Archive for Internet
The archived video(s) of An Exploration of Whiteness and Health A Roundtable Discussion
is available beginning here (updated 12/16/12):
The examination of whiteness in the scholarly literature is well established (Fine et al., 1997; Frankenberg, 1993; Hughey, 2010; Twine and Gallagher, 2008). Whiteness, like other racial categories, is socially constructed and actively maintained through the social boundaries by, for example, defining who is white and is not white (Allen, 1994; Daniels, 1997; Roediger, 2007; Wray, 2006). The seeming invisibility of whiteness is one of its’ central mechanisms because it allows those within the category white to think of themselves as simply human, individual and without race, while Others are racialized (Dyer, 1998). We know that whiteness shapes housing (Low, 2009), education (Leonardo, 2009), politics (Feagin, 2012), law (Lopez, 2006), research methods (Zuberi and Bonilla-Silva, 2008) and indeed, frames much of our misapprehension of society (Feagin, 2010; Lipsitz, 1998). Still, we understand little of how whiteness and health are connected. Being socially assigned as white is associated with large and statistically significant advantages in health status (Jones et al., 2008). Anderson’s ground breaking book The Cultivation of Whiteness (2006) offers an exhaustive examination of the way whiteness was deployed as a scientific and medical category in Australia though to the second world war. Yet, there is relatively little beyond this that explores the myriad connections between whiteness and health (Daniels and Schulz, 2006; Daniels, 2012; Katz Rothman, 2001). References listed here.
The Whiteness & Health Roundtable is an afternoon conversation with scholars and activists doing work on this area.
The roundtable is sponsored by the Advanced Research Collaborative (ARC) and the Critical Social & Environmental Psychology program at the Graduate Center CUNY. The event is hosted by Michelle Fine (Distinguished Professor, Social Psychology, Women’s Studies and Urban Education), Jessie Daniels (Professor, Urban Public Health and Sociology) and Rachel Liebert, (PhD Student, Critical Social/Personality Psychology).
With the re-election of President Obama, white people who rooted for the other guy took to various forms of digital media and unleashed their disappointment. Some white folks went a good deal farther than disappointment into overt racism, like this white woman from California who posted her racism on Facebook. Jezebel pulled together a rogues’ gallery of racist tweets.
The gallery at Jezebel prompted some geographers to create a map of all the racist tweets.
The enterprising folks at Floating Sheep used software they created called DOLLY to collect geocoded tweets for the week beginning November 1. In other words, it’s possible to search Twitter by both location and key word (some other examples here). If I understand it correctly, the DOLLY software allows this search process to be further refined to get data at a more granular level.
What they came up with is a map that allows us to understand, at a glance, how these everyday acts of overt racism are spatially distributed in the U.S.
This is valuable work and just the kind of thing that I'd think sociologists would be interested in doing (but I digress, slightly). The methodology here, buried in the footnotes on the original post, is a worth exploring a little further.
The research questions they pose are: "Are racist tweets relatively evenly distributed? Or, do some states have higher specializations in racist tweets?"
To answer these questions, they sampled the universe of tweets. Specifically, they: "collected tweets that contained the text 'monkey' or 'nigger' AND also contain the text 'Obama' OR 'reelected' OR 'won.' A quick, and very unsettling, examination of the search results revealed that this indeed was a good match for our target of election-related hate speech. We end up with a total of 395 of some of the nastiest tweets you might possibly imagine. And given that we're talking about the Internet, that is really saying something."
Following that, they took the number of "hate tweets" by state and divided by the total number in the U.S., that became the numerator. Then, they got their denominator by doing the same for all the tweets in the state, divided by all the tweets in the U.S., which is easier to understand expressed as a formula:
(# of ALL Tweets in State / # of ALL Tweets in USA)
Based on this, they assign a number, or a Location Quotient (LQ), for "Post Election Racist Tweets." They then rank order states based on their LQ's.
The results they end up with (Alabama, Mississippi, Georgia end up with 3 highest LQ scores) are less interesting than their map and clever methodology. In their analysis, the writers do well to note that the "prevalence of post-election racist tweets is not strictly a southern phenomenon," but the ranking of the LQ scores by states makes the opposite case.
I want to suggest here that the problem is two-fold: 1) the way the research question is posed and 2) the state-level of analysis.
The researchers here frame their question in terms of state boundaries and posit something of a false dichotomy between "even distribution" of racist tweets on the one hand, and, "states that specialize" in racist tweets on the other hand. As anyone who has taken an undergraduate methods class can tell you, this research question shapes the kind of data collection you do, and the analysis you come up with at the end.
The state-level of analysis here is something of a distraction. I understand that since we just went through a presidential election, people are thinking in terms of "states" - swing states, blue states, red states, who carried the state - but here, it makes less sense.
