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      "description_narrative":["Mongolia is a developing country that is large in area but small in population. Since the fall of communism, Mongolia has experienced difficulty in developing both an effective civil service and a university system that generates the expertise to solve the problems of a modern society. Much information is gathered but institutions and stakeholders lack the experience to extract knowledge from this data and use it effectively in the public interest. We propose a programme of workshops that will train Mongolian academics, civil servants and other stakeholders in the use of statistics, machine learning and data science. The programme will be customised to work on some of the current most pressing Mongolian social challenges, using real data accumulated by Mongolian public institutions. This will ensure that the technical knowledge shared is not abstract but applied with the potential for immediate impact on Mongolian society.  The programme will have 4 stages.   In the first stage we will scope out the problems and assemble the data. We have the advantage of our prior collaborations with Mongolia which will already offers a head start.  We follow this in the second stage with a two week session of instruction in the capital of Mongolia, Ulaanbaatar. This will be given by expert academics with the support of well-trained doctoral students. The instruction will be highly interactive using modern teaching techniques to accommodate for the diversity in previous experience of participants as well as diversity in English language ability. Graduate students from the University of Bath will play a significant role in teaching and interacting with the Mongolians as they learn. The team has previous experience in delivering similar activities to civil service data scientists at the Paraguayan Ministry of Development. Best practice from this context will be integrated into the delivery in Mongolia.   In the third stage, four leading Mongolian stakeholders will visit Bath for a week to attend one of Bath's innovative Integrative Think Tanks (ITT). The latter is a unique interactive research training workshop that has been developed and already used multiple times for Bath's EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa). Such workshops are based around the principle of taking real world challenges in industry, or in this case, the public sector, and, through a tried and tested process of facilitation, distilling out well-formulated mathematical research questions that can move forward into an active and collaborative research projects.   The ITT in Bath will use as its starting challenges the specific Mongolian data and societal problems described earlier. This will also involve a larger number of Bath academics and (SAMBa) graduate students who will contribute to and learn from the aforementioned process of distilling out tangible mathematical questions. Having run nine ITTs, and with the accolade of generating manifold new research projects with accompanying funding support, the Department of Mathematical Science at Bath has a strong track record in the delivery of ITTs.   The final stage will be a week long visit back to Ulaanbaatar to further advance the research agenda on the Mongolian problems by feeding them back into an ITT attended by a wide spread of Mongolian stake-holders together with Bath academics and doctoral student.   Throughout, we will be in electronic communication with our Mongolian partners to advance the instruction and progress on research.  At the end of the programme, we will have trained a group of Mongolian academics and civil servants in statistics and data science. We will have advanced understanding on a range of Mongolian problems using their data. Knowledge will be transferred in that the academics will be able to pass it on to their students and the civil servants will have developed data-driven policy making skills.","The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
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      "description_narrative":["Earthquakes, storms, floods, and conflict cause untold damage to infrastructure, services, agriculture and livelihoods. The destruction of housing is often most visible, and the most devastating to the families, with often hundreds of thousands of homes destroyed. Householders themselves are invariably the first to respond; they are never passive, and signs of shelter recovery are very apparent from the first days after a disaster. The majority - as many as 80 or 90% - receive little or no assistance from the international community and are the main drivers of their own recovery process. This process has been termed 'self-recovery'. Previous GCRF awards supported interdisciplinary teams led by ODI in collaboration with CARE International UK, BGS, UCL and Loughborough University. They developed the understanding of the self-recovery process and advanced the theoretical basis for humanitarian assistance to the process of supporting self-recovery in practice. In large part as a result of this work, self-recovery is now a strategic element of the humanitarian shelter sector discourse with many disaster responses purporting to support this inevitable process. In recognition of the value of a people-centred approach that moves away from the convention product-based modalities, the CARE Philippines post-cyclone self-recovery project won the 2018 World Habitat Award in acknowledgment of its self-recovery focus. Sixteen thousand houses were built, each one unique and reflecting the priorities and means of each family. https://www.world-habitat.org/world-habitat-awards/winners-and-finalists/post-haiyan-self-recovery-housing-programme/ The self-recovery approach that respects the primacy of agency and choice aligns well with current humanitarian and development concerns such as the 'humanitarian development nexus', the Grand Bargain's emphasis on localisation, participation and cash-based responses, the Sendai Framework on Disaster Risk Reduction, the Sustainable Development Goals and the Global Shelter Cluster strategy. This is further explained in the Business Case. However, very little has been done to develop guidance for practice. With the exception of the protocol 'Informing Choice for Better Shelter' that delivers a guide for the development of technical educational material, there are no published tools nor guidelines that provide an implementation framework for self-recovery in shelter projects. This project addresses this gap. CARE International has over 70 country offices across the world, all of them in ODA eligible  countries. All of the proposed activities will take place two hazard prone countries where there is a CARE presence and/or an activated coordination system in the form of a country level shelter cluster. The potential regions to be selected include South Pacific islands, East Africa, Central America, Philippines and SE Asia the precise locations to be dependent on ongoing and new disaster responses. In all instances the research team will be working with the Global Shelter Cluster, country level clusters and/or CARE International country teams. These will all be ODA eligible countries. The protocol developed will be adapted to become a preparedness tool for the specific ODA eligible country context. All outputs will be thoroughly scrutinised by the humanitarian sector and incorporated directly into practice.","The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
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