Latino teens.
For example, the “digital edge” acknowledges the marginalized position that black and Latino teens navigate as they participate in the digital world. Black and Latino youth often live in homes with intermittent access to broadband Internet, confront outdated hardware and software, and learn in poor curriculum classrooms. In this context, “edge” is equated with being on the margins of the tech economy, tech rich households, and high quality schooling.
But the “digital edge” also acknowledges the innovative position that black and Latino teens occupy in the digital world. As we reflected on our fieldwork it became clear that so much of the literature focuses on what we might call the deficit narrative—that is, an almost exclusive examination of what black, Latino, and lower-income youth do not have in relation to a rapidly evolving tech landscape. While we understand that black and Latino teens are often bereft of key resources, what they do have is an important part of the story too. We call this the asset narrative. For example, black and Latino teens bring a number of assets to their engagement with technology, including innovative techno-dispositions and practices that have led to important modes of digital expression and community like Black Twitter and social media enhanced movements like Black Lives Matter. Media practices like these highlights the degree to which diverse users of digital media expand what is possible in the connected world.
Three specific dimensions of the digital edge inform our efforts to understand the educational environments and the technology and creative practices that we observed during our fieldwork. These dimensions are the new geography of inequality, persistent racial achievement gaps in education, and evolving trends in the adoption of media technologies. Though distinct from each other, these three elements intersect in complex ways to give an uneven shape and urgency to the making of the digital edge and the lives and futures of young people coming of age in the social and economic margins.
Income inequality in the United States is rising.5 Although some progress has been made in closing the academic achievement gaps in U.S. schools, racial and class disparities persist at the primary, secondary, and postsecondary levels. And then there are the complex shifts that mark the diffusion of technological innovation. For example, even as black and Latino teens are just as likely as their white and Asian counterparts to use the Internet, they are also more likely to grow up in homes that do not provide access to broadband, a crucial gateway to more capital-enriching forms of digital participation.
The New Geography of Inequality
A key dimension of the digital edge is the changing geography of inequality. Despite living in a hyperconnected world where physical distance is often characterized as immaterial, geography—or more precisely, where people live—still matters.6 The neighborhood that a person lives in and the resources (knowledge, schools, and people) available in that neighborhood profoundly shape his or her life chances and access to opportunity. Freeway students lived figuratively and literally on the edges of Austin and its rapidly evolving innovation and tech-driven economy.7
During our fieldwork and subsequent analysis, other insights underscored the significance of geography and its relationship to opportunity and social mobility in the United States. For example, the research of Raj Chetty and colleagues on geography and the dynamics of intergenerational mobility informed our work.8 In their analysis of administrative records on the incomes of more than forty million children and their parents, the researchers argue that specific geographic attributes, and not simply growing up in a poor neighborhood, shape the prospects for a child to rise out of poverty.
The geographical variation in intergenerational mobility detected by Chetty and his colleagues is correlated with factors such as segregation, school quality, and social capital. Upward income mobility, for example, is significantly lower in areas with large and segregated African American populations. Proxies for the quality of K–12 education include things such as test scores, dropout rates, and class sizes. Further, children growing up in communities that rank high in social capital—things like religious affiliation, greater participation in local civic organizations, low crime rates—tend to do better in terms of social mobility measures.9 Neighborhoods in which students perform well across these measures tend to have higher rates of upward mobility.10
Further, the geography of inequality in Austin reflects what Brookings Institution researchers Elizabeth Kneebone and Alan Berube identify as the “suburbanization of poverty.”11 Whereas living in a U.S. suburb was once synonymous with white flight, affluence, and upward social mobility, the story is more complex today. The trend toward greater suburban poverty accelerated during the 2000s. Between 2000 and 2010, suburbs in the nation’s largest metropolitan areas saw their poor population grow by 53 percent. Poverty in metro suburbs grew at a rate that was more than five times that of primary cities. According to Kneebone and Berube, “By 2010, the suburban poor population exceeded that in cities by 2.6 million residents.”12
Between 2000 and 2011 the suburban city that was home to Freeway tripled in size.13 In 2000, white residents made up 77 percent of the suburban population. By 2010 that percentage had decreased to 64 percent. Conversely, Latinos made up 16.7 percent of the population in 2000 compared with 27.7 percent in 2010. African Americans made up 9.5 percent of the population in 2000 and 15.5 percent in 2010. Whereas Asians were less than 1 percent (0.01 percent) of the population in 2000, that percentage climbed to 7.4 percent by 2010. The proportion of foreign-born residents living in this particular suburb increased substantially, too, growing from 6.4 percent in 2000 to 13.3 percent in 2011. By 2010, this suburban area had become what demographers refer to as a “majority-minority city.”14 The population changes did more than remake the demographics of the suburb; they also remade the public schools and educational opportunities that were available to students.
During the first decade of the new millennium, student enrollment in the Austin Metro Area School District (MASD) increased 64 percent and was driven primarily by the enrollment of Latino, black, Asian, immigrant, and lower-income students.15 From 2000 to 2010, the district reported a 115 percent increase in Asian/Pacific Islander students, a 118 percent increase in black students, and a 177 percent increase in Latino students. White student enrollment during the period decreased by 9 percent. The demographic shifts inside the city limits of Austin were considerably different during this period and reflect the racial and class dynamics of population flows in the Austin metropolitan area.16
The rise of Austin’s innovation economy has led to sharp cost of living increases that are driving families, especially working poor and poor families, to the periphery of the city. A study by University of Texas researcher Eric Tang found that Austin was unique in one important way among the nation’s fastest-growing locales: it was the only one to have a net loss of African Americans.17
Social class and economics also marked the student population shifts. During this period, the MASD reported a 194 percent increase among students receiving free lunch and a 376 percent increase in students demonstrating limited English proficiency. Like the district as a whole, Freeway experienced a sharp rise among students from lower-income households. In 1997, 13 percent of Freeway students were designated as economically disadvantaged compared with 60 percent by 2011.
Finally, 45 percent of Freeway students were identified as “at risk” of dropping out of school during our time in the field.18 Labels like these are value laden and generally have implications for how teen bodies are perceived and schooled.19 In the context of education, for example, these labels impact how students are sorted and tracked into specific