the productivity. Translation, in any means, just the small part in the middle between the production of field from field to fork, from the land to the plate. So Let's jump out of our own box, silos, box, to think bigger and in the logical way, along with the value chain. That's scientists that you become the, I said many years ago in Chinese Academy of Sciences, if you want to become the famous scientist, useful, useful. scientist. First, you should be recognized by your fellow scientists. Second, recognized by the farmers. Third, is recognized by the entrepreneurs, because your products, your innovation, it's acceptable. And finally, recognized by the politician, because you get more support. So if you manage to get four recognition, you are a real good, useful scientist. Otherwise, you are two or three or one, like someone recognized by the science community. You are the pure scientist or book professor. If you have to get more and more, and you will get more and more real useful. Thank you. Enjoy your week. Enjoy your debate. Thank you.

Thank you, Director-General, for those great words. We'd now like to welcome His Excellency Armando Rodriguez Batista, Minister of Science, Technology and Environment of Cuba, to give his address to this session from the science ministry perspective. The floor is yours, Minister.

Well, good morning, everybody. It's a pleasure again for us to have the possibility to share with you some of our thoughts about the links of science and policy related to agrofood systems. And in our experience, there are three main things that should be taken into account. One thing is the develop of national science, technology, and innovation capacities. not only at the national, but also at the local level. I think this is crucial to foster the culture for science and innovation within our societies, our universities, our producers. And in this particular field, my country has promoted a lot of policies to have adequate confirmation of science and technology institutions. We have more than 200 institutions, 50 universities, and one-fourth of these institutions provide knowledge to agro-food systems. Another important issue is that this science and technology efforts should be wide enough to take into account all the needs, all the demands of knowledge of the societies. not only the perspectives from research institutions or universities, but also the needs of local communities, or enterprises, producers, and not only on technical sciences or chemistry or even engineering, social sciences should also have an approach. Every project we organize in Cuba, every form we provide, we try to use some indicators related to the connection within this research and the capacity from them to be later introduced in agrofood ecosystem. So this is the science approach, which I include, I want to emphasize, it also include environmental sciences. It should also include the, how to manage the risks of climate change, and we have developed, for example, as founded by the, at the national level, a, a study of the vulnerability we have all over the country related to climate, uh, climate change. on 2050 and 2100. So every municipality in Cuba has the possibility to know what will be those challenges and produce a task, a specific task to confront with these issues. Okay, this is from the science perspective. From the policy perspective, we are encouraging every legal framework that is developed in Cuba to be supported by science. This is a science for policy approach. Environmental law, science, technology, and innovation law, food security law, all these bodies are promoted to be discussed before within our scientists and evidence-based decisions should be taken into account. Yes, you have these two, I mean, two quite important aspects, national capacities on science and technology and science for policy. But how to link, how to promote the synergy? Well, for us, the third important thing is the dialogue, this dialogue between government experts and producers. And it's not only a thing for the picture or only one amongst the most important things is this participation should be linked to the real, to the daily work. So we have developed some governance mechanisms. that make sure that every important decision, not only at the national but also at the local level, even at the sectorial level, should include the participation of experts and also of producers. And I would like to highlight one particular experience, is the case of Cuban National Innovation System. It is a body that is the most important duty is to discuss. best innovation practices, not only in Cuba, but all over the world. And this body is integrated, is led by the president of the republic, with the participation of the prime minister, and with five other ministers, of course, science minister, environment minister, agriculture minister, the bank, economy. but also five distinguished experts from different fields and five successful entrepreneurs. And at this level, you discuss the most important issues related to agriculture and food security system all over the country. And finally, we have periodical meetings with scientists and experts. not only at the national, but at the local level. And it puts on the agenda a lot of things that, if you look at this from the science and technology perspective, probably you won't find out this is an important issue. But when you listen to them, it's quite relevant. And there are two things that... I think we can, you need to use them every time if you want to try to promote this connection. One thing is communication. Social communication is basic for that kind, because there are, as you already mentioned, different languages. I have to connect those languages, the perspective from the science, the perspective from government, also from producer. And the other thing is confidence. You have to nurture the confidence. In Cuban case, COVID-19 was also an opportunity because five vaccine candidates were developed by our scientists. And when those candidates were developed, some other countries, maybe you have the experience, a lot of part of the population didn't want to get vaccine. OK, because the lack of confidence. But in Cuba, almost everybody wanted to get vaccinated because they trust in our scientists. And I think it boosts the confidence in science, in scientists in Cuba, and of course, it's also an opportunity to continue fostering the connection from the science perspective, from government, and also for the producer. This is my main messages, and we really think that Every development in this sense should be rely on this true connection, and as a connection is not developed in one day. It should be a routinary day, a daily-based connection that you can trust on this. Thank you so much.

Thank you, Minister, for the comprehensive overview of the quite extensive science policy system in Cuba. So thank you. So our next speaker, and I'd like to welcome His Excellency Henry Musa Kapaka, Minister for Agriculture and Food Security of Sierra Leone, to deliver the Agriculture Ministry perspective. Thank you, Minister, and you have the floor.

