From the CUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. Hi, I'm Stu Miniman, your host for Cloud Native Insights. When we launched the series, one of the things we wanted to talk about was that we're not just using cloud as a destination, but really enabling new ways of thinking, being able to use the innovations underneath the cloud, and that if you use services in the cloud that you're not necessarily locked into a solution or can't move forward. And that's why I'm really excited to help. Welcome to the program. I have the co-founders of Vendia. First, we have Dr. Tim Wagner. He is the co-founder and CEO of the company, as well as generally known in the industry as the father of serverless from the AWS Lambda. And his co-founder, Shruti Rao, she is the chief business offer at Vendia. Also came from AWS where she worked on blockchain solutions. Tim and Shruti, thanks so much for joining us. Thanks for having us in here, Stu. Great to join the show. All right, so Shruti, actually, if we could start with you because before we get into Vendia, coming out of Stell, really interesting technology space, you and Tim both learned a lot from working with customers in your previous jobs. Why don't we start from you? Blockchain, of course, had a lot of learnings, a lot of things that people don't understand about what it is and what it isn't. So give us a little bit about what you've learned and help that lead towards what you and Tim and the team are doing with Vendia. Yeah, absolutely. So one most important thing that we've all heard of was this great gravitational pull towards blockchain in 2018 and 2019. Well, I was one of the founders and early adopters of blockchain from Bitcoin and Ethereum space all the way back from 2011 onwards. And at AWS, I started the Amazon managed blockchain and launched quantum ledger database, two services in the blockchain category. What I learned there was no surprise there. There was a gold rush to blockchain from many customers. I personally talked to over 1,092 customers when I ran Amazon managed blockchain for the last two years. And I found that customers were looking at solving this dispersed data problem. Most of my customers had invested in IoT and edge devices and these devices were gathering massive amounts of data. And on the flip side, they also had invested quite a bit of effort in AI and ML and analytics to crunch this data, give them intelligence. But guess what? This data existed in multiple parties, in multiple clouds and multiple technology stacks and they needed a mechanism to get this data from wherever they were into one place so they could use their AI ML analytics investment. And they wanted all of this to be done in real time and they gravitated towards blockchain but blockchain had quite a bit of limitations. It was not scalable. It didn't work with the existing stack that you had forced enterprises to adopt this new technology and entirely new type of infrastructure. It didn't work cross cloud unless you hired expensive consultants or did it yourself and require these specialized developers. For all of these reasons, we've seen many POCs, a majority of POCs just dying on the vine and not ever reaching the production potential. So that is when I realized that what the problem to be solved was not the trust problem. The problem was dispersed data in multiple clouds and multiple stacks problem. Sometimes multiple parties even problem. And that's when Tim and I started talking about how can we bring all of the nascent qualities of Lambda and serverless and use all of the features of blockchain and build something together. And he has an interesting story on his own, right? Yeah, truth to truth, if I could, I'd like to get a little bit of that. So first of all, for our audience, if you're watching this on the main, probably wanna hit pause, go search Tim, go watch a video, read his medium posts about the past, present, and future of serverless. But Tim, I'm excited. You and I have talked in the past but finally getting you on the program. I've looked through my career and my background is infrastructure and the role of infrastructure, we know is always just to support the applications and the data that run business. That's what is important. Even when you talk about cloud, it is the applications, the code and the data that are important. So it's not that, okay, I've got near infinite compute capacity, it's the new things that I can do with it. It's a comment I heard in one of your sessions. You talked about one of the most fascinating things about serverless was just the new creativity that it inspired people to do. And I loved it, it wasn't just unlocking developers to say, okay, I have new ways to write things but even people that weren't traditional coders. I've talked to people in marketing that were like, I can start with this and build something new. So I guess the question I have for you is, we had this idea of platform as a service where even when things like containers launched, it was we were trying to get close to that atomic unit of the application. And often it was talked about, well, do I want it for portability or ease of use? So you've been wrangling and looking at this from a lot of different ways. So is that as a starting point, what did you see in the last few years with Lambda and help connect us up to where Shruti just left off her bit of the story? Absolutely, look the great story of the great success of the cloud is this elimination of undifferentiated heavy lifting from getting rid of having to build out a data center to all the complexity of managing hardware. And that first wave of cloud adoption was just phenomenally successful at that. But as you say, the real thing businesses wrestle with are applications, right? It's ultimately about the business solution, not the hardware and software in which it runs. So the very first time I sat down with Andy Jassy to talk about what eventually became Lambda, one of the things I said was, look, if we want to get 10x the number of people to come and be in the cloud and be successful, it has to be 10 times simpler than it is today. If step one is hire an amazing team of distributed engineers to turn a server into a fault-tolerant, scalable, reliable business solution, that's going to be fundamentally limiting. And we have to find a way to put that in a box to give that capability to people without having them go hire that and build that out in the first place. And so that kind of started this journey for compute, for trying to solve the problem of making compute as easy to use as possible. Take some code, as you said, even if you're not a die-hard programmer or backend engineer, maybe you're just a full stack engineer who loves working on the front end, but the backend isn't your focus, turn that into something that is as scalable, as robust, as secure as somebody who, who has spent their entire career working on that. And that was the promise of serverless, outside of the specifics of anyone cloud. Now, the challenge, of course, when you talk to customers is that you always heard, you always heard these same two considerations. One is, I love the idea of Lambda, but it's AWS. Maybe I have multiple departments or business partners or need to kind of work on multiple clouds. The other challenge is fantastic for compute. What about data? You've kind of left me with, you're giving me sort of half the solution. You've made my compute super easy to use. Can you make my data equally easy to use? And so, obviously, the part of the genesis of, of Vendita is going and tackling those pieces of this, by giving all that, that promise and easy use of serverless, now with a model for replicated state and data, and one that can cross accounts, machines, departments, clouds, companies as easily as it, as easily as it scales on a single cloud today. Okay, so you've covered quite a bit of ground there, Tim. If you could just unpack that a little bit, because you talk about state cutting across environments, what is it that Vendita is bringing? How does that tie into solutions like Lambda, as you mentioned, but other clouds or even potentially on-premises solutions? So what is the IP, the code, the solution that Vendita's offering? Happy to. So let's start with the customer problem here. The thing that every enterprise, every company, frankly, wrestles with is in the modern world, they're producing more data than ever. IoT, digital journeys, mobile, edge devices, more data coming in than ever before. At the same time, more data getting consumed than ever before with deep analytics, supply chain optimization, AIML, to even more consumers of ever more data. The challenge, of course, is that data isn't always inside a company's four walls. In fact, we've heard 80% or more of that data actually lives outside of a company's control. So step one to doing something like AIML isn't even just picking a product or selecting a technology, it's getting all of your data back together again. So that's the problem that we set out to solve with Vendita. And we realized that, and we've got a part of the genesis for the name here, you know, Vendita comes from Vend diagram. So part of that need to bring code and data together across companies, across tech stacks, means the ability to solve some of these longstanding challenges. And we looked at the two sort of big movements out there, two that we've obviously both been involved in. One of the thrillers, which amazing ability to scale, but single account, single cloud, single company. The other one is blockchain and distributed ledgers. Manages to run across parties, across clouds, across tech stacks, but doesn't have a great mechanism for scalability. It's really a single box deployment model. And obviously there are a lot of limitations with that. So our technology and kind of our insight and breakthrough here was bringing those two things together by solving the problems in each of them with the best parts of the other. So re-imagine a blockchain as a cloud native implementation built entirely out of serverless components that have all of the scale, the cost efficiencies, the high utilization, like all the ease of deployment that something like Lambda has today. And at the same time, you know, bring state to serverless, give things like Lambda and the equivalent of other clouds, a simple, easy built-in model so that applications can have multi-cloud, a multi-account state at all times, rather than turning that into a complicated DIY project. So that was kind of our, that was our insight here, you know, and frankly, we're a lot of that, we're a lot of the interesting technology for us is in turning those centralized services, the centralized version of serverless compute or serverless database into a multi-account, multi-cloud experience. And so that's where we've spent a lot of time and energy trying to build something that gives customers a great experience. Yeah, so I've got plenty of background in customers that have the information silos, if you will. So, you know, we know in the unstructured data, you know, so much of it is not searchable, I can't leverage it, you know, shruti, but maybe it might make sense.  