Tag Archives: big data

The Person in the (Big) Data

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This edition of is jam-packed with methods for doing people-centred digital research and is edited by Heather Ford, newly-appointed Fellow in Digital Methods at the University of Leeds and thus super excited to understand her role as an ethnographer who (also) does digital methods.

Today we launch the next edition of Ethnography Matters entitled: ‘Methods for uncovering the Person in the (Big) Data’.  The aim of the edition is to document some of the innovative methods that are being used to explore online communities, cultures and politics in ways that connect people to the data created about/by them. By ‘method’, we mean both the things that researchers do (interviews, memo-ing, member checking, participant observation) as well as the principles that underpin what many of us do (serving communities, enabling people-centred research, advocating for change). In this introductory post, I outline the current debate around the risks of data-centric research methods and introduce two principles of people-centric research methods that are common to the methods that we’ll be showcasing in the coming weeks.

As researchers involved in studying life in an environment suffused by data, we are all (to at least some extent) asking and answering questions about how we employ digital methods in our research practice. The increasing reliance on natively digital methods is part of what David Berry calls the “computational turn” in the social sciences, and what industry researchers recognize as moves towards Big Data and the rise of Data Science.

digitalmethods

Digital Methods‘ by Richard Rogers (2013)

First, a word on digital methods. In his groundbreaking work on digital methods, Richard Rogers argued for a move towards natively digital methods. In doing so, Rogers distinguishes between methods that have been digitized (e.g. online surveys) vs. those that are “born digital” (e.g. recommender systems), arguing that the Internet should not only be seen as an object for studying online communities but as a source for studying modern life that is now suffused by data. “Digital methods,” writes Rogers, “strives to follow the evolving methods of the medium” by the researcher becoming a “native” speaker of online vocabulary and practices.

 

The risks of going natively digital

There are, however, risks associated with going native. As ethnographers, we recognize the important critical role that we play of bridging different communities and maintaining reflexivity about our research practice at all times and this makes ethnographers great partners in data studies. Going native in this context, in other words, is an appropriate metaphor for both the benefits and risks of digital methods because the risk is not in using digital methods but in focusing too much on data traces.

Having surveyed some of debates about data-centric methodology, I’ve categorized the risks according to three core themes: 1. accuracy and completeness, 2. access and control, 3. ethical issues. Read More…

Falling in: how ethnography happened to me and what I’ve learned from it

guest author Austin Toombs

Austin Toombs

Editor’s Note: Austin Toombs (@altoombs) brings a background in computer science and a critical sensibility to his ethnographic research on maker cultures.  He explores the formation of maker identities in his research, focusing on how specific sites such as hackerspaces, makerspaces, Fab Labs, and other co-working spaces intersect with the politics of making, gendered practices, urban vs. rural geographies, and creative hardware and software developments. Austin is a PhD student in Human Computer Interaction Design in the School of Informatics and Computing at Indiana University. He is a member of the Cultural Research In Technology (CRIT) Group, and is advised by Shaowen Bardzell and Jeffrey Bardzell. He is also a member of ISTC-Social.


My research as a PhD student began by looking at cultures of participation surrounding hobbyist programming. I was—and still am—interested in the fuzzy-gray area between work and play, and as someone who misses the puzzle, thrill, and flow of programming, these communities were great starting points for me. Working on this research led me, almost inevitably, toward my ethnographic work with my local hackerspace and the broader maker community. In this context, I have seen how this local community embraces the work/play ambiguity, how it can function primarily as a social environment, and how it works to actively cultivate an attitude of lifelong, playful, and ad hoc learning. In this post I explore the role ethnography played in my work and how the ethnographic approach helped me get to these insights. I also discuss some of the complications and issues I have run into because of this approach, and how I am working toward solving them. For more information, feel free to contact me!

hackerspaces

the role of ethnography in my work

My first encounter with the concept of a hackerspace came from my initial research on hobbyist programmers. I remember nearly dancing with excitement when I realized that the city I lived in happened to have a hackerspace, because I knew immediately that I would be joining them in some capacity, if not for research, then for my own personal enjoyment. The first few visits to the space were exploratory; I wanted to see what was going on, how the members and regular attendees interacted with each other, and whether or not this seemed like a good fit for my research.

My initial goal was to use the site as a potentially endless supply of case studies to explore my questions about work and play. Thankfully, I realized fairly early on that this case-study-first approach would not work for me. Instead, I found myself drawn to the overall narrative of the hackerspace and its members. How did this particular maker community form? What did the members do for their day jobs? How did they become ‘makers’? What do they think about themselves, and how has becoming a member of this community influenced that?

Read More…

Studying Up: The Ethnography of Technologists

Nick Seaver

Editor’s Note: Nick Seaver (@npseaver) kicks off the March-April special edition of Ethnography Matters, which will feature a number of researchers at the Intel Science and Technology Center for Social Computing on the forefront of exploring the cultures of hackers, makers, and engineers.