Thank you very much. Good morning, distinguished guests. This is a very interesting conversation, interesting for me because, and interesting at this time for me in my career, because I come from the, my academic background is in the school of the randomized control trial group. Michael Kremer, who is a Nobel laureate for being one of the proponents of that, was my advisor. I was assistant to him. And in fact, now he's appointed as chief economist at World Bank, so a nod to evidence for decision making. Having done that, having been a warrior in that space, I happen to be now the Minister of Agriculture and Food Security in the government of the Republic of Sierra Leone, where my job is to make decision, where I have to act. And I do that in a space where there are really three spheres operating in that governance environmental mechanism. There's always the technical wing, which generates the evidence, if you like. I travel with my director of planning and evidence and data. He's sitting in the room. And there is the administrative wing that is headed by the permanent secretary, those of you that know the governance mechanisms. And then there's the minister or the ministers that are the political sort of head of these institutions. Each of these entities see evidence and data for action very differently. So the notion around lost in translation, I see that every day when I operate. I've also come to learn, there is a, we can use data. We can actually use data only when it's not contentious, when it's not contentious in the way of you're taking resources from me to the other group, or when it's not a, I don't know, some people are tied to certain ideas, right? But when it's just genuinely... developing evidence slowly over time, repeatedly, in a structured manner that doesn't seem to threaten anybody, we can generate that evidence. And then we have to look for that opportunity to sip that into decision making. It's really what I've found to be very, very effective. So when I took over as minister, of course, we needed to know baseline of where things are. And we had a strategy, and I insisted on having key indicators on each of our targets. We want to reduce importation by this amount. We want to see our yield increase from this to this amount. We want to see growth in exports. We want to count the dollars. Now, establishing that baseline is always a problem because all of a sudden there's an implication for the previous guy and all of that. So that's a challenge. So then you can, there's lots of ways you can do that while providing and pushing that information out there. And owning even that part of the process that you are not pushing it, it's not yours, it's ours. This is where we are starting. So we did that. And then we have to institute in a way, in a routine manner, without people noticing that what we're actually trying to do is generate evidence for these things that we're saying. I've had to fight a lot in government. Like I said, I'm coming from the group where we did randomized control trials. I did my PhD at LSE and did fantastic econometrics work. So really, that's where I was coming from. But I've come to also know that sometimes, just by bringing your data and evidence, like, here it is, let's do something with it, and you match with it, it's not going to cut it. Because the politician is going to say, what does this do for me? I have so many other things I have to think about. And if you don't take that into consideration, you are not going to act as a policymaker. I have to admit that we've done a lot of good work, but if it was just us as technical people, maybe we'll have done even better. But I will say, oftentimes, we do, you know, second-best solutions are not bad. when you are in certain situations. And you have to do that because you have to compromise. And sometimes our science and scientists and data, I think, the spirit of compromise is not a thing that we think is worthy of undertaking in this context. But if you have to act and do something, you have to do that. And that's what I found. coming from that space where if you don't show me, I always ask these guys, where is your control? I ask them actually, just these days I do it for fun, but they will tell me, and I know where we ought to be, and I know what's going to pass, what's going to move when I engage my colleagues, when I engage other agencies, when I engage, I know what's going to pass, but I know that this is where we ought to be. And that's how we make progress. And so in Sierra Leone, we've done quite a lot in just building evidence that is going to be structural to support the space. We came, we used to just give fertilizer without really knowing our swells. We hadn't done our swell mapping for 40 years. I insisted that we must do that. We've done that. We've digitalized that. We passed a policy, a broad policy, by the way, around biotechnology. I framed it that way because then people are going to fight me, which they did, because we ought to use, we can, there are a lot of ways to use technology to increase yield, to stop pest and diseases that our farmers are facing, using biotechnology. And the places where we import food from, that they do, but our folks don't know that the moment we passed that, it was a big outcry. but we left it as a general thing. And so for me, really, I think there's a way to move science and data and innovation into the food system space. It's to make it be structural, make it be part of the everyday actions that we take in a way. You will find challenges when things are contentious. Look for the compromise, because you have to, as a minister, people are asking me every day, whenever I go on TV, why is the price of rice still high? Why is onions not available? When I sit in my office, I'm trying to solve that problem. I could wait for scientists to develop the best varieties that are out there, but if there's existing ones that we can tweak and keep moving, that's what I have to do. So I have to compromise so that I can act. And so the question of what's sitting between the evidence that we have and action, I think part of it is... These three areas that I've called, the scientists, sometimes we can be too hanging onto our evidence that it must be this and nothing else. And the world actually is never like that. The world is never like that. Really, when it comes to what matters, when it comes to what people are talking about, it's really never like that. And so finding how you move people, so advocacy is key. so that you can act and get results and track it and send it back to, by the way, because we did that, that's how we were able to move. That's how people will be open to more evidence, data for driving change in the food systems. So those are my thoughts, my experience, fascinating topic. I'm still on the journey and learning, but that's how I address this issue in my day-to-day as minister and still as a technical person, because I do engage the guys in the processes. I wish you a great deliberation and thank you very much.