What was leading them to you and you know, how does the solution help them solve that problem? Yeah, absolutely. One of our design partners, our early design partners is this automotive company. They're a premier automotive company. They want, their end goal is to track car parts for warranty recalls issue. So they want to track every single part that goes into a particular car. So there are about 30 to 35,000 parts in each of these cars. And then all the way from manufacturing floor to when the car is sold and when that particular part is replaced eventually toward the end of the life cycle of that part. So for this, they have put together a small test group of their partners, couple of the parts manufacturers, their second tier partners, National Highway Safety Administration is part of this group. Also a couple of dealers and service centers. Now, if you just look at this group of partners, you will see some of these parties have high technology backgrounds just like the auto manufacturers themselves or the part manufacturers. Low modality or low IT competency partners such as the service centers, for them desktop PCs, literally the IT competency. And so it is the service centers. Now, most of majority of these are on multiple clouds. This particular auto customer is on AWS, a manufacturer is on Azure, another one is on GCP. Now they all have to share these large files between each other while making sure that there are some transparency and business rules applicable. For example, two partners who make the same parts or similar parts cannot see each other's data. Most of the participants cannot see the PII data that are not applicable, only the service center can see that. National Highway Safety Administration has read access, not write access. All of that needed to be done and their alternatives before they started using Vendia was either use point-to-point APIs which was very expensive, very cumbersome. It works for a finite small set of parties. It does not scale as and when you add more participants into this particular network. The second option for them was blockchains which they did use. They used Hyperledger Fabric, they used Ethereum Private to see how this works but the scalability with Ethereum Private, it's about 14 to 15 transactions per second. With Hyperledger Fabric, it taps out at 100 or 150 on a good day. Transaction through but it's not just useful. Although all of these are always on systems, they're not serverless. So just provisioning capacity, our customer said it took them two to three weeks per participant. So it's just not a scalable solution. With Vendia, what we delivered to them was this virtual data lake where the sources of this data are on multiple clouds, are on multiple accounts owned by multiple parties but all of that data is shared on a virtual data lake with all of the permissions, with all of the logging, with all of the security, PII and compliance. Now this particular auto manufacturer and the National Highway Safety Administration can run their ML algorithms to gain intelligence off of it and I start to understand patterns of when certain parts go bad or what's the propensity of a certain manufacturing unit producing faulty parts and so on and so forth. This really shows you this concept of unstructured data being shared between parties that are not interconnected with each other while when there are data silos. But I love to follow this up with another example of the democratization. Democratization is very important to Vendia. When Tim launched Lambda and founded the AWS serverless movement as a whole and at AWS, one thing, very important thing happened. It lowered the barrier to entry for a new wave of businesses that could just experiment, try out new things. If it failed, they scrap it. If it worked, they could scale it out. That was possible because of the entry point, because of the paper use and the architecture itself. And our vision and mission for Vendia is that Vendia fuels the next generation of multi-party connected distributed applications. Our second design partner is actually a nonprofit that is in animal welfare industry. Their mission is to maintain a no kill for dogs and cats in the United States. And the number one reason for overpopulations of dogs and cats in the shelters is dogs lost. Dogs and cats lost during natural disasters like the hurricane season. And when that happens, and when let's say your dogs get lost and you wanna find the dog, the ID or the chip reading is not reliable. You wanna search this through pictures. But we also know that if you look at a picture of a dog, four people can come up with four different breed names. So, and this particular nonprofit has 2,500 plus partners across the US and they're all low to no IT modalities. Some of them have higher IT competency and a huge turnover because of volunteer employees. So what we did for them was came up with a mechanism where they could connect with all 2,500 of these participants very easily in a very cost effective way and get all of the pictures of all of the dogs and all these repositories into one data lake so they can run some kind of a dog facial recognition algorithm on it and identify where my lost dog is in minutes as opposed to days it used to take before. So you see a very large customer with very sophisticated IT competency use this also a nonprofit being able to use this and they were both able to get to this outcome in days not months or years as a critical blockchain but just under a few days. So we're very excited about that. Thank you so much for the examples. All right, Tim, before we get to the end I'm wondering if you could take us under the hood a little bit here. My understanding the solution that you talk about if it's universal apps or what you call Unis, I believe. So if I saw that right, give me a little bit of a comparison contrast if you will. Obviously there's been a lot of interest in what Kubernetes has been doing. We've been watching closely, there's connections between what Kubernetes is doing and serverless with the K native project. When I saw the first video talking about Vendia you said we're serverless and we're even containerless underneath. So help us understand because at a super high level some of the multi-cloud and making things very flexible sound very similar. So how has Vendia different and what do you feel your architecture helps solve this really challenging problem? Sure, awesome, look one of the tenets that we had here was that things have to be as easy as possible for customers and if you think about the way somebody walks up today to an existing database system, they say look I've got a schema, I know the shape of my data and a few minutes later I can get a production database. Now it's single user, single cloud, single consumer there but it's a very fast, simple process that doesn't require having code, hiring a team, et cetera. And we want it Vendia to work the same way. Somebody can walk up with a JSON schema handed to us five minutes later they have a database only now it's a multi-party database that's decentralized, so runs across multiple platforms, multiple clouds, multiple technology stacks instead of being single user. So that's going to go one is make that as easy to use as possible. The other key tenant though is we don't want to be the least common denominator of the cloud. One of the challenges with saying everyone's going to deploy their own servers, they're going to run all their own software, they're going to build, they're all going to go deploy a Kubernetes cluster. One of the challenges with that is that Ashruti was saying first anyone for whom that's a challenge, if you don't have a whole IT department wrapped around you that's a difficult proposition to get started on no matter how amazing that technology might be. The other challenge with it though is that it locks you out, it's sort of the inverse of the lock-in process, right, it's the lock-out process. It locks you out of some of the best and brightest things that the public cloud providers have come up with. And we wanted to empower customers to pick the best degree, maybe they want to go use IBM Watson, maybe they want to use a database on Google and at the same time they want to ingest IoT on AWS and they want to all to work together, they want all of that to be seamless, not something where they have to recreate an experience over and over and over again on three different clouds. So that was our goal here in producing this. What we designed as an architecture was decentralized data storage at the core of it. So think about all the precepts you hear with blockchain, they're all there, they all just look different. So we use a NoSQL database to store data so that we could scale that easily. We still have a consensus algorithm only now it's a high speed serverless and cloud function based mechanism. Instead of smart contracts, you write things in a cloud function like Lambda instead. So no more learning solidity, now you can use any language you want. So we changed how we think about that architecture but many of those ideas that got people about it really excited about blockchain and its capabilities and the vision for the future are still alive and well. They've just been implemented in a way that's far more practical and effective for the enterprise. All right, so what environments can I use today for your solution? Shruti talked about customers, spanning across some of the clouds. So what's available kind of today? What's on the roadmap in the future? Will this include beyond this, maybe the top five or six hyperscalers, can I do? Does it just require serverless underneath? So will things that are in a customer's own data center eventually support that? Absolutely, so what we're doing right now is having people sign up for our preview release. So in the next few weeks, we're gonna start turning that on for early access to developers. That'll be the early access program, will be multi account focused on AWS. And then end of summer, we'll be doing our GA release which will be