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Is foreign aid an effective instrument of soft power? Does it generate affinity for donor countries and the values they espouse? This article answers these questions in the context of Chinese aid to Africa and the competing aid regime of the United States. The study combines data on thirty-eight African countries from Afrobarometer, AidData, and the Aid Information Management Systems of African finance and planning ministries. The authors use spatial difference-in-differences to isolate the causal effects of Chinese and US aid. The study finds that Chinese aid to Africa does not increase (and may in fact reduce) beneficiaries' support for China. By contrast, US aid appears to increase support for the United States and to strengthen recipients' commitment to liberal democratic values, such as the belief in the importance of elections. Chinese aid does not appear to weaken this commitment, and may strengthen it. The study also finds that Chinese aid increases support for the UK, France and other former colonial powers. These findings advance our understanding of the conditions under which competing aid regimes generate soft power and facilitate the transmission of political principles and ideals. [ABSTRACT FROM AUTHOR]

With all the recent attention focused on big data, it is easy to overlook that basic vital statistics remain difficult to obtain in most of the world. What makes this frustrating is that private companies hold potentially useful data, but it is not accessible by the people who can use it to track poverty, reduce disease, or build urban infrastructure. This project set out to test whether we can transform an openly available dataset (Twitter) into a resource for urban planning and development. We test our hypothesis by creating road traffic crash location data, which is scarce in most resource-poor environments but essential for addressing the number one cause of mortality for children over five and young adults. The research project scraped 874,588 traffic related tweets in Nairobi, Kenya, applied a machine learning model to capture the occurrence of a crash, and developed an improved geoparsing algorithm to identify its location. We geolocate 32,991 crash reports in Twitter for 2012–2020 and cluster them into 22,872 unique crashes during this period. For a subset of crashes reported on Twitter, a motorcycle delivery service was dispatched in real-time to verify the crash and its location; the results show 92% accuracy. To our knowledge this is the first geolocated dataset of crashes for the city and allowed us to produce the first crash map for Nairobi. Using a spatial clustering algorithm, we are able to locate portions of the road network (<1%) where 50% of the crashes identified occurred. Even with limitations in the representativeness of the data, the results can provide urban planners with useful information that can be used to target road safety improvements where resources are limited. The work shows how twitter data might be used to create other types of essential data for urban planning in resource poor environments. [ABSTRACT FROM AUTHOR]

Bonamia spp. cause epizootics in oysters worldwide. In southern Australia, Bonamia exitiosa Hine, Cochennac and Berthe, 2001 threatens aquaculture of Ostrea angasi Sowerby, 1871. Bonamia spp. infections can display strong seasonality, but seasonal dynamics of B. exitiosa–O. angasi are unknown. Ostrea angasi naïve to B. exitiosa infection were stocked onto farms in three growing regions, and B. exitiosa was monitored seasonally for one year. Environmental parameters we measured did not correlate with B. exitiosa prevalence or infection intensities. Extreme temperatures suggest O. angasi culture systems need development. Bonamia exitiosa prevalence increased over time. After three months, O. angasi had B. exitiosa prevalence of 0.08–0.4, and after one year, the prevalence was 0.57–0.88. At some sites, O. angasi had >0.5 B. exitiosa prevalence in >6 months, but at other sites, >9 months passed before prevalence was >0.5. Bonamia exitiosa infection intensities were low with no seasonal pattern but were affected by the interaction of site, season and oyster meat:shell ratio. Understanding infection and initiating a breeding programme for resistance would provide benefits for O. angasi industry expansion. [ABSTRACT FROM AUTHOR]

The haplosporidian Bonamia was first detected in Australian shellfish in 1991. Australian isolates in Ostrea angasi Sowerby, 1871 were identified as Bonamia exitiosa Hine, Cochennac and Berthe, 2001, which threatens development of an O. angasi aquaculture industry. European field data suggest that Bonamia ostreae Pichot, Comps, Tigé, Grizel and Rabouin, 1980 infections in Ostrea edulis Linnaeus, 1758 build slowly, but infection dynamics of B. exitiosa in O. angasi are unknown. We investigated B. exitiosa infection in O. angasi by cohabiting uninfected juvenile O. angasi with adults infected with B. exitiosa. Oysters were sampled at 10, 21 and 40 days after cohabitation, and B. exitiosa prevalence and intensity were assessed. Bonamia exitiosa rapidly infected and caused disease in O. angasi. Mortalities began at 12 days, with ˜50% mortality by day 21 and >85% mortality by day 40. Mortalities displayed pathology consistent with clinical B. exitiosa infection. Time to first infection is likely influenced by a combination of parasite infectivity, host exposure and host immune capacity. Host death is not required for transmission, but probably facilitates release of parasites from decaying tissue. Understanding B. exitiosa transmission informs design and interpretation of field studies and aids development of management strategies for oyster aquaculture. [ABSTRACT FROM AUTHOR]

The formal analysis of the principles leading the classification of the hexadic, decadic, and triadic signs from C. S. Peirce especially, gives rise to a general methodology allowing to systematically classify any n-adic combinatory named "protosign." Basic concepts of the algebraic theory regarding the categories and functors will be used. That formalization provides an additional benefit by highlighting and systematizing formal immanent relationships between the classes of protosigns (or signs). Well known hierarchical structures (lattices) are then obtained. Thanks to the contribution of specific concepts in the Homological Algebra, new methodologies of analysis and creation of significations can be introduced. [ABSTRACT FROM AUTHOR]