Thank you, Minister, for that rather superb, reflective and honest overview, really, of the challenges and opportunities of translating evidence into actions and policy. So thank you for that. So please, a round of applause for the important messages from the Director General and our ministers. So we've heard from the ministers, we've heard from our director general, and clearly science policy interfaces, they are the channels that connect scientific evidence to the decisions governments actually make. And these interfaces, they exist really at many levels. We have global science policy interfaces, regional, national, and indeed subnational. and across every sector and agriculture among those, but never agriculture alone. So the opportunity to strengthening our science policy interfaces is what this session is really focused on. And perhaps the most concrete expression of a science policy interface, the one a government actually leans on when a decision is due, is its national agri-food science advisory system. And this is where I want to spend just a few minutes before we come back to the global level. I'd like to thank the Director General for grounding us in why this matters at the highest level. I'd like to thank you, Minister Rodriguez Batista, for the view from the Science Ministry, and Minister Kapaka for the view from the Agriculture Ministry. As ministers, you have really shown us something important. Science advice to government is not one office, and it's certainly not one person. It's really a system, or indeed it should be. And the real question we face this morning is whether that system is a well-oiled machine or simply some set of disconnected parts. Every single FAO member state has a science and innovation community. You have universities, research institutes, academies, professional societies, private sector, NGOs, farmers' organizations, grassroots innovators, and so forth. So science and innovation expertise and talent exists almost everywhere, and the opportunity we have is to better connect it systemically into the decisions government is making. There are different examples of what a well-oiled agri-food science advisory machines can look like in practice. not a single advisor in a room that perhaps is rarely called upon, but a system of interlocking science advisory bodies across sectors and ministries deliberately connected to one another. In Japan, we have the Council for Science, Technology and Innovation, which brings government scientists and civil society into the same room. In Canada, we have the Federal Chief Science Advisor's Office alongside a departmental network spanning agriculture, health and environment. The European Union draws on Sapea, which is a consortium of over 100 national academies. So not a lone expert, but science advisory committees and networks built to interact and work together to guide government decisions, investments, and actions. So our agri-food science advisory structures need to sit inside national systems like these, not outside or beside them. This matters most at the national level, where an action where an action can become a budget line, a regulation, a decision that a minister signs, that you sign every day. China channels its agri-food science advice through the Chinese Academy of Agricultural Sciences, represented this morning by Professor Sun Tan. The UK DEFRA runs its own science advisory structure, represented by Justine Becher. And ICARDA, led by Dr. Nizar Haddad, who's in the audience here, connects national dryland agricultural systems globally. The global level of science policy interfaces also matters, interfaces for science policies that every country can negotiate from at the same table. We have the Intergovernmental Panel on Climate Change on climate. We have the Intergovernmental Science Policy Platform on Biodiversity and Ecosystem Services for Nature, and the Committee on World Food Security's High-Level Panel of Experts, one of whose current members, Cecilia Elizondo, is joining us this morning. So science policy interfaces, they're not abstract theoretical concepts. They're really core to FAO's business and FAO's own strategy. Our FAO's science and innovation strategy aims to strengthen science policy interfaces at national, regional and global levels for greater policy coherence and indeed shared ownership. My own office within FAO, the Office of Chief Scientist, carries that mandate forward in practice. And through a joint effort with CIRAD, we have been building a shared framework for assessing how effectively a science policy interface ecosystem is actually working. And that's a tool you'll get a glimpse of before this session closes. Systemic strengthening of science policy interfaces across all FAO member states is really high on the agenda of my office, working closely with partners and member states to improve the functioning of science policy interfaces, our agri-food systems. The purpose of linking science bodies together at a national level is coherence, weighing a country's social, economic, and environmental goals together, rather than each ministry optimizing its own slice of the picture while possibly contradicting the others. So here is what I'd ask you to listen for in today's session, not whether your country has a scientist advising government somewhere, almost every country does. but whether what exists is a genuine interlocking system that is well oiled, is a well oiled agri-food science advisory system that is helping to advance the national goals. You will hear from seven different science advisory systems, models and sectors, short number of minutes each, followed by a test of some comfortable myths that exist around science policy interfaces. So at that, I'm going to hand over to my colleague, Dr. Preet Litter from my office, who will take it from here. Thank you very much.

Thank you, Charlie, and also to everyone else who set the scene so nicely before. Good morning, everyone. And I think I don't need to tell this room that the challenge today is not a lack of science. Robust evidence is generated every day across agri-food systems. The challenge really is ensuring that knowledge becomes actionable, informing decisions, investments, and implementation at the speed and scale that is required. I'm delighted to welcome today our panelists, so please come and join us on stage. Dr. John Roche, Prime Minister's Chief Science Advisor, New Zealand. Dr. Justine Betar, Deputy Chief Scientific Advisor, Defra, United Kingdom. Professor Sun Tan, Vice President from the Chinese Academy of Agricultural Sciences. Dr. Cecilia Elizondo, Steering Committee Member of the High-Level Panel of Experts and ECOSUR, Mexico. Ms. Claudia Martinez-Zuleta, Country Director, FOLU Colombia and Executive Director of E3. Dr. Greet Manhout, Deputy Director, Directorate D, Sustainable Resources, European Commission Joint Research Centre. And Dr. Nizar Haddad, Director General, ICARDA. Now, the title of the session today is quite apt. Lost in translation, is evidence lost in translation? And as the DG reminded us in the morning, translation is not simply a communication task. We know science and evidence, or evidence really doesn't move in a linear pathway from science to policy. Instead, it is interpreted through institutions, through values, through political priorities, and also sometimes competing social objectives. So I'm going to ask today our distinguished panel one question, and I encourage you not just to highlight what has worked, but I think it's really important to understand what remains difficult. So, Dr. Rosh, we will begin with you. What feature of the New Zealand advisory system most improves the chances that evidence actually influences government decisions, and what still does not work?

Good morning. Thank you, Madam Chair. I suppose what works best in our system is that we have a network of chief science advisors, as has been described earlier this morning as well. So our major policy ministries have science advisors, and many of them are actively involved at the executive or the senior leadership level. So that works exceptionally well. The more experienced the scientist is with government policies, the more effective that they are. So an academic coming in out of a university expecting to change how government operates, as the ministers have previously described, is going to have very little impact. So understanding that policy is complicated. Albert Einstein is reputed to have said that politics is more difficult than physics, and that's because politics has to deal with people, and physics generally doesn't. So that's one of the challenges, but we overcome that by having experienced scientists that are experienced in government in many different ministries. Myself, as the Prime Minister's Chief Science Advisor, I have the opportunity to bring those science advisors together as a network, which enables us to learn off each other, discuss complex topics with each other in a closed and safe environment. And the other thing that works very well is where that chief science advisor is positioned at the upper echelons of the ministry. Because where it doesn't work so well is where the chief science advisor is buried down in the ministry. And they become very operational in that situation, just going through the routines of actually being a ministerial scientist rather than a science advisor. So as well as being the prime minister's chief science advisor, I'm on the senior leadership team of the Ministry for Primary Industries in New Zealand. I've held that role for the last 8 1/2 years, and so I'm actively involved in the ministry strategy, all executive discussions. I have a very strong relationships with my deputy director generals, and that enables me to be active at a strategic level while still getting involved in the operational science as well.

Thank you, Dr. Roche, and also for highlighting the network of science, experienced scientists, and where the chief scientist advisor is situated. But yet, sometimes the evidence does not point neatly in one direction. So let me move to Dr. Beda. How do you reconcile situations where agriculture, environment, and economic objectives point in different directions?