multi cloud. So we'll actually be able to operate across multiple clouds, multiple cloud services on different platforms. But even from day one, we'll have API support in there. So if you've got a service, could even be running on a mainframe, could be on-prem. If it's API based, you can still interact with Vendia and still get the benefits of the system. So developers, please start signing up. You can go find more information on vendia.net and we're really looking forward to getting some of that early feedback and hear more from the people that were the most excited to have start building these projects. Excellent, well, great call to action to get the developers and the users in there. Shruti, if you could just give us the last bit, how the thing that's been fascinating, Tim, when I look at the serverless movement, I've talked to some amazing companies that were two or three people and out of their basement and they created a business and then they're like, oh my gosh, I got VC funding and it's usually sub 10 million dollars. So I look at your team, I had heard, Tim, you're the primary coder on the team and when it comes to the seed funding, it's compared to many startups, it's a small number. So Shruti, give us a little bit, if you could, the speeds and feeds of the company, your funding and any places that you're hiring. Yeah, we are definitely hiring. Let's me start from there. We're hiring for developers and we are also hiring for Solution Architect. So please go to vendia.net and we have all the roles listed there. We would love to hear from you. The second one, funding. Yes, Tim is our main developer and solutions architect here and look, the serverless movement really helped quite a few companies, including us to build this, bring this to market in record speeds and we're very thankful that Tim and AWS started taking the stands back in 2014, 2013 to bring this to market and democratize this. I think when we brought this new concept to our investors and they saw what this could be. It's not an easy concept to understand in the first wave, but when you understand the problem space, you see that the opportunity is pretty endless and I'll say this for our investors on behalf of our investors that they saw a real founder market fit between us. We're literally the two people who have launched and been brand businesses for both serverless and blockchain at scale. So that's what they thought was very attractive to them. And then look, it's Tim and I and we're looking to hire eight to 10 folks and I think we have gotten to a space where we're making a meaningful difference to the world and we would love for more people to join us, join this movement and democratize this dispersed data problem and solve for this and help us create more meanings to the data that our customers and our companies worldwide are creating. We're very excited and we're very thankful for all of our investors to be deeply committed to us and having conviction on us. Well, Shruti and Tim, first of all, congratulations. Thank you, thank you. We've done absolutely looking forward to watching the progress going forward. Thanks so much for joining us. Thank you, sir. Thank you very much. All right, and definitely tune in to our regular conversations on cloud native insights. I'm your host Stu Miniman and looking forward to hearing more about your cloud native insights.


I wanted to say thank you to the Vice President of the Republic of Ghana for such a warm welcome, as well as to Professors Areiti and Tarp for inviting me to share some of the research we've been engaged with myself and colleagues. This is a wonderful opportunity for us to share ideas from different parts of the continent. I'm very excited to be here. I did take the liberty of changing the presentation very slightly when I saw who was in the audience. Although in my abstract I indicated that I would speak specifically about trafficking, the trafficking work I wanted to speak about was part of a broader study aimed at understanding how policy gets changed in the global south. I think I'll speak to some of the broader lessons and draw on three case studies, in fact, not just the one. In the research I want to share with you this morning, we began with a very simple question. Seemingly simple question. And that was a question of how does policy get changed? What causes a policy to change when we're engaged in research? How do we engage in such a way that it can have impact? And we came to this question through our partnership with the Migrating Out of Poverty Consortium. This is a consortium coordinated by the Institute for Development Studies at the University of Sussex and has a number of partners which I'll tell you a bit more about as I continue. This research consortium has a number of questions that it seeks to answer, but the ones that I'm going to focus on here are those to do with policy change. As I said, we began with what seems to be a very simple question. How does policy get made? How does it change? How do we affect change? We came to this through a number of concerns that we've been talking about but not empirically studying for far too long within our research centre. And this is a concern that perhaps the theories that exist of change do not quite fit the context in which we're working initially in South Africa but also in other contexts. And there are a number of reasons for this. I think they're very well summarised by the work of a colleague of mine, Kuda Van Joro, who has expressed some of these concerns and picking up the baton from him, we went on to look at, OK, if we know that there are concerns about the theories of change that we're working with, then how could we adjust them? What kinds of theories of change might we be looking for? His concerns around using northern-based theories of policy change in the global south come from a number of sources. The one is that he points out that there are two assumptions often implicit in policy change efforts. The first is a knowledge-oriented assumption and the second is a problem-oriented assumption. So in the knowledge-oriented assumption, we work from the assumption that if we as researchers produce knowledge and present it to policy makers, that should create change. In the problem-oriented assumption, the assumption is that if we're able to identify a social problem and present it, that too should create policy change. Now, the problem with both of those is that it hasn't panned out in reality and he points to a number of possible reasons including issues of resource poverty, issues to do with institutional weakness, for example, the strength of bureaucracies to effect policy change, to implement it and highly politicize policy contexts. I don't think I would need to tell anybody here that migration has become a highly politicized topic in recent years and migration policies are largely unpopular and that's why we started by terming this research unpopular decisions, unpopular policy decisions get made. Nevertheless, I think as researchers we're facing increasing pressure to show the relevance of our work, to show that there's uptake, to show that there's impact and much of this is policy impact and so there's real work to be done in understanding how it is that we can make this impact. Just to give you an idea of the studies that have been done using the advocacy coalition framework, one of the more common theories of policy uptake, 84% of studies using this framework and trying to implement it in a policy environment come from either the US or Europe and so we lack an understanding of whether these frameworks can be used in our context and if so how, if not how they need to be adjusted. And that was the emphasis for the research. I want to begin by just giving you a very, very brief sketch of the methods. I don't have time here to go into much of it. I'm going to, when I draw the broad conclusions I do towards the end of this presentation, I'm going to ask you in some ways to trust that it is based on very detailed empirical studies in each of the three contexts I'll speak about and there are full reports on the website of the Migrating Out of Poverty website which I gave you the web address of in the previous slide. I don't want to look at any of the individual country reports that would be available to you free to download. We engaged in qualitative methods using process tracing which I think many of you will be familiar with. In our particular case we used three primary methodologies. The first and one of the countries the second was a process of document analysis. Where we could we looked at parliamentary minutes, we looked at debates and this was really to assess how it is that certain ideas came to be popular, came to dominate policy discussions and we also from that began to do a stakeholder mapping of who were the key stakeholders who were influencing a policy change. So and then from there we were able to identify key informants who we needed more information from about the nature of the change that took place. And so in many ways we used what some of you will be familiar with is called the three eyes framework where you map three eyes namely the institutions, the ideas and the interests that might shape a policy change. And in using that as some authors have described a kind of methodological checklist we were able to go through a rigorous process of mapping how it is the policy came to be changed. Alright so let me give you a background to the three case studies that informed the conclusions I'll present to you in a moment. In Bangladesh which was one of the countries in which the work was done and it was done by the refugee and migratory movements research unit at the University of Dhaka they did an in-depth study into the domestic workers and welfare policy which was passed in by the Bangladeshi government in 2015. This is something that's very interesting because in fact advocacy around domestic workers in Bangladesh has a long history from the 1970s so it was by no means a new issue but it gained new energy among particularly civil society in 2006 where domestic workers were excluded in the Labour Act from protections within the Labour Act that was passed during that year. And so it gave a new energy to questions and concerns about protection for migrant domestic workers. In Bangladesh in this particular case study the domestic work that we're talking about is largely a result of internal migration from rural to urban areas and is often a familial arrangement so may well be a young person from a more impoverished background in a rural area going to a family member in the urban