The role of social innovation in tackling global poverty and vulnerability

Tackling the rapid rise in global poverty is one of the most pressing challenges the world faces today, especially in this new age of turbulence. On top of the ongoing environmental crisis, the last fifteen years has been rocked by the financial crisis of 2007–8, compounded by the 2020 Covid-pandemic and then by the 2022 war in Ukraine, each of which has negatively impacted all aspects of sustainable development. Although in practice many development organizations have been using the methods and processes of social innovation to tackle poverty and vulnerability for many years, it is only recently that they have specifically begun to analyse and codify its contribution to these and other SDGs. Social innovation provides beneficial social outcomes for citizens and other actors, often at local level with the strong bottom-up involvement of civil society and through its cross-actor, cross-sector, cross-disciplinary and cross-cutting strengths. Importantly, it aims to empower those with a social need, particularly when they have little to begin with. It focuses on increasing the beneficiaries' own agency and capability rather than passively only relying on others to act on their behalf. This is done by transforming social relationships and developing new collaborative processes. Amongst a wide range of recent and contemporary sources, this paper analyses a large scale quantitative and qualitative global survey of social innovations that tackle poverty and vulnerability in different global regions. It examines various definitions of poverty, including extreme, absolute and relative measures as well as arguably more useful approaches like the Multidimensional Poverty Index. It proposes how social innovation should be recalibrated to meet the increasing threats of the new age of turbulence, including by deploying the sociological lens of the agency-structure dichotomy to show why the public sector needs to become involved more proactively in social innovation. It also looks at certain myths around poverty and vulnerability, examines why we need to revise our understanding of sustainable development and resilience, and why a new nexus approach is needed that combines SDG1 with other strongly related SDGs.</p

The Geo-Demographics of European Consumers’ Food Behaviour in the New Age of Disruption

The COVID-19 pandemic, unlike the 2007–2008 financial crisis, was a supply side shock, now sharply exacerbated by the Ukrainian war. Drawing on relevant sources, this chapter illustrates the resulting impacts on changes in consumers’ food behaviour during the first wave of the pandemic, based on a large sample of households from 12 countries spread across Europe. Unlike most previous studies, this analysis takes place at European level revealing large scale general trends. Findings show that the food system, like many other strategic consumer markets, has experienced shortages, panic-buying, hoarding and a focus on products both with longer shelf-lives and that help to reduce stress. However, there have been wildly different outcomes related to socio-demographics, household income and location. As a result, and supported by digital technologies, new spatial dynamics and relationships are emerging that exemplify important lessons for all food system actors, in particular significant shifts towards more local-regional production and supply. This is accompanied by much greater consumer awareness of the importance of food and involvement in its preparation, mediated through geography and the socio-demographic characteristics of household consumption. A strong driver is the increasingly local orientation of work and business transformed by a resurgence of hybrid working

CppFlow: Generative Inverse Kinematics for Efficient and Robust Cartesian Path Planning

In this work we present CppFlow - a novel and performant planner for the Cartesian Path Planning problem, which finds valid trajectories up to 129x faster than current methods, while also succeeding on more difficult problems where others fail. At the core of the proposed algorithm is the use of a learned, generative Inverse Kinematics solver, which is able to efficiently produce promising entire candidate solution trajectories on the GPU. Precise, valid solutions are then found through classical approaches such as differentiable programming, global search, and optimization. In combining approaches from these two paradigms we get the best of both worlds - efficient approximate solutions from generative AI which are made exact using the guarantees of traditional planning and optimization. We evaluate our system against other state of the art methods on a set of established baselines as well as new ones introduced in this work and find that our method significantly outperforms others in terms of the time to find a valid solution and planning success rate, and performs comparably in terms of trajectory length over time. The work is made open source and available for use upon acceptance