Thank you, thank you very much. That's a very good question. But before I start on that, I think it's quite apt that this session is called Lost in Translation. And just to be clear, my name is Justine Bata. I'm not quite sure who this person is that's in front of me. I think that's quite good. So yes, something lost in translation. So apologies to the person whose beautiful picture is up behind me. But to go to your question about how do we reconcile, where different information is pointing in different directions. Actually, that's something that we deal with quite frequently. So in government, we frequently have to make decisions on an evidence base that is incomplete, that is contested, and sometimes does point in different directions. And part of our role is actually to support ministers to help them make these decisions, because as it's been mentioned times already in this session, ministers are having to balance not only the scientific evidence in front of them but the economic evidence, the information that is coming from social research, from legal considerations and other considerations as well. So I think as our role, what we need to do to make that really effective is we have to be exceptionally clear on what we do know, what we don't know, what the confidence we have in our evidence bases, and also the consequences of those decisions. And I think trying to make this come to life a little bit as an example is I'd like to tell you a bit about some of the work that the systems research program, which is a program that I run within my team. It was launched in 2019 and looks at a range of different programs. But one I think that would be useful for this audience is we looked at land use, food, and environmental transition as a connected whole. So to do that, we ran a series of workshops that included scientists, academics, policymakers, farmers, land managers and others, brought them all together really to try and understand what their aims were, what their assumptions and constraints were, but with the aim to identify what was the desirable and impactful change that could be realised through this mechanism. And what I found what was really interesting was actually it did reveal conflicts between agriculture, environments and economic objectives. But in many ways, that wasn't an either-or. With some shared evidence and delivery insight, we could reframe and sometimes align those objectives. And at the best of that, what you get is not just a balancing of those tensions, but you can actually find where those sectors work together to reinforce themselves in a mutual way, but it does often come to a point that tensions do remain, and I think we have to be real and recognise that. And what that mechanism allows you to do is to identify where those certain trade-offs are, where the uncertainties are, and where the evidence gaps are, because that informs your next steps. So you can distinguish those to help with the policy design, to design further research where it's really important, or to set out the stall quite clearly to help ministers inform their political judgments. And the so what of this is, as a direct result of that work, we've shaped the UK's land use framework and our food strategy. And I just wanted you to come away with the idea of actually systems thinking, it can't remove hard choices, but can help you reconcile what's really important and where to focus attention into a system. And it gives us an approach to look at a complex system. And our natural environments are always complex systems and a way to support informed decision making that optimizes good outcomes, which I think everybody in this room, that's our shared objective that we all want to get to. Thank you very much.

Thank you, Justine. First of all, apologies for the wrong picture, some crossed wires there. But thank you for highlighting that a critical role actually of science policy interfaces is not to remove disagreement or eliminate trade-offs, it's to make the choices and the implications of those choices very clear. Great. So now we turn to the supply side of the interface, particularly the role of major scientific institutions. Professor Tan, I'll direct this question to you. How do large scientific institutions ensure that evidence remains useful and relevant for decision makers and it doesn't get disconnected from what the policy needs are?

Okay, thank you. As you know, we keep producing scientific evidence for decision making, but the institutional mechanisms to translate science into effective policies and tangible impacts often remain weak. The science policy interface may become a bottleneck. instead of a driving force for agri-food system transformation. Uh, I would like to share briefly China's experience, reflections, and, uh, suggestions for building robust scientific advisory systems. to embed scientific evidence into policy making, we follow demand-driven and innovation-driven principles. You know, innovation, we have to embed innovation chain into the industry chain. But we also remember innovation could start new technologies, technology, new possibly new model, new industry. Since 2007, we have launched 50 modern agriculture industrial technology systems to allocate innovation resources across value chains. Uh, we have developed, uh, multiple expert advisory, uh, bodies, uh, top scholar panels for high level policy, uh, advice, and, uh, technical communities for high risk areas, such as GMO biosafety. Uh, we also set up 18 industrial export panels covering the full agricultural production chain. Every year, uh, experts conduct field surveys in key growing seasons, uh, generate, uh, evidence-based judgments, offer technical and, uh, policy recommendations for governments and, uh, farmers. and the scale technologies will field demonstrations and training. CAS has built agricultural think tanks and integrated cross-sectoral data to create a unified traceable repository of scientific evidence hyping brick dates, fragmentation, and avoid conflicting policies across agriculture, environment, health, and trade. We also identify common country constraints shared by many countries. First, research incentive systems still prioritize papers and patents. Uh, policy otherwise their work is under valued, relying largely on scientists' voluntary commitments. Second, the science policy connection is mostly one way. We supply evidence well, but lack stable routines to capture policy needs with few, uh, continuous feedback mechanisms. Third, cross-sectoral boundary spanners are insufficient. Complex challenges like climate change and zoonosis demand interdisciplinary work, yet, uh, yet disciplinary silos remain, and coordination often depends on personal networks. Here are four recommendations. First, the top-level design to establish permanent, transparent national scientific advisory systems, linking international scientific assessments with domestic policy priorities. Second, develop a shared cross-sector evidence base with consistent traceable standards to reduce policy contradictions. Third, boost the policymakers' capacity to use science is very important. We propose releasing the science policy interface assessment report and learning materials at this conference to train practitioners and support developing countries. Fourth, safeguard the legitimacy, independence, and inclusiveness of advisory bodies, guard against vested interest influence, manage conflicts of interest, and incorporate knowledge from smallholders women, youth, and the local communities to leave no one behind. Uh, KESS stands ready to deepen practical cooperate- uh, cooperation with partners worldwide. Uh, thank you.

Thank you, Professor Tan. And what you actually said transitions very nicely on what I wanted to ask you, Cecilia, because the science policy interface also depends on how different forms of knowledge interact. And I think in particular from your experience, how can SPIs bring scientific evidence and indigenous people's knowledge and local knowledge into constructive dialogue? And this is especially important when perspectives differ.