areas with great opportunities on the one hand but also in exchange for their labour. And so one of the central debates that shaped the Bangladeshi case study was the extent to which this was indeed work. Was this a labour contract or was this a family arrangement? Did the state have any role to play in trying to regulate such arrangements between families? And that was one of the central ideas if I return to the three eyes framework that circulated and as you'll see that was common in the other case studies as well. What we also saw were two clear coalitions emerging by coalitions I'm drawing on Sabatiya's idea of advocacy coalitions for those who work in the policy change arena. The first was the domestic workers rights network. This was a network an umbrella organisation representing domestic workers and it was one that was largely animated by the exclusion of domestic workers in the Labour Act. On the other hand the second coalition that formed was the Bangladesh Employers Federation that really emerged to represent the interests of employers of domestic workers. Bangladesh in fact let me rather say that in fact what was really interesting and this is true of all three case studies is that Sabatiya talks about these two coalitions that are almost inevitable in a policy change process and I think that's very useful for us. But there were two other clear coalitions that are not evident in the existing research. The first was that of international organisations. So the ILO at the time was producing Convention 189, the domestic workers convention and although Bangladesh had ratified other conventions they were reluctant to ratify this one. There was strong pressure particularly from UNICEF to ratify this convention but the concerns from the Bangladeshi state were that whether it was feasible to implement and so there was a reluctant to sign. And it's very interesting to me comparing it to the South African context where often the critique has been that the signing of international conventions doesn't map onto actual policy change and so it was a very different approach. There were also key concerns raised about national sovereignty and the role that international organisations can and should play in policy change around the globe and I think this is a question we're going to have to delve into in more detail if we're going to understand migration policy change in the African region because it is such a globalised phenomenon, the process of policy making on migration. Alright, so the other very interesting group that emerged as a key stakeholder which I'll talk about more towards the conclusion were in fact the policy makers themselves and I think that's another mission in the existing literature. It assumes that in some ways policy makers and particularly the bureaucrats implementing policies somehow do so in a mechanistic way without their own investments in a policy without their own concerns about what it means for their lives and their work and this is also something that I'll flag later. Okay, so that's the Bangladeshi case study. The other case study from which I'll draw my conclusions was done in Singapore. It was conducted by our colleagues the Asia Research Institute which is based at the National University of Singapore and we investigated a mandatory day off policy for migrant domestic workers. The context here is that Singapore is heavily reliant on migrant domestic workers. At the moment the estimates from the Ministry of Manpower in Singapore are that there are 231,500 migrant domestic workers in the country at the moment. In Singapore there is an aging population with very high levels of formal employment which means that childcare and care for the elderly becomes a very central social issue. Again, we saw a case where renewed activism began because migrant domestic workers excluded from the Employment Act and so there began to be concerns around human rights issues, employment conditions and so on. So in 2008 there were a number of leading civil society organizations that took up this issue. Our colleagues have drafted this report to explain in great detail how there's a very strong Singaporean state. It's a very dominant state and these civil society organizations required the state to buy into the policy before the advocacy began. However, in their research they point to three things that really resulted in the policy being adopted. The first was sustained activism and I'll talk more about the amount of time that it actually requires for policy change, something that I think many of us who work in the sector know but it does require reiterating. The second was that there was a strong influential debate put forward that not implementing the mandatory day for migrant domestic workers would harm Singapore's international reputation and this issue of international reputation was quite powerful. And then the third finding was that there was a real realization from the Singaporean state that migrant domestic workers had choices to go to other countries where their rights were better protected and the dependence on migrant domestic workers really was one of the issues that pushed for this policy to be passed. And then the third case study that I'll draw on is the one I spoke about more in my abstract which is the South African case study and we looked at the Trafficking in Persons Act. What's very interesting about the Trafficking in Persons Act is exactly as in the other two cases we saw two clear coalitions formed. However, the coalition formed by those who were pushing for the Trafficking in Persons Act to be passed was not as centrally drawing on a human rights debate as in the other two contexts. It was largely one that profiled the abuses faced by trafficking victims and interestingly the group that was much more cautious about the policy was one that drew very centrally on a human rights debate. This was largely because of concerns around the human rights particularly of sex workers in South Africa. So I can go into more on that if people would like to hear. But for now what I want to flag is that again we see very strong international influences. Two key triggers in the passing of the South African Act were one when South Africa was demoted on the US Trafficking in Persons report that's issued by the Department of State. We were demoted to the tier two watch list which meant that a further demotion could even result in sanctions or ceasing aid. Now we did some very interesting interviews that shows there wasn't a simple punitive measure but a complex set of relationships between the US and South African government including for example the fact that South African government is the highest recipient of PEPFAR funding which in theory has no relationship to trafficking but made for a particular set of international relationships. We also see in 2010 South Africa hosting the FIFA Football World Cup which also became a strong impetus for renewed activism. What we see that I'll also come back to when I talk about our learnings from these three case studies is incredibly shaky research evidence. In all cases the role of research was not particularly clear and I think it's something we have to ask ourselves as researchers. But in the South African case the evidence that was used was really very weak and often has been heavily, heavily critiqued. So I'll come back to that point. However the act was still passed and to a large extent it was passed because of very high popular support for counter trafficking campaigns and for doing something about trafficking as well as a strong political commitment. The fact that even in 2005 the South African government had written into the Children's Act issues of trafficking even though that particular clause was not at that time implemented that we were always going to develop a counter-trafficking policy. So I'm going to give a brief overview because it's such a multidisciplinary audience about how I feel understandings of policy change have shifted in the academic literature. It's going to be wholly inadequate, a single slide to try and describe a whole body of literature but it helps to put us on the same page when I talk about what I think we've learned about how policy change happens outside of the global north. I think it's fair to say that the early work on policy change from the 1970s relied very heavily on focusing on networks and institutions. So if we think about the level of analysis, it was largely at the level of organization or at the level of institution. I think that by the mid-1980s we had started to see a number of authors writing much more about cognitive and normative frames and much more understanding that really when we're talking about policy change we're talking about change in perceptions. This is if a policy is going to change, it is first and foremost a change in perceptions, understandings and being able to shape the way a problem is seen. As Surrell who offers a very useful summary says, the influence of ideas, general precepts and representations above social evolution and state action based on the belief that cognitive normative elements play an important role in how actors understand and explain the world is common to most approaches or most theories of policy change. So the quote I've put up here really is one that shows that if we're going to try to understand policy change what we're essentially doing is trying to understand the importance of the dynamics of the social construction of reality in shaping historically specific and socially legitimate frames and practices. Now I've written in other ways specifically about trafficking, about how it is that we've come to understand forms of exploitation and social problems which have always been understood as social problems, don't get me wrong, but frame them within the language and ideas of trafficking. And this is something that's been at the heart of the policy change we've seen globally. Most of us, many of us use our quantitative research in particular and believe that it has a very strong power to influence as it should. But what's very clear from the research we've been doing is that this is largely a process of altering perceptions and that means that we have to find ways of making our research relevant to the perceptions, principles and socially legitimate frames and practices that policy makers are working with. And that's really the complexity. What we found was that in all three case studies we did make a decision that we would try to work with the three eyes framework, both as a way of testing its value in context outside of the global north but also that