The health sector has attracted significant foreign aid; however, evidence on the effectiveness of this support is mixed. This paper combines household panel data with geographically referenced subnational foreign aid data to investigate the contribution of health aid to health outcomes in Uganda. Using a difference-in-differences approach, we find that aid had a strong effect on reducing the productivity burden of disease indicated by days of productivity lost due to illness but was less effective in reducing disease prevalence. Consequently, health aid appeared to primarily quicken recovery times rather than prevent disease. In addition, we find that health aid was most beneficial to individuals who lived closest to aid projects. Apart from the impact of aid, we find that aid tended to not be targeted to localities with the worse socioeconomic conditions. Overall, the results highlight the importance of allocating aid close to subnational areas with greater need to enhance aid effectiveness. [ABSTRACT FROM AUTHOR]

Since 1945, over $4.9 trillion dollars of international aid has been allocated to developing countries. To date, there have been no estimates of the regional impact of this aid on the carbon cycle. We apply a geographically explicit matching method to estimate the relative impact of large-scale World Bank projects implemented between 2000 and 2010 on sequestered carbon, using a novel and publicly available data set of 61,243 World Bank project locations. Considering only carbon sequestered due to fluctuations in vegetative biomass caused byWorld Bank projects, we illustrate the relative impact of World Bank projects on carbon sequestration. We use this information to illustrate the geographic variation in the apparent effectiveness of environmental safeguards implemented by theWorld Bank. We argue that sub-national data can help to identify geographically heterogeneous impact effects, and highlight many remaining methodological challenges. [ABSTRACT FROM AUTHOR]

The study utilizes survival analysis methodology to examine unemployment duration in Uganda's five regions. The analysis is developed on a database of cohorts of the Uganda National Household Survey (UNHS) for the year 2005/06 and the Uganda National Panel Survey (UNPS) for the years 2009/10, 2010/11 and 2011/12. This work analyses individuals' first spell of unemployment using the Kaplan Meier estimator of the survival functions in unemployment and the covariate effects on duration using the Cox Proportional Hazard Model. Results suggest that over 12 months cohorts in the Eastern and Northern regions face longer spells of unemployment with a 0.85 probability of unemployment. However, in the long run and with the exception of Western Uganda, unemployment duration in all regions is not statistically different from that of Kampala. Cohorts with higher education gain employment slower than those with less education across all regions. Women exit unemployment much slower than men if the unemployment duration is less than 12 months and much faster where the duration is longer than a year. Exit from unemployment increases with age. Investments to curb unemployment should focus on equipping youth younger than 25 years with employable skills. [ABSTRACT FROM AUTHOR]

We describe the efforts of two related undergraduate projects to promote lasting social change in marginalized communities in the Dominican Republic and Nicaragua. The projects represent a test of the premise that undergraduate projects can engage academically based strategies and transcend good intentions to achieve effective community partnerships to improve health and health care. The projects proceed from a perspective and theory of marginalization and its consequences. Specifically, marginalization undermines individual and collective capacity to meet basic needs and efforts to thrive. Through strengthening social infrastructure, communities can overcome the effects of marginalization. Project work begins with annual medical clinics and, with the permission of community residents, team members conduct ethnographic descriptions of the communities and their health and health care concerns and resources. We use social network analysis (SNA) and geographic information system (GIS) techniques to describe social infrastructure. Working from those foundations, both projects have enabled increased social infrastructure. To date, we have observed increased communication among community residents, facilitated the development of community-endorsed five-year plans, and established partnerships with regional and international groups. [ABSTRACT FROM AUTHOR]

Objective: Cross-national studies provide inconclusive results as to the effectiveness of foreign health aid. We highlight a novel application of using subnational data to evaluate aid impacts, using Malawi as a case study., Design: We employ two rounds of nationally representative household surveys (2004/2005 and 2010/2011) and geo-referenced foreign aid data. We examine the determinants of Malawi's traditional authorities receiving aid according to health, environmental risk, socioeconomic and political factors. We use two approaches to estimate the impact of aid on reducing malaria prevalence and increasing healthcare quality: difference-in-difference models, which include traditional authority and month-of-interview fixed effects and control for individual and household level time-varying factors, and entropy balancing, where models balance on health-related and socioeconomic baseline characteristics. General health aid and four specific health aid sectors are examined., Results: Traditional authorities with greater proportions of individuals living in urban areas, more health facilities and greater proportions of those in major ethnic groups were more likely to receive aid. Difference-in-difference models show health infrastructure and parasitic disease control aid reduced malaria prevalence by 1.20 (95% CI -0.36 to 2.76) and 2.20 (95% CI 0.43 to 3.96) percentage points, respectively, and increased the likelihood of individuals reporting healthcare as more than adequate by 12.1 (95% CI 1.51 to 22.68) and 14.0 (95% CI 0.11 to 28.11) percentage points. Entropy balancing shows similar results., Conclusions: Aid was targeted to areas with greater existing health infrastructure rather than areas most in need, but still effectively reduced malaria prevalence and enhanced self-reported healthcare quality., Competing Interests: Competing interests: None declared.