The Mississippi Semester Project is a collaborative, critical GIS project bringing together members of Barnard College’s Empirical Reasoning Center, History Professor Premilla Nadasen, undergraduate students, and the Mississippi Low-Income Child Care Initiative (MLICCI), an advocacy organization for women on welfare and child-care providers. This project developed out of the needs of MLICCI to understand the economic security of women in Mississippi and sought to move beyond the limitations of current analyses on poverty. Measuring economic security has often been synonymous with measuring poverty and most studies on poverty, even critical studies, privilege data and/or maps and limit their analysis to either gender or race. We utilized mapping as a way to surface inequities, but we also prioritized the lived experiences of low-income women in Mississippi and worked with them to redefine economic security to include variables such as education, unemployment, and health insurance. Complicating the narrative around race and gender, we incorporated Kimberlé Crenshaw’s theory on intersectionality and mapped the effect of both race and gender on women’s economic security. This project provides a framework for developing critical GIS projects that are participatory, incorporate nuanced understandings of inequality and power, and that value oral histories and lived experiences. An experiment in pedagogy, the project also provides a framework for teaching students, primarily in the social sciences, how to incorporate quantitative analysis into advocacy work, while still utilizing qualitative analysis and elevating people’s stories.
Mississippi State University
This paper asks, and seeks to answer, the question: what makes mapping critical? I argue that most examples of ‘doing’ critical mapping tend to fall into one of two camps with very different manifestations, goals and assumptions. The first of these groups takes inspiration from Donna Haraway’s invocation of – and desire to counteract – what she calls the ‘god trick’ of ostensible technoscientific objectivity, reworking the map in order to challenge its privileged epistemological position. The second group seeks to leverage the ostensible objectivity of maps and quantitative data to prove the existence of social inequality in the spirit of what the geographer Elvin Wyly has called ‘strategic positivism’. The rest of the paper argues, however, that these two positions are not mutually exclusive, and that practitioners of critical mapping need not choose between the twin imperatives of stabilizing our understanding of the objectivity of cartographic knowledge and taking advantage of such a pervasive understanding in order to produce more just social and spatial outcomes. It is possible to simultaneously use maps to prove that inequality exists and that space matters, while also demonstrating that the ways we conventionally think about space through maps aren’t really sufficient to understand what’s actually going on in the world. Using examples from my own research on mapping the relational geographies of concentrated poverty and affluence in Lexington, Kentucky, I demonstrate one possible example of what such an approach to situated mapping might look like.
This paper takes up synthetic populations as a way to discuss the ethics of uncertainty in data-driven urban processes. Urban-tech tells us that better data is a replacement for more robust democracy; that urban issues are solved through more computation, not more deliberation; and that data can increasingly substitute for political representation. In the face of these ever louder claims for calculable urban futures we examine the logics underlying one of these urban models conceptually and methodologically. Synthetic populations describe a fictitious but statistically representative urban populace. Materially, a synthetic population is a dataset. A dataset comprised of individual-level statistics, (think of age, household income, number of children) which were calculated from aggregate data, for example, the number of 35-40 year olds per census tract. Thus, population synthesis is a method that aims to generate granular data where it didn’t exist previously, a way of estimating specificity. These fictional populations are mobilized in the form of computational depictions of human behavior and decisions in ‘agent-based models’. Synthetic urban residents are used to determine the impacts of transportation systems; to map the spread of disease; and to draw segregation over time; to inform urban policy. This paper presents ongoing research using GIS-based methods to investigate whether synthetic populations evenly represent the cities and citizens they claim to describe. It asks whether mathematical sophistication here obscures an underlying uncertainty, and, in turn, speculates on the stakes of this uncertainty for the creation of a just city.