Thank you very much, Preet. An honor to be here. So I'm going to answer this from the evidence that we have from the report 21 that we are presenting next week in the assembly of the CFS. The first thing an effective science policy interface should do is ask, is this actually a conflict, or is a different framing? Our reports found that many supposed conflicts disappear when Indigenous people knowledge is recognized as science in its own right, not a compliment, not as something to be validated by conventional science. Let me give a concrete example. In the first case in Norway, Europe's largest onshore wind farm was licensed on a land of the Sami, where they rely on a winter pasture for reindeer herding. The Sami had observed over generations how the cumulative effects that the turbines and infrastructure would make herding an evil. So the scientific assessment had not captured this. In 2021, the Supreme Court of Norway ruled that the licenses violated the Sami right to enjoy their own culture. So which knowledge mattered here? Both. but only one had been heard. The conflict was not between science and indigenous knowledge. It was between evidence that was included and evidence that was not. The semi-knowledge was not less rigorous. It was simply not part of the process. So what should an effective science and policy interface do? Three things. First, it should not resolve the conflict by choosing between knowledge systems. It should create the conditions for dialogue without subordination, free, prior, and informed consent, indigenous governance of indigenous knowledge, and no obligation to co-create or to cede governance. Second, it should recognize indigenous people as right holders and knowledge holders. not simply as stakeholders or informants. Third, it should recognize that exclusion degrades decision quality. When Indigenous voices are absent, we lose not only legitimacy, we lose evidence. An effective science and policy interface does not treat indigenous knowledge as a scale holders view to be balanced against science. It recognizes indigenous knowledge as legitimate basis for public policy, in addition to not subordinated to conventional scientific evidence. Thank you.

Thank you, Cecilia, and also for that powerful reminder about inclusion and framing, right? Because the question of whose knowledge counts is also closely linked to even who has the opportunities to shape the questions in the first place.

Exactly.

Yes. So once we start to look at knowledge systems in this way, I think the next question is, who is present? who is absent. So I'll turn to Claudia. Whose perspectives are often underrepresented in agri-food policy and science policy processes, and how can their inclusion actually contribute to more informed and effective decision making?

Thank you, Preet, and thank you for the invitation. Happy to be here. So who's systemically excluded? Small farmers, indigenous people, women. young people. I'm very glad to be here with so many young people around because this is sort of a different ambience. Consumers facing food insecurity, agri-food SMEs, territorial practitioners, people holding practical knowledge in the field, but with limited influence over research agendas and policy decisions. So I think we need sort of a systemic perspective. We're still working in silos around the world, food systems, connect agriculture, ecosystems, climate, nutrition, markets. And I wonder, are there any, for example, doctors in this room? No. Sometimes we need to really decide decisions with systemically proven sort of stakeholders in the room. So what happens to decision quality? We risk producing technically sound policies that fail to reflect territorial or sectorial realities. We overlook trade-offs and interdependencies between food, health, livelihoods, climate, biodiversity, et cetera. Solutions may lack legitimacy, trust, feasibility, ownership, So who defines what is important to research, which is the main question? I mean, scientific interdependence is essential. We spoke about it yesterday. Preet, you were in that panel, sort of chairing that panel. But who decides which questions receive funding and attention? Are research priorities responding to society's needs? or disproportionately to the interest of those who fund the research or are politically influenced, no? So I have, for example, an example when I was Deputy Minister of Environment, very young in my life in Colombia, we had to face this decision about spreading Fusarium oxysporum to eradicate coca plantations in Colombia. And at the time, we didn't have the research in hand. And I remember looking for all the scientists around, what happened with Fusarium oxysporum to eradicate cocaine in Colombia, and nobody knew. We took the decision not to deploy Fusarium with that government, but the next government decided to deploy Fusarium. And now we're seeing the consequences on food systems throughout Colombia. And I wonder, was the research ready? Were we acting? driven by science. Lastly, I think we need to jump from consultation to co-creation. I have been working with the Food and Land Use Coalition in Colombia, deploying these diagnosis of food systems that are contextualized to the departments in Colombia. We have 32 departments. And it's not like one size fits all. We have to go very deeply into the regions to understand the ecosystems, the society, and et cetera. And we bring together science, academia, civil society, governments, farmers, businessmen to sort of do a theory of change of what will happen with food systems in the future and how to act correctly today, no? And I think that we need to bridge these coalitions at the very territorial levels in the world, because we need to act together in shaping science, but in shaping also policy decisions for the future. And again, we're together in the Nexus Action, where we connect science, policy, and society And we nurture collective learning. And I think collective learning is so much needed, because we learn from each other. So we need to connect global, national, local scales. We need to foster dialogues. We need to learn from each other. We need to coordinate science policy interfaces. So thank you.

Thank you, Claudia. And Thanks, Rali, for emphasizing that inclusion is not just about representation, but also about improving the quality of the decisions. Now, I think the next challenge is that even when diverse actors are involved, there are significant challenges. across multiple sectors and institutions. And I think I'll turn to Dr. Manhout for the next question. So we have a lot of evidence on growing interactions between agriculture, health, environment, trade, and finance. But still, cross-ministerial coordination remains a persistent challenge. So what can be done about that?