we would use it very loosely and we would adjust it as we needed to as a way of learning how we could understand policy change better. So we found it very useful precisely because it's much less prescriptive than some of the other theories of policy change that exist. In a sense, it doesn't speak about... Sorry, I should have changed that. In a sense, it doesn't speak about what causes policy change in any universal way. What it does rather is map out where we should look if we want to understand change in a policy. And I think that is very, very useful. We added very key ideas from other theories. We found that Reese's notion of norm socialization precisely because it speaks to this interface between the global and the local and the international influences on local policymaking was extremely interesting and important. It hasn't been tested very extensively but we thought that perhaps this is something that as researchers in the global south we need to take up further. So norm socialization, those who don't work in that field really speaks to the process of how after a convention and signed, for example, the norms and principles of that convention might become popular discourse or become popularized in a local context. So how does that process happen? By which something that's written in a convention seems to be the way we understand our society, our reality in a particular country. So we found that very, very interesting. We also really realized the extent to which sustained activism is necessary for that norm socialization to take place. What we also found though is that most of these new theories, even though they critique the simplistic and rather linear models which suggest that if you give policy makers research they implement it, they still assume far too great a degree of evidence-based policy making and I'll speak to that in a minute. All right, so let me move on then to talk about what we did find from these three case studies. As I've said, there's a single report on each of the three country case studies on the website that I gave you the address of and I'll put it back up. So if you want the technical details of each methodology and the details of the finding you'll find them there. What I want to do now is say what did we learn overall in broad brush strokes about what we need to think about when we're trying to affect policy change. And the first thing that was very clear and there were six things we identified, six key factors. The first was that there needs to be a strong understanding of the nature of the policy that's being developed or made. In our case, and I actually think this is something of a limitation of the study, that I'd challenge others to pick up and try it out in other contexts, we were talking about protective oriented policy. So it was policy aimed at protecting a group that are deemed vulnerable, other migrant domestic workers, victims of trafficking in the South African case. So that shaped very much the nature of the policy that was developed. Nevertheless, in spite of this, it's still largely unpopular policy and I still think that presents a real question mark as to why implement a policy that's largely unpopular. So I can give you an example in South Africa, although there was a general sympathy for trafficking victims, nobody suggested that there was no problem with someone being trafficked. There was a lack of support for the policy precisely because there was a sense that this might open a floodgate, it might open a back door to the kinds of migration that the country's been trying to restrict. And so it wasn't an entirely popular policy. The gendered nature of all of the policies is really relevant and when we, using the Three Eyes framework, mapped the ideas that circulated in all three contexts, it was really interesting to see how much that influenced the nature of the debates that were happening. The nature of the debates were very much, and I'll talk about those now, they were very much about, is this even something that the state has a place intervening in? Or is this something about families, about private relationships, and so on? So for example, if I can give you an example of the day off policy in Singapore, one of the debates that was very central was that there's not much difference between migrant domestic workers and housewives. And if housewives don't get a day off, we don't say they're exploited. So how can this be exploitation? And so there was a real kind of questioning of whether this was relevant for the state to start meddling in, if you like. And of course, in each of these cases, there was huge public interest. For some kinds of policy, they seem very removed from people's everyday lives. They seem not to affect us sometimes, whether it's a migration policy that has to do with money laundering or other kinds of things. This is not the daily dinnertime conversations of most people. Whereas in this case, particularly in the two cases to do with the regulation of domestic work, it very much affected the average person in the street and it very much affected the people who are passing the legislation as employers of domestic workers. So the first area to understand in affecting policy change would be the nature of the policy being made. The second question would be the one of who the policy is for. And this overlaps a lot with what I've already said. As I mentioned, the fact that all these policies were heavily gendered had a strong impact on the nature of the ideas that circulated. We're talking about policies for poor women and for migrant women, and there was a strong emphasis on issues of morality in the debates that circulated. So, for example, the conflation often in the South African context between sex work and trafficking meant that there was a strong moral element. A lot of religious groups were very concerned about the trafficking legislation and it was often difficult to unpack what it was that we wanted the trafficking legislation to do. Was it about avoiding what had been deemed to be an immoral or inappropriate practice? Or was it about trying to address the exploitation that it goes with trafficking? Or was it about addressing the syndicates and the traffickers? So it was difficult to pull apart from the moral arguments what the legislation was supposed to do. There were also a number of examples from the Singaporean context and the Bangladeshi context actually where in Singapore, for example, if migrant workers were given a day off, there was a real concern about what would this mean? Would there be increased problems around domestic workers falling pregnant? Would they behave inappropriately in public spaces? So there was this incredible moralizing. It was really very strong around these. We've drawn a lot on Cohen's very famous work on moral panics, where very often the morality of a topic deflects from the broader structural aspects at play and I think that maps quite nicely to what we saw going on in this policy process. So the concerns about morality in some ways became a deflection from the concerns about labour regulation, which were much more difficult to get into public discourse. What was really interesting in our findings is that the fact that one of the case studies focused on internal migration and the other two focused on international migration made absolutely no difference. We didn't see a difference in the tone of the ideas that circulated. We didn't see a difference in the levels of public sympathy, for example, that circulated and that was a real surprise to me and I haven't completely figured out why. The groups that were largely pushing against policy change were largely doing so on the basis of debates that had to do with economic costs and benefits and the connection to the desirability of skilled or unskilled mobility. So, for example, in the Bangladeshi case, the groups that organised to represent employers were largely concerned about whether this would promote unskilled migration, which they deemed to be something largely negative, and whether the policy could be implemented given the economic costs of it. All right, so the third key thing that we learned that has to be accounted for in understanding policy change in our context is who the actors are. I think that the existing literature has focused on this quite a lot, but there were some new learnings for us and one of the main new learning was the role of international actors. It was very interesting because in South Africa there's been some criticism of the role of international actors, which is a policy I'm talking about, but it wasn't nearly as simple as this criticism is often made out. So, in all cases, there had been long-term local activism on an issue, and really what the international attention to the issue did, either, and by international attention, it could be the signing of a convention or it could be an international NGO that really bolsters an issue. What it did was to act as a trigger rather than to put the issue on the agenda. And what would be really important to try and understand is whether, if the issue was not already on the agenda, whether this international influence would be as strong. The other thing that was very key was that the kind of legal approaches were not necessarily more powerful than softer issues to do with international reputation and credibility. This came out very strongly in the South African case where South Africa has tried to cultivate a reputation for being a defender of human rights, and in the Singaporean case as well. And so it was often a softer issue than simply international pressure. The conventions were important, but what's really interesting is that they made no difference in speeding up policy development. So, if I could give you an example that I'm just trying to find so I can do it properly. In Bangladesh, the High Court had already implemented a range of conventions locally for migrant domestic workers that in many ways had done what the activists were trying to do, but not via the route that was imagined, not via the kind of assigning of the international convention on domestic workers. So that, I think, was very interesting. And on each of these cases, the policy change took an average of 10 years. So we're talking about timeframes that are often not... Well, it's not popular within development work but we're looking at 10-year timeframes to change policy. In terms of the role-players, it was also significant that... And I put the question here, which women? That the women affected by this policy change were not the advocates. In all cases, it was largely more middle-class