Tag Archives: data

Vulnerable Knowledge: DataRefuge and the Protection of Public Research

Judith Butler has written that “resistance is the mobilization of vulnerability,” arguing that precariousness animates action. This suggests that rather than a state of docile subjugation, vulnerability is a source of empowerment. A particularly revealing example of this relationship between power and vulnerability is evidenced in the current status of federal climate science data. This data is increasingly vulnerable, as it is now maintained by an administration that has openly disavowed its credibility. At the same time, its vulnerability is directly tied to the potential power it wields in upsetting the authority and legitimacy of this administration. The power and vulnerability of climate data are positively correlated.

On its first day in office, the incoming administration ordered all mention of climate change removed from the official White House website. This, and the new president’s vow to eliminate Obama-era environmental policies, suggest a broad mistrust of science (climate science particularly) among the executive branch and its supporters. Suspecting that this could endanger decades of accumulated scientific data and research, UPenn’s Environmental Humanities program and Penn Libraries have initiated the DataRefuge project (#DataRefuge, @DataRefuge), facilitating a series of DataRescue events around the country designed to ensure that federal climate and environmental data remain publicly available under the current administration – a clear illustration of resistance stemming from the mobilization of vulnerability.

The following is an email conversation with one of the initiative’s organizers, Patricia Kim (@lowerendtheory) – Ph.D. candidate in Art History and Program Coordinator and Graduate Fellow at the Penn Program in Environmental Humanities (PPEH).

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Amazon Go and the Erosion of Supermarket Sociability

Invited post by: Sally A. Applin (@AnthroPunk on Twitter)[1]

I recently finished my Ph.D. As a present, a friend of mine gave me a hand. Not help, which he had done during the process, but rather a battery-powered automated hand, cut off at the wrist, similar to that of Thing, the Addams Family’s servant from TV and film. In part of my thesis, and my research on automation, I’ve looked to Thing as a metaphor for IoT software automation. Thing, on TV, is a trusted friend who builds relationships with family members and can negotiate with others on their behalf. In fiction, and the representation of fiction, Thing works beautifully and embodies what a smart agent could be. It is aware of its surroundings, it builds trust. It connects people. Thing is a keeper of local knowledge. The Applin and Fischer (2013) Thing agent, is a software construct using deontic logic to encourage and support human agency, building trust in a relationship based context.  The hand my friend gave me moved on a fixed path for several seconds, and then stopped until its button was pushed again. It looked like Thing, but it was only a physical representation, a simulation of physical form. In automation, data collection is not the same as building relationships, and community knowledge cannot easily be derived from quantitative Big Data. This is one of the more serious problem with Amazon Go.

Amazon Go is a grocery store concept that allows people who have activated the Amazon Go app on their mobile phone, to walk through an “authentication” turnstile into an Amazon Go supermarket. Once inside, people can “grab” what groceries they want or need, and walk out the door, without needing to check out, because Amazon’s “computer vision, sensor fusion, and deep learning” will calculate what people take, and charge them accordingly via the app. Amazon Go has a video on their website that explains all of this, and shows people “grabbing and going” with their groceries, stuffing them into bags or just holding onto them, and walking out. In the Amazon Go video, no one is shown talking to each other. Continue reading

Archiving for the longue durée (Tools we use)

Do you backup? Good. But not good enough.

First, lets talk about backup. A good backup strategy should be regular, redundant, and involve multiple locations. Regular, so that you don’t have to worry about whether or not you backed up your data the day, week, or month before you accidentally spill your soup on your keyboard. It should be redundant, so that if your backup drive was shorted out by the same thunderstorm that destroyed your computer you still have another copy. And it should involve multiple locations so that if a fire burns down your house there is still a copy of your most important stuff at your parent’s house.

There are lots of ways to make sure you meet these basic requirements. My solution involves:

I feel pretty good about this system. It may not be perfect, but it meets the minimal requirements I listed above. However, it isn’t good enough for me, and it might not be good enough for you either… Continue reading

Dataverse: an open source solution for data sharing

When you think of scholarship you might think first of publications, articles and books, but that is just the final product. Yes it is polished through countless hours of research, writing, and responding to reviewers, however all that work is built on an even more time consuming foundation of collecting raw materials. In cultural anthropology this includes field notes, journals, marked up literature, audio recordings, transcripts, and maybe photographs and video. I think I even have a few 3-D objects squirreled away in banker’s boxes. Although we seldom refer to it as such all of this is “data,” it is information awaiting interpretation.

We take great pride in our finished products. Peer reviewed publications are still the coin of the realm. Our attitudes towards data in cultural anthropology are less clear. Are our data worth saving? What have you done with your data? How would you feel about sharing your data with others?
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Ethnographers as Writers: Theory and Data – Part II

So I’m staring at some fieldnotes and trying to sort out the best way to blend my theoretical analysis with my ethnographic data. Where to start? How to find the right balance? Once again, I decided to contact fellow ethnographers to gather insights about their writing processes. Sociologist Olga Shevchenko also struggles with what parts of her fieldnotes to include:

I almost never know in advance which parts of the field notes will go into the text, because it takes me some time, and a lot of writing, to figure out what it is exactly that I am going to argue! With interviews, it’s different. There are some turns of phrase that seem to leap off the page, and these are usually those that capture experience in a fresh or complex way. I also tend to notice when a turn of phase, or a metaphor emerges more than once. When I heard a third person compare their everyday life with living on a volcano, I knew it was going to be in the book in a major way. But it also got me thinking about what this metaphor accomplished, which sent me right back to the field notes. When I can’t find a place in the text for an evocative image or turn of phrase that I hear from a respondent, this causes me great torments!

Coding your fieldnotes the old fashioned way
Coding your fieldnotes the old fashioned way

Like Olga, I now spend a lot of time reading my fieldnotes and deciding what material I want to include before I figure out my core argument, a process sometimes called “grounded theory,” a way of incorporating theoretical insights that emerge organically from the fieldwork. I also search for great quotes or turns of phrase that capture something about the everyday experience of my informants.

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Ethnographers as Writers: Theory and Data – Part I

There's nothing more intimidating than a blank page.
There’s nothing more intimidating than a blank page.

Every ethnographer must find a balance between theory and data. Our fieldwork and our specific case studies render our work original, but this work fails to be scholarly if it lacks dialogue with larger theoretical concerns. When writing the dissertation the literature review section remains de rigueur, but most acquisitions editors demand that this section be exorcised from the eventual book manuscript. This means that the theoretical insights inspired by your participant observation must somehow be woven into the final text so as to elucidate your original ideas without burying the reader under an avalanche of information about what other scholars, studying other cases, have said before you.

The task of integrating theory proves difficult for even the most experienced ethnographers, and different scholars maintain varying opinions on its importance. In a 1999 article, anthropologist Ruth Behar argues that theory for theory’s sake undermines the potential vibrancy of ethnographic writing:

What I do find tiresome is the habit of using whatever theory happens to be fashionable…as a substitute for really engaging the tough questions posed by those whom we encounter on our journeys as ethnographers. When ethnographers working in far corners of the globe are all citing the same two pages from the work of the latest trendy theorist, without reflecting on the politics of how that theory travels, you can be sure they have killed the life in their ethnography.

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