What I see when I look at this map are population centers. Take my home state, of Texas. The red dots there are clustered around places where there's population density - Houston, Dallas, and more along the I-35 corridor. And, compare that to where I live now, on the East Coast. There are red dots all along the Northeast corridor of I-95. At a glance, it looks like racist tweets are not evenly distributed across the U.S. but are concentrated where white people live.
Again, let me say, I appreciate this work immensely, but I think that the state-level questions are the least interesting, and ultimately least revealing set of questions for mapping racism through digital media. Instead, I'd be interested in seeing some other basic demographic info about percentage of white people in the population and the proportion of racist tweets. My guess is that the LQ is highest where there is the highest proportion of white people, but that, as academics are so fond of saying, is an empirical question worth investigating.
More in posts to come on calling out racism in digital media, and the growing backlash against it.
In the early days of the Internet, there was a lot of talk about “access” to technology. Alongside that was a lot of concern that only people who are white and rich had access to technology, while people who were poor and/or black or brown (and sometimes women) didn’t have access to technology. This concern about who had technology and who didn’t got called “the digital divide” and lots of research got done on it.
Digital Divide(s)? In an initial study conducted by the Census Bureau under the direction of the U.S. National Telecommunications and Information Administration, African-Americans were found to have lower rates than whites in both computer equipment ownership and telephone service (“Falling Through the Net,” NTIA, 1995). Even though the original report was subtitled, “A Survey of ‘Have Nots’ in Rural and Urban America,” the findings about race are what made headlines. The finding about differences in computer ownership between whites and blacks was widely reported and quickly became known as ‘the digital divide.’ It also sparked an entire subfield of research within Internet studies relating to race. The initial focus on computer ownership shifted in subsequent versions of the study to Internet access and the second report included “digital divide” in the title (“Falling Through the Net II: New Data on the Digital Divide,” NTIA, 1998). These initial “divides” in ownership and access have largely vanished now (for example: Leggon, 2006, ““Gender, Race/Ethnicity and the Digital Divide,” in edited by Mary Frank Fox, Deborah G. Johnson, and Sue V. Rosser, (eds.) Women, Gender and Technology, University of Illinois Press, 2006). Still some researchers subsequently identified “second level divides” that focused on the relationship between skills, “Internet literacy” and Internet usage (Hargittai, “Second-Level Digital Divide: Differences in People’s Online Skills,” First Monday 7(4), 2002).
he rhetoric of “digital divides” has also been heavily critiqued by some scholars as a “disabling rhetoric” that marginalizes people of color as technological innovators (e.g., Anna Everett, (2004) ‘On Cyberfeminism and Cyberwomanism: High-Tech Mediations of Feminism’s Discontents’, Signs 30(1):1278-86; Michelle Wright, (2005) ‘Finding a Place in Cyberspace: Black Women, Technology and Identity,’ Frontiers 26(1):48-59).
Selwyn (“Apart from technology: Understanding people’s non-use of information and communication technologies in everyday life,” Technology in Society, 25 (1), 99-116.) contends that digital divide formulations rely on the assumption that Internet access and usage is desirable for everyone, when in fact, people might not be using the Internet because they don’t see a social beneﬁt in doing so. Brock (2006) extends this argument to race and explains that slower Internet adoption rates among Blacks may have more to do with the lack of culturally relevant content online for Blacks rather than any lack of “Internet literacy.”
Then came Mobile Technology. Much has changed since the mid-1990s when ‘digital divide’ research began and computer ownership and Internet access meant sitting before a desktop machine with a wire plugged into a wall. Today, being connected to the Internet often means having a “smart phone” (e.g., a phone that enables users to access the Internet).
Ten years ago, Howard Rheingold (2002) accurately predicted the ‘next social revolution’ in computing would be the advent of mobile technologies, and this development has had important implications for race, racism and Internet studies.
Mobile phones enabled with Internet access are approaching ubiquity and with that, bridging some of the divides noted in an earlier era. According to the Pew Research Center’s Internet & American Life Project (a rich resource of data), cell phone and wireless laptop Internet use have each grown more prevalent between 2009-2010. African-Americans and English-speaking Latinos continue to be among the most active users of the mobile web, for example:
- Mobile phone ownership is higher among African-Americans and Latinos (87%) than among whites (80%)
- African-American and Latino mobile phone owners take advantage of a much greater range of their phones’ features compared with white mobile phone users
- Among Latinos, 29% of mobile-phone users surf the Internet on their device, compared to 12% of mobile-phone-owning whites.
