Violence against Women Policy and Practice in Uganda - Promoting Justice within the Context of Patriarchy

The goal of this study was to understand how and whether policy and practice relating to violence against women in Uganda, especially Uganda’s Domestic Violence Act of 2010, have had an effect on women’s beliefs and practices, as well as on support and justice for women who experience abuse by their male partners. Research used multi-sited ethnography at transnational, national, and local levels to understand the context that affects what policies are developed, how they are implemented, and how, and whether, women benefit from these. Ethnography within a local community situated global and national dynamics within the lives of women. Women who experience VAW within their intimate partnerships in Uganda confront a political economy that undermines their access to justice, even as a women’s rights agenda is working to develop and implement laws, policies, and interventions that promote gender equality and women’s empowerment. This dissertation provides insights into the daily struggles of women who try to utilize policy that challenges duty bearers, in part because it is a new law, but also because it conflicts with the structural patriarchy that is engrained in Ugandan society. Two explanatory models were developed. One explains factors relating to a woman’s decision to seek support or to report domestic violence. The second explains why women do and do not report DV. Among the findings is that a woman is most likely to report abuse under the following circumstances: 1) her own, or her children’s survival (physical or economic) is severely threatened; 2) she experiences severe physical abuse; or, 3) she needs financial support for her children. Research highlights three supportive factors for women who persist in reporting DV. These are: 1) the presence of an “advocate” or support 2) belief that reporting will be helpful; and, 3) lack of interest in returning to the relationship. This dissertation speaks to the role that anthropologists can play in a multi-disciplinary approach to a complex issue. This role is understanding – deeply and holistically; and, articulating knowledge generated locally that provides connections between what happens at global, national and local levels.

Efficient Secure Computation for Real-world Settings and Security Models

Secure computation involves multiple parties computing a common function while keeping their inputs private, and is a growing field of cryptography due to its potential for maintaining privacy guarantees in real-world applications. However, current secure computation protocols are not yet efficient enough to be used in practice. We argue that this is due to much of the research effort being focused on generality rather than specificity. Namely, current research tends to focus on constructing and improving protocols for the strongest notions of security or for an arbitrary number of parties. However, in real-world deployments, these security notions are often too strong, or the number of parties running a protocol would be smaller. In this thesis we make several steps towards bridging the efficiency gap of secure computation by focusing on constructing efficient protocols for specific real-world settings and security models. In particular, we make the following four contributions: - We show an efficient (when amortized over multiple runs) maliciously secure two-party secure computation (2PC) protocol in the multiple-execution setting, where the same function is computed multiple times by the same pair of parties. - We improve the efficiency of 2PC protocols in the publicly verifiable covert security model, where a party can cheat with some probability but if it gets caught then the honest party obtains a certificate proving that the given party cheated. - We show how to optimize existing 2PC protocols when the function to be computed includes predicate checks on its inputs. - We demonstrate an efficient maliciously secure protocol in the three-party setting.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.