Yes, thank you. I see three major challenges for bringing the science to policymakers. The first thing is what we say, the fear to miss out something. And you have now even AI at the fingertips of everybody, but sometimes this is even distracting from the main problem and not always giving the focus. And so our scientists need to bring often more time, spend more time in bringing this back. We want, of course, to have balanced information, synthetic information, and that in a timely manner. But with more information, you often enhance rather this fear of missing out something. So we need to bring people together. We need to acknowledge as well that scientists are not making the decision. It's the policymaker who is making the decision. And I would like to share here a small anecdote. I was going to a former commissioner for climate action with my scientific figures and facts. And he said, great, this is perfect to address the head of the people that I need to see. But making policy, I need more than that. I need to address three things. I need to address as well the heart of the people, because the people will need to be convinced, they need to love it, this measure, because they will need to implement it. And finally, thirdly, we need as well to address the stomach, because it needs to feel right, because I will not be able to address all people. Some people will be left out without that I talk to them, and it needs to feel that this measure is also digestible by them. They might not love it, but they need to not suffer too much from it. And so this is what we need to take into account, that every policymaker might have his own cocktail of arguments for going into a certain way. Now, coming on a more timely manner, this is what is... probably one of the biggest challenge. And there I think I would like to illustrate how at the European Commission, we believe that we can shorten a bit the policy cycle by having the anticipatory phase shorter, by bringing more diverse people together. And that is the beauty of science, because you can bring different policies, different disciplines all together, social economists, also environmentalists, and you can bring different policymakers together, the health policy, the humanitarian aid, climate, environment, agriculture, all different policies in the same room from the beginning, so that the iterations and the discussions are happening in the beginning, not after one policy has been worked out already a part of the policy. And that is what we like to do with these inter-service groups. at the beginning of a policy cycle. It's A participatory approach that, of course, is from time to time weakening a little bit some policies. But in the Commission, we have as well a second habit to bring as well packages of policy proposals in the negotiation phase together, so that there is something in there for everybody, some Member states might rather go for more support, one less profit from another, but if you have something in for you and something less in another. part of the package, that is still fine. And this is what we do now in also our knowledge centers at the Joint Research Center, the scientific arm of the European Commission. We have for these knowledge centers inter-service groups, and they are getting information on a monthly basis, even with newsletters, also like, for instance, on the El Nino, we have these short science for policy briefs, so that people feel they are informed. They are as well involved, and that creates transparency and trust, and then probably as well easier decisions and a faster policy cycle. Thank you.

Thank you, Greet. And what you've really highlighted is also what is in the SPI literature, the principle of iterativity, right? This continuous dialogue and engagement that builds trust. So our final panel question is to Dr. Haddad. Maybe we'll ask him something related to the title itself. What gets lost most often in translation between global evidence and national decision making?

Good morning, everyone. Do you still expect that I will be able to address this question after two ministers, one DG, one chief scientist, and seven? One of the most important things that I see that in many occasions, we as international organizations, yes, we think globally. However, we lack the implementation locally. We have very nice modalities, very nice situation analysis, very nice understanding of the status quo, but we do not lack evidences. We lack, in many occasions, the decision to implement the evidences. This is the first one. The second thing is the framework that we are using. Are we understanding the needs on ground, or we are not understanding the needs on ground? We understand globally the status as international organizations, as think tanks. But in many occasions, we are trying to drive a fancy car in a plowed field, not on the street. We develop the best tool that the farmer cannot use. Or it is wonderfully working in Malawi, but it would never work in Malaysia. Or it might work in dry land, but it would never work in another area which is also dry land. Therefore, I'm really very proud that I've been part of the FAO, been part of the private sector, been part of the national institutions. So I did go through all that. In my career, I saw the most successful implementation happens when international agencies come humbly and listen first. Once we listen to the farmers, to the national research centers, to the national stakeholders and start implementing, then we can address the needs on ground. This is one. Two, something like about 25 years ago, I heard the first time this terminology, farmer participatory research approach. Farmer participatory research approach, and it was presented to the MENA region and the C1 region by ICAR at that time. I was a junior scientist. I was working in another field, but ICARDA was able to transform my career early at that time without having the intent to start working with ICARDA. How you can do that? If you have your shoes in the field, if you are standing in the field wearing the shoes of the farmer, understanding his needs. And there is a very important tool which is used by FAO, which is farmer field school approach of knowledge transfer. So it's always understanding the culture, understanding the ethics, the philosophy, the people's need, and try to address them in the way they understand it. You cannot use a plug which you use in the States to use it in England. You need an adapter. Likewise, any international knowledge need to be adapted to the local understanding. I hope I could conclude something after all those wonderful brains presented what they presented. Thank you. I left my notes downstairs because they are not helpful after all those people.

Thank you, Dr. Haddad. And indeed, that was a fitting point to conclude this first panel. Now, in the interest of time, we are running late. I'm not going to try to condense some of the threads emerging. But I think what is really coming out strongly is that strengthening SPIs is not just about a supply of evidence or focusing on individual organizations. It's really about strengthening the entire ecosystem of how knowledge is produced, how it is brokered, how it is interpreted, and ultimately put to use. And this is, I think, precisely the perspective that also informs the joint FAO-CIRAD assessment framework. And I'm really delighted to bring on stage my collaborator, Dr. Salim Louafi, Deputy Director of Research and Strategy at CIRAD. Salim, you have the floor.

