Collateral Strategies for Poverty Reduction in Kenya: Prospects and Challenges

In practice all over the world, development practitioners’ concern about poverty has been increasing because of their long history in working with the marginalized groups amidst inadequate resources and unfavourable scenarios that push them to poverty situations. At the micro level, development practitioners engage different strategies to deal with poverty, including poverty risk assessment, programme design, liaison with state agents and different resource providers to generate innovative ways to help individuals and communities to understand their wanting situation and improve their livelihoods for the better. This paper seeks to analyze the diverse collateral strategies engaged by different development practitioners in their efforts to eradicate poverty in Kenya. The role of the county and national governments, development agencies, civil society and international organizations and their collaboration with other actors such as the private sector, community based organizations, faith based organizations and self-help groups are analyzed in this paper. Special emphasis is placed on how such efforts can complement those of professional social workers for holistic and sustainable poverty reduction in Kenya. Keywords: Development Practitioners, Poverty Reduction, Collateral Strategies, Self-help Groups

Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data

Wildlife conservation organizations task rangers to deter and capture wildlife poachers. Since rangers are responsible for patrolling vast areas, adversary behavior modeling can help more effectively direct future patrols. In this innovative application track paper, we present an adversary behavior modeling system, INTERCEPT (INTERpretable Classification Ensemble to Protect Threatened species), and provide the most extensive evaluation in the AI literature of one of the largest poaching datasets from Queen Elizabeth National Park (QENP) in Uganda, comparing INTERCEPT with its competitors; we also present results from a month-long test of INTERCEPT in the field. We present three major contributions. First, we present a paradigm shift in modeling and forecasting wildlife poacher behavior. Some of the latest work in the AI literature (and in Conservation) has relied on models similar to the Quantal Response model from Behavioral Game Theory for poacher behavior prediction. In contrast, INTERCEPT presents a behavior model based on an ensemble of decision trees (i) that more effectively predicts poacher attacks and (ii) that is more effectively interpretable and verifiable. We augment this model to account for spatial correlations and construct an ensemble of the best models, significantly improving performance. Second, we conduct an extensive evaluation on the QENP dataset, comparing 41 models in prediction performance over two years. Third, we present the results of deploying INTERCEPT for a one-month field test in QENP - a first for adversary behavior modeling applications in this domain. This field test has led to finding a poached elephant and more than a dozen snares (including a roll of elephant snares) before they were deployed, potentially saving the lives of multiple animals - including elephants.Engineering and Applied Science

An assessment of interactions between global health initiatives and country health systems

Since 2000, the emergence of several large disease-specific global health initiatives (GHIs) has changed the way in which international donors provide assistance for public health. Some critics have claimed that these initiatives burden health systems that are already fragile in countries with few resources, whereas others have asserted that weak health systems prevent progress in meeting disease-specific targets. So far, most of the evidence for this debate has been provided by speculation and anecdotes. We use a review and analysis of existing data, and 15 new studies that were submitted to WHO for the purpose of writing this Report to describe the complex nature of the interplay between country health systems and GHIs. We suggest that this Report provides the most detailed compilation of published and emerging evidence so far, and provides a basis for identification of the ways in which GHIs and health systems can interact to mutually reinforce their effects. On the basis of the findings, we make some general recommendations and identify a series of action points for international partners, governments, and other stakeholders that will help ensure that investments in GHIs and country health systems can fulfil their potential to produce comprehensive and lasting results in disease-specific work, and advance the general public health agenda. The target date for achievement of the health-related Millennium Development Goals is drawing close, and the economic downturn threatens to undermine the improvements in health outcomes that have been achieved in the past few years. If adjustments to the interactions between GHIs and country health systems will improve efficiency, equity value for money, and outcomes in global public health, then these opportunities should not be missed