THE DEVELOPMENT EFFECTIVENESS OF INTERNATIONAL WATER AND SANITATION INFRASTRUCTURE PROJECTS: DEFINING “QUALITY AT ENTRY” OF WORLD BANK PROJECTS.

Over the past 15 years, the number of international development projects aimed at combating global poverty has increased significantly. Within the water and sanitation sector however, and despite heightened global attention and an increase in the number of infrastructure projects, over 800 million people remain without access to appropriate water and sanitation facilities. The majority of donor aid in the water supply and sanitation sector of developing countries is delivered through standalone projects. The quality of projects at the design and preparation stage is a critical determinant in meeting project objectives. The quality of projects at early stage of design, widely referred to as quality at entry (QAE), however remains unquantified and largely subjective. This research argues that water and sanitation infrastructure projects in the developing world tend to be designed in the absence of a specific set of actions that ensure high QAE, and consequently have relatively high rates of failure. This research analyzes 32 cases of water and sanitation infrastructure projects implemented with partial or full World Bank financing globally from 2000 – 2010. The research uses categorical data analysis, regression analysis and descriptive analysis to examine perceived linkages between project QAE and project development outcomes and determines which upstream project design factors are likely to impact the QAE of international development projects in water supply and sanitation. The research proposes a number of specific design stage actions that can be incorporated into the formal review process of water and sanitation projects financed by the World Bank or other international development partners.

INVISIBLE LABOR FOR DATA: INSTITUTIONS, INFRASTRUCTURE, AND VIRTUAL SPACE

Americans are accustomed to a wide range of data collection in their lives: census, polls, surveys, user registrations, and disclosure forms. When logging onto the Internet, users’ actions are being tracked everywhere: clicking, typing, tapping, swiping, searching, and placing orders. All of this data is stored to create data-driven profiles of each user. Social network sites, furthermore, set the voluntarily sharing of personal data as the default mode of engagement. But people’s time and energy devoted to creating this massive amount of data, on paper and online, are taken for granted. Few people would consider their time and energy spent on data production as labor. Even if some people do acknowledge their labor for data, they believe it is accessory to the activities at hand. In the face of pervasive data collection and the rising time spent on screens, why do people keep ignoring their labor for data? How has labor for data been become invisible, as something that is disregarded by many users? What does invisible labor for data imply for everyday cultural practices in the United States? Invisible Labor for Data addresses these questions. I argue that three intertwined forces contribute to framing data production as being void of labor: data production institutions throughout history, the Internet’s technological infrastructure (especially with the implementation of algorithms), and the multiplication of virtual spaces. There is a common tendency in the framework of human interactions with computers to deprive data and bodies of their materiality. My Introduction and Chapter 1 offer theoretical interventions by reinstating embodied materiality and redefining labor for data as an ongoing process. The middle Chapters present case studies explaining how labor for data is pushed to the margin of the narratives about data production. I focus on a nationwide debate in the 1960s on whether the U.S. should build a databank, contemporary Big Data practices in the data broker and the Internet industries, and the group of people who are hired to produce data for other people’s avatars in the virtual games. I conclude with a discussion on how the new development of crowdsourcing projects may usher in the new chapter in exploiting invisible and discounted labor for data.

School Development in Urbanizing Areas

Good schools are essential for building thriving urban areas. They are important for preparing the future human resource and directly contribute to social and economic development of a place. They not only act as magnets for prospective residents, but also are necessary for retaining current population. As public infrastructure, schools mirror their neighborhood. “Their location, design and physical condition are important determinants of neighborhood quality, regional growth and change, and quality of life.”2 They impact housing development and utility requirements among many things. Hence, planning for schools along with other infrastructure in an area is essential. Schools are very challenging to plan, especially in urbanizing areas with changing demographic dynamics, where the development market and housing development can shift drastically a number of times. In such places projecting the future school enrollments is very difficult and in case of large population influx, school development can be unable to catch up with population growth which results in overcrowding. Typical is the case of Arlington County VA. In the past two decades the County has changed dramatically from a collection of bedroom communities in Washington DC Metro Region to a thriving urban area. Its metro accessible urban corridors are among most desired locations for development in the region. However, converting single family neighborhoods into high density areas has put a lot of pressure on its school facilities and has resulted in overcrowded schools. Its public school enrollment has grown by 19% from 2009 to 2014.3 While the percentage of population under 5 years age has increased in last 10 years, those in the 5-19 age group have decreased4. Hence, there is more pressure on the elementary school facilities than others in the County. Design-wise, elementary schools, due to their size, can be imagined as a community component. There are a number of strategies that can be used to develop elementary school in urbanizing areas as a part of the neighborhood. Experimenting with space planning and building on partnership and mixed-use opportunities can help produce better designs for new schools in future. This thesis is an attempt to develop elementary school models for urbanizing areas of Arlington County. The school models will be designed keeping in mind the shifting nature of population and resulting student enrollments in these areas. They will also aim to be efficient and sustainable, and lead to the next generation design for elementary school education. The overall purpose of the project is to address barriers to elementary school development in urbanizing areas through creative design and planning strategies. To test above mentioned ideas, the Joint-Use School typology of housing +school design has been identified for elementary school development in urbanizing areas in this thesis project. The development is based on the Arlington Public School’s Program guidelines (catering to 600 students). The site selected for this project is Clarendon West (part of Red Top Cab Properties) in Clarendon, Arlington County VA.