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      Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling

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          Abstract

          Multi-stakeholder platforms (MSPs) are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their ‘capacity to innovate’ and contribute to the ‘scaling of innovations’. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC). In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM) to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors) are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts.

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          Education, Vulnerability, and Resilience after a Natural Disaster.

          The extent to which education provides protection in the face of a large-scale natural disaster is investigated. Using longitudinal population-representative survey data collected in two provinces on the island of Sumatra, Indonesia, before and after the 2004 Indian Ocean tsunami, we examine changes in a broad array of indicators of well-being of adults. Focusing on adults who were living, before the tsunami, in areas that were subsequently severely damaged by the tsunami, better educated males were more likely to survive the tsunami, but education is not predictive of survival among females. Education is not associated with levels of post-traumatic stress among survivors 1 year after the tsunami, or with the likelihood of being displaced. Where education does appear to play a role is with respect to coping with the disaster over the longer term. The better educated were far less likely than others to live in a camp or other temporary housing, moving, instead, to private homes, staying with family or friends, or renting a new home. The better educated were more able to minimize dips in spending levels following the tsunami, relative to the cuts made by those with little education. Five years after the tsunami, the better educated were in better psycho-social health than those with less education. In sum, education is associated with higher levels of resilience over the longer term.
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            Adjusting for network size and composition effects in exponential-family random graph models

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              Academic Cross-Pollination: The Role of Disciplinary Affiliation in Research Collaboration

              Academic collaboration is critical to knowledge production, especially as teams dominate scientific endeavors. Typical predictors of collaboration include individual characteristics such as academic rank or institution, and network characteristics such as a central position in a publication network. The role of disciplinary affiliation in the initiation of an academic collaboration between two investigators deserves more attention. Here, we examine the influence of disciplinary patterns on collaboration formation with control of known predictors using an inferential network model. The study group included all researchers in the Institute of Clinical and Translational Sciences (ICTS) at Washington University in St. Louis. Longitudinal data were collected on co-authorships in grants and publications before and after ICTS establishment. Exponential-family random graph models were used to build the network models. The results show that disciplinary affiliation independently predicted collaboration in grant and publication networks, particularly in the later years. Overall collaboration increased in the post-ICTS networks, with cross-discipline ties occurring more often than within-discipline ties in grants, but not publications. This research may inform better evaluation models of university-based collaboration, and offer a roadmap to improve cross-disciplinary collaboration with discipline-informed network interventions.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 February 2017
                2017
                : 12
                : 2
                : e0169634
                Affiliations
                [1 ]Leibniz Institute for Agricultural Development in Transition Economies (IAMO), Theodor-Lieser-Strasse 2, Halle (Saale), Germany
                [2 ]Knowledge, Technology and Innovation Group, Wageningen University, EW Wageningen, The Netherlands
                [3 ]International Institute of Tropical Agriculture (IITA), Kacyiru, Kigali, Rwanda
                [4 ]Swedish University of Agricultural Sciences (SLU), Department of Urban and Rural Development, Ulls väg Uppsala, Sweden
                [5 ]Bioversity International, Quartier Kabondo, Rohero 1, Avenue 18 Septembre 10, Bujumbura, Burundi
                [6 ]International Institute of Tropical Agriculture (IITA), Kampala, Uganda
                Utrecht University, NETHERLANDS
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: M. Schut FH M. Sartas.

                • Data curation: M. Schut M. Sartas BvS.

                • Formal analysis: FH.

                • Funding acquisition: PvA BvS M. Schut.

                • Investigation: M. Schut FH M. Sartas PvA BvS.

                • Methodology: FH M. Sartas.

                • Project administration: M. Schut PvA.

                • Resources: PvA BvS M. Schut.

                • Software: FH.

                • Supervision: PvA M. Schut.

                • Validation: M. Schut M. Sartas PvA BvS FH.

                • Visualization: FH.

                • Writing – original draft: M. Schut FH M. Sartas.

                • Writing – review & editing: FH M. Schut M. Sartas PvA BvS.

                Author information
                http://orcid.org/0000-0002-3361-4581
                Article
                PONE-D-16-10883
                10.1371/journal.pone.0169634
                5293196
                28166226
                ca0b5daf-845d-457d-894c-b524df75b04e
                © 2017 Hermans et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 March 2016
                : 20 December 2016
                Page count
                Figures: 6, Tables: 9, Pages: 21
                Funding
                Funded by: Humidtropics CGIAR Research Program
                Award Recipient :
                Funded by: CIALCA Rwanda, Burundi and DRC
                Award Recipient :
                This work was funded under the framework of the Consortium for Improving Agricultural Livelihoods in Central Africa (CIALCA), which is funded by the Belgian Directorate General for Development Cooperation and Humanitarian Aid (DGD). CIALCA forms part of the CGIAR Research Program on Integrated Systems for the Humid Tropics (Humidtropics), and the CGIAR Research Program on Roots, Tubers and Bananas (RTB). We would like to acknowledge Humidtropics, RTB, and the CGIAR Fund Donors ( http://www.cgiar.org/about-us/governing-2010-june-2016/cgiar-fund/fund-donors-2/) for their provision of core funding without which this research could not have been possible. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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