We have to hurry. Thank you. Thank you, Preet. Good morning, everyone. So I will be-- So just to start, just to say that this work is building on the longstanding collaboration between FAO and CIRAD, and it has already produced a guidance document that has been published in December 24 to strengthen science policy interface at the national level for food system transformation. And that was piloted in different countries through dedicated workshops. So this work will also feed an ongoing multi-institutional global initiative on science policy interface, the Nexus Action Montpellier process supported by IDRC, and that aims also at enhancing collective learning on science policy interface. So based on the piloting work that I've mentioned that we've been conducting in various countries, and also on the literature on science policy interface, we can identify several challenges. and pitfalls that are usually observed in the way science and policy interact. To present these pitfalls, let's imagine policymakers in a given country X who are deeply committed to using the best knowledge available to establish a national transformation pathway for a food system. And determined to get it right, they launch an ambitious, national initiative, yet despite genuine goodwill and substantial funding, the effort quickly hits a wall because it falls into five common traps. The first one is the mono-sectoral trap. The decision makers hand the lead only to one ministry, usually the Ministry of Agriculture, treating agri-food purely from a sectoral challenge while ignoring its deep interconnection with health, with the environment, with trade. The second trap is the monoscalar trap. The teams drive to high-level national policy in the capital, designing top-down directives without really integrating local municipal realities on the ground or aligning with international commitment like the SDGs or the NDCs. The third trap is the linear one. They treat science as a one-way delivery service commissioning a massive 300-page scientific report and expecting policymakers to simply read it and implement it, omitting any iterative dialogue or joint problem solving. The fourth one is the exclusive focus on expert knowledge. And here, the advisory council invites only senior academic, agronomist, economist, completely excluding other knowledge holders and systems. And fifth, even if the initiative convene a multi-stakeholder forum, it does so under the naive assumption that all voice carries equal weight and blind to political power imbalance that has an impact on which voice is being heard and policy option and on the policy option that are eventually selected. So to address these challenges, Uh, with the LOF, uh, framework centered on three major shifts that has already been, uh, mentioned during the discussion, first from isolat- i- isolated science policy interface, moving from really individual, uh, looking on only at individual organization to looking at the, uh, whole, uh, SPI ecosystem. emphasizing the diversity of actors and institution involved in knowledge policy interactions and the critical need to strengthen the connection between these different players. The second shift is from science to knowledge. We've already covered that in the discussion, but although the dedicated word we are referring to is science policy interface, it's important for complex and weak problems such as food system transformation to rely on different types of knowledge systems who may actually inform policy. And the third one is moving from the linear model to the co-production approach, moving away from a supply approach to a more collaborative processes in which researchers, decision makers, and other, uh, knowledge holder jointly frame, uh, problems and, and generate, uh, knowledge. So let me now hand it over to, to Preet, who is going to present the, the framework and the key takeaway message coming out of this work.

Thank you, Salim. And I'm going to rush through this because I know we're very late on time. This will be published shortly so you can peruse at it with your leisure. Now, the framework, this overview of the diagnostic framework basically has four elements. We have actors and organizations, the intermediary roles they perform, the knowledge pluralism aspect, and also the spaces and processes. And our central proposition is that when these four elements are present, connected, and adequately resource, you can strengthen the SPI ecosystem. Actors are really the heart of this framework. So really, we want to know who is present, who participates, who is absent, the people who are participating, what are their capacities. For intermediary roles, what are the actions that connect knowledge and decision making and practice? Who performs them, with what mandate, what resources, and what roles are absent, not being performed? Knowledge, whose knowledge is recognized, used, and exchanged? How is a holistic view of agri-food systems assembled, and what is systematically missing from it? And finally, how is this multi-actor collaboration enabled? Who sets the rules of engagement, and how could these processes be strengthened? And then, of course, for each element, our forthcoming report also talks about some design features as well as assessment criteria. And again, we say when these four elements work together, they create pathways that can shift societal narratives, enable the co-creation of knowledge, amplify ongoing policy processes that can actually drive change, and then transform the behaviors of the actors. And just a few key takeaways. So you really have to look at the system because assessing one single organization does not tell you much. What really matters is if the knowledge producers, the users, and the intermediaries are connected, and more importantly, whether those connections hold when decisions have to be made quickly. Widen what counts as knowledge. We've heard this multiple times today. Scientific evidence remains indispensable. However, much of the knowledge for agri-food systems is held by small-scale producers, processors, indigenous peoples. Intermediation work should be mandated and funded because boundary work, facilitation, synthesis, translation, it does not happen spontaneously. If it is underfunded or informal, when those individuals move on, those connections also disappear. Anchor the ecosystem in existing policy processes. So we have the National Food System Transformation Pathways, the NAPs, the NDCs, the NB-SAPs. All of them offer strong entry points because it's more effective and also considerably cheaper to connect to ongoing policy processes. And finally, assessment is a means, not an end. What we really want to do is open a structured conversation about where the gaps are and what a realistic next step could look like in a country. Now, this framework also highlights an important reality. So even when you have the institutions and the platforms, if you want effective science policy engagement, it really rests on the skills and the capacities of the people who produce knowledge, who interpret knowledge, broker knowledge, and also use knowledge. And it is in this spirit today that we are very pleased to launch the FAO e-learning course on strengthening national science policy interfaces for agri-food systems. This course really has an introduction to what the core concepts of SPIs are, what they are, why they matter, and also how they operate across sectors, across knowledge systems, and also across geographic scales. So the QR code is here. Please do take this course and share it with your colleagues. And with that, I'm going to hand it over to Salim for the myth-busting section. And I'm sorry, we'll really have to rush through it. Thank you all.

Thank you, Preet. Thank you, Preet. And it's my pleasure to moderate the concluding panel as we explore common-- we will be exploring common assumption and myths surrounding discussion on science policy interface. So in this myth-busting round, I will be asking our panelists to challenge some of these familiar narratives and share what their experience tells them about what really makes science policy interface work. So let me first turn to Dr. Justine Begja to provide us with her insight about the first following myth, if evidence is robust enough, policymakers will act on it.

Thank you. Is this on? Perfect. Well, policymakers are people, so we're all people in this room. So shall we try some audience participation? You have a decision in front of you. Is your only factor that you're going to take into account evidence? Anyone put their hand up? No, I'm in exactly the same place. Evidence is a really, really important component of that. It has to be timely, it has to be robust, it has to be quality, it has to meet all of the things that we've spoken about as a panel today, but that is not enough. It has to be articulated well. So what I would leave people with is that it is such a powerful tool, but it must be wielded and that takes skill and that takes training and that is our challenge. Thank you.

Thank you, thank you, Justine. Then let me turn now to Cecilia, Cecilia Elizondo, to comment on the following statement, scientific knowledge is the only knowledge that matters.