So what does all this research tell us about race and technology? It’s still way too early to know how these patterns might shift again, but it seems clear that early predictions about “digital divides” between technological “haves” and “have nots” – especially along stark racial lines – were overstating what the evidence suggested. It also seems very likely that many of those dire early reports about “minorities left behind” were engaging in the disabling rhetoric of racism’s low expectations. As African Americans and Latinos lead the adoption of mobile technology here in the U.S. is among the more fascinating developments as it over turns those expectations.
The Internet is changing us. It’s changing how we acquire knowledge, how we communicate, how we connect with one another. Today, some 15 years into the scholarship of the Internet, researchers are just beginning to look at how race and racism are (and are not) changing by and through the way we use the Internet. Over the next week or so, I’m going to be writing a series of posts about what the research tells us about race and racism online. I’ll also point out spots along the way that, in my view, are understudied and need someone to turn a critical eye toward.
RACE & STRUCTURE OF THE INTERNET. While we may not think of the Internet as having been invented, but in fact it was, at a particular place and time. The combination of technologies that has come to be known as the popular Internet was developed in a number of specific geographic places, institutional contexts and historical moments. For more about this history, see Berners-Lee, T. and M. Fischetti Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by Its Inventor, 2nd ed. (New York: HarperCollins, 2008). This narrative is compelling, but to date, no one has offered a thorough examination of the ways that race was, and continues to be, implicated in the structure of the invention of the Internet.
INFRASTRUCTURE & DESIGN. Scholar Tyrone Taborn notes that the role of black and brown technology innovators has largely been obscured (Taborn, 2007). As Sinclair observes, “The history of race in America has been written as if technologies scarcely existed, and the history of technology as if it were utterly innocent of racial signiﬁcance” (Sinclair, B. (ed.) (2004) Technology and the African-American Experience: Needs and Opportunities for Study. Cambridge, MA: MIT Press, p.1).
Yet, race is implicated in the very structure of the “graphic user interface” (GUI). For example, Anna Everett observes that she is perpetually taken aback by DOS-commands designating a “Master Disk” and “Slave Disk,” a programming language predicated upon a digitally conﬁgured “master/slave” relationship with all the racial meanings coded into the hierarchy of command lines (Everett, 2002, ‘The Revolution Will Be Digitized: Afrocentricity and the Digital Public Sphere’, Social Text 20(2):125-146., p.125).
Nakamura writes that the drop-down menus and clickable boxes that are all too often used to categorically define `race’ online are traced back to the fact that race is a key marketing category (Nakamura, 2002). Beyond the selection and targeted-marketing via race, elements of the interface are racialized. The nearly ubiquitous white hand-pointer acts as a kind of avatar that in turn becomes ‘attached’ to depictions of white people in advertisements, graphical communication settings, and web greeting cards (White, M., The body and the screen: theories of Internet spectatorship. Cambridge, MA: MIT Press, 2006). The images of racial or ethnic minorities and their relationship to IT infrastructure and design is either to the role of consumers or of operators of the technological wizardry created by whites.
Assumptions about the whiteness embedded in the infrastructure and design gets spoken when there are ruptures in that sameness, such as the introduction of an African-American-themed web browser, Blackbird which I wrote about here in 2008. While Blackbird caused quite a stir among those who had operated on the assumption of a race-blind Internet, the development of a racially-themed browser is not qualitatively different from, but rather an extension of, the racially targeted marketing facilitated by drop-down menus and clickable boxes.
Tomorrow, I’ll be back tomorrow to discuss some of what the research tells us about race and mobile technology.
The Vancouver Sun has a story about a new cupcake/cake glaze product. The commercial company DH had the film company Filmaka create some YouTube commercials
designed to portray how the new product “makes dessert sing.” The first video in the series was themed “hip hop”, created by director Josh Biner. In it, a series of vanilla cupcakes sit on a counter until topped with the chocolate flavoured Amazing Glazes – as the glaze hits them they sprout lips and eyes and break into singing and dancing.
Clearly, the company’s media staff is not familiar with (or did not think it serious racism) the long racist tradition of blackface minstrelsy– in which images of Black Americans (such as big lips and buggy eyes) are stereotyped in extreme and degrading ways for white entertainment—now for at least 180 years or so
The Sun notes too the music that went with the commercials, which were quickly pulled from Youtube when there were protests:
[They] chose not to soundtrack the commercial with hip hop, but an instrumental electronic and beatbox track. Hip hop magazine The Source furthers the argument: “First, they aren’t even rapping! If you’re going to have inanimate food objects make music then they should at least have a real song or beat.”
Reportedly, nearly 20,000 people viewed these racist-image commercials. Was this commonplace ignorance of our extremely racist history, or much more? I suspect many whites (and some others) today do not see this type of conventional racial imagery as racist mocking and like old minstrelsy.