women who spoke and acted as a conduit, largely through their representation of NGOs and coalitions. And I think that creates a number of complex sets of relationships but also really important to know. In all cases, it did require coalitions to be formed, and this seemed to be one of the more powerful ways of affecting policy change. These coalitions tend to include groups with very diverse skills. So it might be lawyers alongside human rights activists, alongside researchers, et cetera. But it was the point at which the advocacy really took off was at the point where coalitions were often formed. What is really interesting, though, and I'd be interested to hear in other contexts whether this is the case, because it was a surprise to me, was that although civil society was very good at getting an issue onto the policy agenda, and in seeing through the process up to when policy began to be drafted, none of the NGOs, except in South Africa, the legal NGOs and in Singapore as well, in fact then played a role in the actual drafting of the policy. They tended then to step back, and I think it does suggest that that might be a gap in the kind of policy process. And then, of course, the other surprise, as I've mentioned, was the role of civil servants in actually lobbying for a particular policy orientation, because, of course, they too have their own investments, and it was described in the Bangladeshi case as an invisible force, because it's not technically part of what we think of as policy change, but it actually mattered in the context. Okay. I can try to speed things up, because I think I've spoken quite a lot about the nature of the positions that were taken. In all three cases, the gendered nature of the policy meant that the positions taken were largely often moral ones with support from legal and human rights discourses. So very often it was about profiling policies and then responding to what was seen as a failure of human rights abuse. For those who were against a particular policy change or were more cautious about it, the debates were almost entirely focused on feasibility and the cost of policy change. What's also clear is that concessions are almost inevitable, and this is what's already in the policy change literature. In no case did any particular coalition get exactly what they wanted. And so factoring in the issues to do with concessions is a really important part of understanding how policy processes work. Finally, I come to some commentary about the role of research, which I thought this study would entirely be about. Research is ambiguous and sometimes ambivalent place in policy change. I don't want to overstate this because the policy makers we interviewed really did want research. It's not that there wasn't an interest in research. There was, and there was a desire to have research, but it was often used extremely problematically. I think the South African case was the most extreme example of how poor the quality of the research was. And as a result, we passed the policy without really knowing a great deal about the phenomenon we were developing policy on, and that was a real pity. The nature of the research that existed was about the abuses that this group faced. And that's fine in terms of getting an issue onto the agenda, but the research lacked focus on what kinds of policy approaches, what kinds of models of policy change might be the most effective. And with hindsight that perhaps would have been very useful research to have. Within policy makers we also noted that they have a very loose understanding of research or of evidence. So in the parliamentary debates it was as possible to use a kind of testimony as well as a research paper, and there were multiple sources of evidence that were drawn on. And that means some of the technical debates about whether a methodology was appropriate, whether a piece of research represented quality research, whether it was any good were largely lost in the actual policy debates. And I think that's a message for us to think about as researchers. The research was heavily contested, particularly in the South African example, but also in the Singaporean example where a human rights watch report was attacked quite heavily on the basis of its methodology. In both those contexts it was contested, but in some ways those contestations didn't map onto the kind of policy change we then saw. We saw it being contested among researchers, but the policy process continued nevertheless. And again I think there's a lesson in that for us. And then finally the research was largely passively consumed. And what I mean by that is not that as I said, policymakers kept saying to us, we want research. We want researchers to come to us and guide the process of policy change, give ideas, put forward ideas. But largely the onus was on researchers to take what they know to policymakers in all three contexts, rather than the other way around. And again that was very interesting. In South African Parliament we made a number of representations on the Trafficking Act. What was interesting about it was that our parliament doesn't have budget for bringing people to parliament. So it just happened that we had the resources and people to be able to do that, but other organizations may not have that. And so it's not always a good representation of what research exists out there, if only one or two people can make those presentations. And then finally the political environment. This is something that I don't think I have to speak on in much at great length, because I think migration has become such a complicated area to effect policy change. It took, as I said, approximately ten years for the policy to change in each of the contexts. And that is not really the pace at which a research cycle works. Many of us would say that after ten years research is outdated. And so it does create a complex mismatch perhaps between researchers and some of our guiding ideas and policy makers and some of their guiding ideas. But nevertheless that was the reality. The other key issue that came up in all three case studies was that the relationship particularly between NGOs and policy makers was key to whether there was any kind of influence on the policy process. In all cases the relationship was not hostile by any stretch of the imagination, but there were for example in the Singapore case they spoke about a particular member of parliament who had an interest in the issue and that had a good relationship with some of the groups that worked on the issue. And that was an avenue to access the policy making process. In South Africa it was perhaps more conflictual, although with hindsight I think that conflict was much more among different lobby groups than it was between parliament and NGOs. With parliament often coming down on researchers and saying well you're saying research is no good, we're saying that research is no good, we need something we can work with. So the relationship that civil society and particularly NGOs had with their members of parliament was absolutely key to whether there could be a constructive engagement. And then finally the ethos of the state and this is something that I won't pretend to know enough about, but it came up in the research and I think it's important for us to deliberate on. In some instances the approach as I said was to avoid for example signing conventions unless it was absolutely clear that those could be implemented and implemented efficiently and that was very much the argument in both Bangladesh and Singapore. South Africa we almost had the opposite case where we signed the convention quite early on but then didn't implement for a very long time until pressure was really quite intense and that's a different kind of ethos of what these instruments mean and what different states use them for. I also think that for example the presence of the bureaucracy in Singapore was far stronger than it was say in South African Bangladesh and that shaped what a policy meant as as I'm sure you can imagine. Alright so to summarize what I have tried to focus on is the ways in which policy changes in the global south what our research has shown us is that there are useful elements in existing theories from the global north that we can use but there are also significant differences in the ways that policy processes are constructed in our context and in order to perhaps offer a way forward for future research we've identified these six factors that we think anyone trying to understand and shape a policy process might need to take into account. We would really welcome other researchers then taking them up and saying no you're absolutely wrong about this point we need to rather focus on A, B and C but I think this was a way of getting a conversation going in the global south about how policy changes. A couple of conclusions that I want to flag which I feel are important came up as important but we didn't do justice to in our study yet is really to understand this relationship between global and local processes. It's not sufficiently evident in the international literature and yet it came out so strongly as something that shapes policy in our context and so we need to do more to figure out how exactly this works. We also found that this 3IS framework is useful precisely because of its lack of because of its flexibility. It's much less deterministic than many of the models out there and it operates as I said as a kind of methodological checklist and for that reason it's loose enough to be used but with adjustments that reflect the way the policy is changed in our context and as I said the approach we took in identifying the six key factors we did was to emphasize where to look for policy influence rather than what factors in some kind of universal way change policy. We looked and I haven't talked much about it but we did look at the advocacy coalition framework which I know many researchers here will be working with but we found a very rigid but nevertheless useful to use selectively so if I can give you an example in this advocacy coalition framework one of the concepts that identified is that of devil shift where often the so called losing coalition, the coalition who didn't get what they wanted out of a policy change imagine that the other group had far greater resources and far greater influence than they in fact had that was quite a useful concept but it was just selective cherry like of those concepts that we could use to understand policy change in our context. Alright so I will stop there I think we only have four minutes or so and thank you very much for your attention.