Public Services 2.0: The Impact of Social Computing on Public Services

This report presents the findings of the study on "Public Services 2.0: The Impact of Social Computing on Public Services" conducted by TNO and DTI on behalf of IPTS from 2008 to 2009. The report gives an overview of the main trends of Social Computing, in the wider context of an evolving public sector, and in relation to relevant government trends and normative policy visions on future public services within and across EU Member States. It then provides an exhaustive literature review of research and practice in the area of Social Computing and identifies its key impact areas in the public sector. The report goes on to discuss four case studies of Social Computing-enabled communities in different areas: education (Connexions), health (Doctors.net.uk), inclusion (PatientsLikeMe) and governance (Wikileaks). This is followed by the findings of a scenario-building exercise in which two alternative scenarios were developed and related future opportunities and risks discussed. Additionally, the report presents the results of a cross-case analysis and an ad-hoc online survey which identifies the level of usage, the general characteristics and the key drivers of Social Computing for public services. The report concludes with a summary of research challenges and policy-relevant recommendations. Evidence from the study indicates that Social Computing technologies, applications and values have already been adopted in many areas of government activity. Social Computing affects several aspects of public service, related to both the front office (citizen-government relations) and the back office activities of public administrations. Social Computing is leading to new forms of ICT-enabled participation, capable of enhancing users¿ social awareness and involvement. Social Computing is also transforming relationships and ways of working within and between public sector organisations and opens the way to innovative service delivery mechanisms.JRC.J.4-Information Societ

Estimating cropland requirements for global food system scenario modeling

IntroductionThe production of plant crops is foundational to the global food system. With the need for this system to become more sustainable while feeding an increasing global population, tools to investigate future food system scenarios can be useful to aid decision making, but are often limited to a calorie- or protein-centric view of human nutrition.MethodsHere, a mathematical model for forecasting the future cropland requirement to produce a given quantity of crop mass is presented in conjunction with the DELTA Model®: an existing food system scenario model calculating global availability of 29 nutrients against human requirements. The model uses national crop yield data to assign yield metrics for 137 crops.ResultsThe crops with the greatest variation between high and low yielding production were specific nuts, fruits, and vegetables of minor significance to global nutrient availability. The nut crop group showed the greatest overall yield variation between countries, and thus the greatest uncertainty when forecasting the cropland requirement for future increases in production. Sugar crops showed the least overall yield variation. The greatest potential for increasing global food production by improving poor yielding production was found for the most widely grown crops: maize, wheat, and rice, which were also demonstrated to be of high nutritional significance.DiscussionThe combined cropland and nutrient availability model allowed the contribution of plant production to global nutrition to be quantified, and the cropland requirement of future food production scenarios to be estimated. The unified cropland estimation and nutrient availability model presented here is an intuitive and broadly applicable tool for use in global food system scenario modeling. It should benefit future research and policy making by demonstrating the implications for human nutrition of changes to crop production, and conversely the implications for cropland requirement of food production scenarios aimed at improving nutrition

Is There an Association between Advanced Paternal Age and Endophenotype Deficit Levels in Schizophrenia?

The children of older fathers have increased risks of developing schizophrenia spectrum disorders, and among those who develop these disorders, those with older fathers present with more severe clinical symptoms. However, the influence of advanced paternal age on other important domains related to schizophrenia, such as quantitative endophenotype deficit levels, remains unknown. This study investigated the associations between paternal age and level of endophenotypic impairment in a well-characterized family-based sample from the Consortium on the Genetics of Schizophrenia (COGS). All families included at least one affected subject and one unaffected sibling. Subjects met criteria for schizophrenia (probands; n = 293) or were unaffected first-degree siblings of those probands (n = 382). Paternal age at the time of subjects’ birth was documented. Subjects completed a comprehensive clinical assessment and a battery of tests that measured 16 endophenotypes. After controlling for covariates, potential paternal age–endophenotype associations were analyzed using one model that included probands alone and a second model that included both probands and unaffected siblings. Endophenotype deficits in the Identical Pairs version of the 4-digit Continuous Performance Test and in the Penn Computerized Neurocognitive Battery verbal memory test showed significant associations with paternal age. However, after correcting for multiple comparisons, no endophenotype was significantly associated with paternal age. These findings suggest that factors other than advanced paternal age at birth may account for endophenotypic deficit levels in schizophrenia

Driving Innovation through Big Open Linked Data (BOLD): Exploring Antecedents using Interpretive Structural Modelling

YesInnovation is vital to find new solutions to problems, increase quality, and improve profitability. Big open linked data (BOLD) is a fledgling and rapidly evolving field that creates new opportunities for innovation. However, none of the existing literature has yet considered the interrelationships between antecedents of innovation through BOLD. This research contributes to knowledge building through utilising interpretive structural modelling to organise nineteen factors linked to innovation using BOLD identified by experts in the field. The findings show that almost all the variables fall within the linkage cluster, thus having high driving and dependence powers, demonstrating the volatility of the process. It was also found that technical infrastructure, data quality, and external pressure form the fundamental foundations for innovation through BOLD. Deriving a framework to encourage and manage innovation through BOLD offers important theoretical and practical contributions