Okay, thank you. I'm going to run also. The myth says that conventional scientific knowledge is the only knowledge that matters. I want to suggest that this myth is not just wrong, it's dangerous. because it leads us to ignore the very knowledge system that have answers we know-- the answers we now need. Our report review evidence from different countries, Inuit communities in Canada use 79 plants and animal species, the in Peru, 223. And in every case, these health and nutrition outcomes are better than national average. But this is not just about better data. It's about a different kind of knowledge. The report concludes that indigenous knowledge systems are independent and valid in their own terms. They are built through generations of observation, experimentation, and adaptation. They contain rigorous concepts, methods, analysis, and synthesis that they are expressed through storytelling, oral stories, ceremonies, and land-based observation, not through peer-reviewed journals. But that does not make them less scientific. It makes them differently scientific. Recognizing this is not a concession to political correctness. It is a recognition of evidence. Thank you.

Thank you. Thank you, Cecilia. Let me turn now to Claudia. And Claudia, how do you react if I tell you that SPIs are a neutral space?

So the audience, who thinks SPIs are neutral? No one? Me neither. So they are shaped by power and interest. Scientific interdependencies is essential, but the priorities surrounding research are not necessarily neutral. Policymaking does not always wait for science. Politicians, and we have several in the room, face pressure to act, deliver results, and respond to immediate demands. And they make often decisions without sufficient evidence. Science must be communicated in ways that help decision-making act in time. And obviously, you know, evidence does not automatically become action. You were speaking about El Nino, for example. I have heard about El Nino in many rooms during these three days. We have the sufficient evidence of El Nino. Are we taking the right decisions? Are we acting on the Nino? It's never neutral, no? So what needs to change, I think, Selim, to translate evidence into concrete options, responsibilities, investments, actions, while learning and adapting in the changing condition.

Thank you. Thank you very much, Claudia. Finally, Dr. Roche, would you agree if I say that the biggest problem is the supply of evidence?

No, I wouldn't. And I think the best example of this is in vaccine hesitancy. We have a growing vaccine hesitancy in the world, and the one thing you can say is that there isn't a lack of evidence to suggest that vaccines reduce the likelihood of death or serious harm from some of our communicable diseases. Yet, every parent that decides to vaccinate their child and every parent that decides to not vaccinate their child care for their children. So it's not a lack of evidence. Where it comes down to, in my opinion, is that it's a lack of trust. And Simon Covey, the author of Seven Habits of Highly Effective People, one of his famous quotes was, you seek first to understand. And a recent survey of around the world, 78 countries, suggested that about approximately 70% of people still have trust in science, but only 40% of people believe that scientists listen to other people's opinions. And that is really the challenge that we've got, is to seek first to understand our audience to be able to provide the right evidence contextualized to the need.

Thank you. Thank you very much. And I think without -- thank you for -- all of you for those very insightful response and comment. And I will hand it over to Charles for his concluding remarks for this panel. Thank you very much.

Thank you, Salim. So let me try to pull together really the overview of what has been discussed this morning. So essentially, I think what we've seen is it adds up to something that is more than the sum of the parts. That's what we can consider that. Across the seats on the panel, from Wellington to Beijing, from Chiapas to Ispra, from Beirut to Bogota, A few threads kept resurfacing no matter what science advisory systems anyone was describing. Firstly, there is no one-size-fits-all model. The models for agri-food science advisory systems have to work within the governance and the political systems of each country. But they must be embedded if they're going to be useful and effective. The minister from Cuba highlighted that trust and independence of science often matters more to whether the advice is acted upon than the technical quality of the advice itself. And the minister from Sierra Leone revealed to us that the pathway from evidence to action has to take into account compromise. The best may not often be feasible. The fancy car in the plowed field. And the question then of whose knowledge counts has to be considered. And that's really fundamentally a question of inclusion and representation. Who has a seat at the table before a decision is made earlier rather than after is not a side issue to science advice. It is a critical issue. Then the point of cross-ministerial coordination and trade-offs, it will always be a challenge, but it must be faced by inclusive dialogue to navigate the tensions and identify the no regrets pathways forward. We have a visual harvest on the screen of all that's being discussed today, so we'd encourage you to take photographs of this, take it home with you, it's a good synopsis of today's session. session. So where does this leave us? We came into this room with a number of things we wanted to achieve. We wanted to name what effective science policy interfaces for agri-food systems actually look like, global, regional, and national. We also wanted to consider the real variety of agri-food science advisory structures that already exist and to acknowledge that none of them is a simple template that any country can simply copy. Adapting national science agri-food systems advisory systems to the national context and needs is really critical. We named the bottlenecks, the challenge of baselines, the need for subnational evidence, the coordination that can work in principle yet stalls in practice. We also touched upon the opportunities for improved peer-to-peer learning between our national agri-food science advisory systems, sharing what works, what is not working, piloting new innovations for strengthening those interfaces. So we've achieved all of this in the past 90 minutes or so. Just by 90 minutes of focus. Through a concerted joined up effort across nations, I'm confident that we could strengthen science policy interfaces everywhere through sharing of the experiences of what works. And we also did two very concrete things today beyond the words and the dialogue. Dr. Litter and Dr. Lwafi are putting the joint FAO CIRAD framework for assessing the effectiveness of science policy interface ecosystems into your hands. And an FAO e-learning course on strengthening national science policy interfaces is now launched. But in a sense, one thing we did not finish in our 90 minutes is to consider whether the potential for a global network of national agri-food science advisory systems, which has one seat, one voice for every member state, national advisory system, so that people doing this important work of translating science for policy no longer have to share, solve that same problem alone, country by country, with no shared forum to compare notes. So following this session, this is something that we plan to explore with our member states to assess the interest or the utility that such a network could provide. So let me close with some thanks to our Director General, to our ministers for their wise words and guidance who are at the coalface of the science policy interface, to all of our panelists for their valuable perspectives and guidance. that really were worth far more than the three minutes they were allocated. And to Salim for the overview of the FAO CIRAD work, and to Preet for holding the floor open to all of you. So a round of applause for all of our speakers, panelists, and moderators for this morning's session. In this session, you all ensured that science did not stumble its way in the dark to policy. In fact, we just spent 90 minutes shining strong lights on the pathways to strengthen our agri-food science policy interfaces. So thank you all.