I'm just wondering if you know everybody here. I am. I am. I'm just going to say it again. Well, thanks. I'll say it again. Good. Well, since we're all sharing the same things. Let's share your answer. I'm going to ask them. That was the biggest question I've ever asked. This is President, this is a letter of Martin Dio. I'm familiar with the word semistat. So if you can't read E.H. That's what it looks like. That is a message to many, from many women, blocked in the bathrooms having done such things as how to be watched and so on. This is what they say. We women political progress congratulates you on your very election to the president of the USA. We live with hope to your country which is on the road of freedom and respect for human rights. We wish you success on this resolution. This is a schedule of hunger strikes that they schedule in September through December of last year in celebration of Helsinki days and things of that sort. This in here is for the documentation of who they are, where the camp is. That is smothered out, lured into a castle. And no way to thank them because they'd be in trouble. Actually, these people want to be publicized. Well, I have a hunger strike that the world doesn't know. One way or another, they will be allergic to the fire. What about an explicit name? What can be smuggled out? I see you can be smuggled back in. They don't mean for us to do something about acknowledging this publicly. How to get to you, Jim. George, those are some of the questions of unofficial documents. Because people know that once it reaches us, it can reach the world. Because then we broadcast it back to the country. That's the actual size. How could anyone write that small? It is an equal number. I'm going to say it again. Yes, yes, Jim. We've just been talking in here about the Nicholson thing. And it's just the difference there. You can't really say that down to the people, sir. I'm sure that the people of Russia are going probably very nice and warm people. But the system is barbarism. Good to see you. Let's see you again. Hello. Good to see you. Good to see you. Glad to see you again. Hello, sir. Well, I think they want us to come up with a topic. To see you again, shall we? And then we'll go right into the cabinet room for me. Once you all come in, we'll just walk into the room. We're going to meet. And don't go out alone to get the photos. Well, how are you? Good to see you. Good to see you. Good to see you. Good to see you. They were... They were sure yelling. Yeah, that's a decision maker. No. No. No, right. To me. This is the one that's got a lot of strength. Well, great pleasure. And it gives me a chance to thank you very much for what you did. And I know what it required, and we regret very much that one week for her. The President has a great time. Bill Kazakowski, he's the President of the state and the FMBA. And he's got a free speech program, and they were the first union in New Jersey to endorse you. We have two Democrats, one Republican and one independent to cover the spectrum. One is a Democratic District Leader, Committee Man, and they went all out during the campaign and took a lot of heat. But they did it because they believed in you and the policies that you had. Well, I know of your support, but I didn't realize that a little bit went there. This is Bill Flynn. Hi, how are you? Nice to see you. Charlie Donahue. Nice to see you. John Thoreau. John Thoreau. I'm glad to see you. I'm real proud of the President. You've made us proud to be Americans. We're just so happy with the job that you're doing and we thought it was only appropriate that we present to you this chief's helmet. Thank you very much. Thank you very much. Thank you. Thank you. I'm very proud and pleased to have you. We also have a life membership badge. Life membership badge. Thank you very much. Just in case a police officer's name fix a ticket. Well, I thank you very much, of course. And I thank him very much for what he was doing last week here and helping us in getting the MX and so forth. And we could use it last week. I needed it this weekend when I went home. I needed it this weekend when I went home. I needed it this weekend when I went home. I needed it this weekend when I went home. Yes. I think I have to tell you, because I think I invented it. When I was about half-high, four years old, and living in the city of Chicago, that's what I said I wanted to be when I grew up. I think old. I never lose those hats without heavy. You made a shift. You did a lot better. You made a good choice. I'll tell you, of course, in those days, the death down there in the south side of Chicago near the university. And when the fire ended, it was pretty spectacular because they were fooled by those natural teams of horses in those days.  That's even a couple of years before much. Well, thank you, Walter. I think this is one of the reasons why you won so big in New Jersey, though. Believe me. Even on my disc. All those Democrats we got in. We spent about four hours in the Port Authority of New York the night before your election, and that was an experience. I got involved enough to find out a diversification of attitude, and you do find it in the Port Authority of New York when you're in the Dorian election. Thank you for that. Thank you, Mr. President, for everything. Thank you. One second here. Mr. Little Souvenirs, I know you can't win. Thank you. Thank you, Mr. President. Thank you. Thank you for your time, Mr. President. I know you were busy. Thank you. Kelly is the one who wrote you a letter after your unfortunate shooting four years ago and ever since then, we're for dinner. Actually, he's very busy. We'll see if we can do the next best thing to get in and meet him. I know we pose here for a real posed picture. What's the best way of doing this? That's perfect. I'm busy, but he's busy, too, and she knows what it is here and how tough it is. You're still thrilling to come. Say hello to Mrs. McCable. Tell her how proud you are for especially in California. Mr. McCable. Good to see you. Mr. President, how are you? I'm good. Kelly, Gwen, and Paul Brayton And Fred Alexander. Mr. President, how are you? In the room. Mr. President, Steve's picked you up in the automobile several times in California. All of these good folks, Mr. President, are my constituents from High Point. I want to make a mistake, Mr. President. Identify High Point as the furniture center of the South. I was told no furniture center of the world. So I'm glad, Mr. President, to present Paul Brayton to you, and he will tell you why we're here. I'm sure you already know that. I'd like to read you a letter, President Reagan. I agree. Dear President Reagan, the Brayton International Chair of Excellence Award is presented annually to one outstanding American citizen who has distinguished themselves in his or her field of endeavor. We are very proud to inform you that you have been selected our recipient for 1985. This award is designed to recognize business, political, humanitarian, or scientific excellence and achievement. As 1985's recipient, you will be asked to serve on the board in nomination to select future recipients of this award. Past recipients include Mr. Fred Alexander of High Point, North Carolina, Mr. Ivy Clayton of Raleigh, North Carolina, Senator Jesse Helms of North Carolina, and now you, Mr. President, from the citizens of North Carolina and the employees of Brayton International, I congratulate you. We are very proud to present you with this distinctive leather chair with your name engraved on the belt. You must try it on. All right. We'll have a close picture. Okay. Say it. I'm very comfortable. Thank you. It is. Congratulations. I'll put that on the top of the chair. It is. It is. Break off. You didn't make some of those long days. Sure. Yes. That's right.  Stand behind the chair. You can try it. You can like it. Do you like to sit in? What? If you look best in it, I'll tell you later. Mr. President, thank you. For our people. Come on. This is Zachary. I'm sorry. That's Abraham. And Jeanette Shaffer, their mother. Okay. And their grandmother. Mr. President, nice to see you.  Did I make a mistake? No. Oh, no. That's your sport. He likes basketball. Oh. I thought you were especially fond of baseball, too. Well, I brought gas baseball. I made a baseball. That was a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. It's not a sport. That was a sports supplies. Birch. It's a Chicagocups game. It was exactly what you wanted. I wrote your poem, and it fell in the sink and I went, ah- heh heh. Oh, wait just a minute. I didn't get you in there. pharmacistmusic... I know you have lots of photographers on camera. But I just bet gaan grab a vest. Just look through the thing and push the little button. See what I'm doing here. I really need a third one here. You can hear the jar with this seal. It's just going to the presidential seat. I'm hitting the jar with jelly beans. I keep forgetting to tell people that I know they must look and get it. Well, we're conscious of ears and eyes. Yes. Are you going through here? Yes. Mr. President, this is Anne Jenner's question. Thank you. And this is your portrait of Ronald Reagan. Hey. How about you, Anne, get over here with the President and give that to him. Thank you. I don't know what to say at a time like this. Should I hold it for you? Should I look? I think that would be easier. Hey, because anything I say makes me sound kind of wrong. It's a handsome fellow. Yes. I was going to say, thank you for making me look a little bigger than I think I would. Thank you, sir. Anne is the art director of Soldiers Magazine. I know. And she did this and asked me if I would communicate with you and see if she could give it to you and you very graciously gave it to us. You certainly. Thank you. Thank you very much. You're so cool. I know you've designed several covers for me. Yes. Here you are. May I give that to you? Mr. President, I'd like to introduce you as well to, you know, my wife. Rosemary Trivel, so nice to see you. Good. My parents were here for Mark himself, so I appreciate you all being here with me and saying, look, Mary and Mark went away. Could we take one family picture before we rush out? That would be great. Congratulations, Anne. And then you and I will get a just one. Absolutely. You've got to have one. Yes. Let's see. Should we get the president in the middle? I would like to. The president won't you and I trace this one. They have a chance to see you. That's right. Thank you. Great. Thank you.


Hello it's Missy! Thank you for watching! Today's tutorial is an updo version of my previous video. I did a topsy tail type of braid that's done with elastics and I did a ponytail version on that video. Today is going to be an updo so make sure to comment down below which version you like better, the ponytail or the updo. Make sure to subscribe if you're new to my channel, click that notification bell as always then you'll never miss any future videos and let's get started! To begin this hairstyle I'm going to be parting my hair on the right side since I'm placing my braid on the left side of my head. I'm going to first divide up a section of hair that I'll leave out to frame my face. Then I'm going to pick up a section of hair next to the hairline and brush through it to use for the first section of my braid. Using a clear elastic band I'm going to tie the elastic over the section a few inches down from the part line. I want the top of the braid to be softer so I'm not placing the first section right on top of my head but instead a little bit lower. Once it's tied off I'm going to create a gap in the hair right above the elastic band and then flip the ends up through the gap and then pull the hair back down again so the two side pieces above the elastic are twisted. Now I'm going to gently pull on small pieces of hair above the elastic to add some volume and create a fuller section. Once that's done I'm going to create a new section of the braid so I'm dividing off two new sections of hair on either side of the previous section. The forward section will be from along the hairline and the back section will be from the top of my head behind the first section that I already tied off. I'm going to combine the two sections together over the top of the previously tied off section. Using another clear elastic band I'm going to tie the two sections together about an inch or so down from the previous elastic then I'm going to flip the ends up and through the gap above the elastic band so the two side sections are twisted. After it's tied off I'm going to gently pull on the two sections above the elastic band to make them a little puffier and fuller. Now I'm going to divide off two new sections of hair for the next part of the braid so I'm separating off a small section from along the hairline underneath the previously divided off section. Then I'm taking a section from the top of my head behind the previous section and I'm going to combine the two sections together over the top of the previously tied off section. I'm going to use another clear elastic band to tie them together and then flip the ends around the elastic band to create twisted side sections. Then I'm going to go back over the hair and carefully puff them up by gently sliding small sections up and out of the elastic band. Now I'm going to pick up two new sections for the next piece of the braid so I'm dividing off a section from above my ear and another section from the top of my head. I'm going to combine them together over the previous section and tie them off using a clear elastic band. Then I'm going to flip the ends around the elastic band and then go back over the two sides and carefully slide small sections up and out of the elastic so they're puffier and fuller. Once the braid reaches my left ear I'm going to create two more sections of the braid.  I'm going to repeat this process working my way back towards the back of my head dividing off two sections of hair one from along the hairline and one from the top or back of my head combining them together over the previous section and tying them off using a clear elastic band. Then I'm going to flip the ends up and through the gap above the elastic band before puffing them up by gently pulling small sections out of the elastic band. After I've created the final sections of the braid I'm going to tie the rest of my hair into a low messy bun. I'm going to combine all of my hair together at the nape of my neck. Using a hair band I'm going to wrap this over the hair until the last wrap of the hair band and instead of pulling all the hair through I'm going to pull it part way and create a large looped section with the hair. Now with the ends sticking out the bottom I'm going to divide them into two equal sections and wrap them around the sides of the loop so they meet together back at the top of the bun. Then using a clear elastic band I'm going to tie the two sections together about an inch or so up from the ends of the hair. Now I'm going to twist these two sections so the one on the right I'm going to twist to the left and the one on the left will go over to the right and then I'm going to bring it back down and pull the looped section through the gap above the elastic band so the two end pieces that were tied together are now wrapped around the big looped section we created at the beginning. Then I'm just going to pin the elastic band underneath the bun at the nape of my neck using a couple bobby pins and once the bun is all wrapped and pinned I'm going to go back over it and kind of pinch and pull on small sections to detail it a little bit adding some volume and texture to the bun. This is one of my favorite ways to wear a messy bun I think it's so fun with this fishtail looking type braid so let me know what you think about this hairstyle down below in the comments. That wraps up today's video comment down below what you think about this look if you saw the ponytail version make sure to comment which one you like better the ponytail or the updo. If you haven't subscribed yet make sure to click that subscribe button click that notification bell as well then you'll be notified every time I post a new video and you'll never miss one and I will see you next time.