Nick’s post makes the case for the importance of “studying up“: doing ethnographies not only of disempowered groups, but of groups who wield power in society, perhaps even more than the ethnographers themselves.

Nick’s own research explores how people imagine and negotiate the relationship between cultural and technical domains, particularly in the organization, reproduction, and dissemination of sonic materials. His current project focuses on the development of algorithmic music recommendation systems. Nick is a PhD candidate in sociocultural anthropology at UC Irvine. Before coming to UCI, Nick researched the history of the player piano at MIT. 


When people in the tech industry hear “ethnography,” they tend to think “user research.” Whether we’re talking about broad, multinational explorations or narrowly targeted interviews, ethnography has proven to be a fantastic way to bring outside voices in to the making of technology. As a growing collection of writing on Ethnography Matters attests, ethnography can help us better understand how technology fits into people’s everyday lives, how “users” turn technologies to unexpected ends, and how across the world, technologies get taken up or rejected in a diverse range of cultural contexts. Ethnography takes “users” and shows how they are people — creative, cultural, and contextual, rarely fitting into the small boxes that the term “user” provides for them.

But ethnography doesn’t have to be limited to “users.”

Engineers in context. cc by-nc-nd 2.0 | http://www.flickr.com/somewhatfrank

My ethnographic research is focused on the developers of technologies — specifically, people who design and build systems for music recommendation. These systems, like PandoraSpotifySongza, or Beats Music, suggest listening material to users, drawing on a mix of data sources, algorithms, and human curation. The people who build them are the typical audience for ethnographic user studies: they’re producing technology that works in an explicitly cultural domain, trying to model and profile a diverse range of users. But for the engineers, product managers, and researchers I work with, ethnography takes a backseat to other ways of knowing people: data mining, machine learning, and personal experience as a music listener are far more common sources of information.

Ethnographers with an interest in big data have worked hard to define what they do in relation to these other methods. Ethnography, they argue, provides thick, specific, contextualized understanding, which can complement and sometimes correct the findings of the more quantitative, formalized methods that dominate in tech companies. However, our understandings of what big data researchers actually do tend to lack the specificity and thickness we bring to our descriptions of users.

Just as ethnography is an excellent tool for showing how “users” are more complicated than one might have thought, it is also useful for understanding the processes through which technologies get built. By turning an ethnographic eye to the designers of technology — to their social and cultural lives, and even to their understandings of users — we can get a more nuanced picture of what goes on under the labels “big data” or “algorithms.” For outsiders interested in the cultural ramifications of technologies like recommender systems, this perspective is crucial for making informed critiques. For developers themselves, being the subject of ethnographic research provides a unique opportunity for reflection and self-evaluation.

Starbucks Listeners and Savants

Among music tech companies, it is very common to think about users in terms of how avidly they consume music. Here is one popular typology, as printed in David Jennings’ book Net, Blogs, and Rock ‘n’ Roll:

Read More…

March-April 2014: Studying Hackers, Makers, and Engineers

Editor Morgan G. Ames

This month’s theme – ethnographies of hackers, makers, and engineers – is edited by Morgan G. Ames, who made the transition from being a hacker to studying them herself.

Stories abound of the translation work that ethnographers in industry do to make the experiences of those they observe – the ‘users’ – legible to engineers, designers, marketers, and others in the businesses that employ them. Lucy Suchman, one of the first and most inspiring critical ethnographers in industry, referred to the expectations she encountered for this translation-work in her own job at Xerox PARC as ‘throwing results over the wall.’ These results may take the form of the dreaded ‘implications for design’ that ethnographers are sometimes asked to generate, whether for employers or ACM conferences.

What happens, though, when the ethnographic gaze is turned back on those who are usually the beneficiaries of this translation-work? Lucy Suchman explored this in her groundbreaking book, Plans and Situated Actions, drawing on her experiences at Xerox PARC in the 1980s. Alongside Lucy, a growing number of ethnographers from both academia and industry have been exploring the cultures of scientists, analysts, and others like them in a bid to help the outside world better understand them – and for them to better understand themselves.

The March-April edition of Ethnography Matters will continue this ethnographic inversion by featuring guest authors who are exploring the cultures of hackers, makers, and engineers. The authors hail from the Intel Science and Technology Center for Social Computing, a five-university alliance advised by Intel’s Genevieve Bell (another inspiring industry ethnographer). This group is working on new ways of bridging the academy-industry divide, and many of its members are exploring various aspects of hacker, maker, and engineer cultures.

Caution: Hackers Thinking!

The first post, by Nick Seaver (@npseaver), makes the case for studying technologists as a form of ‘studying up’ – of putting those who wield power under the ethnographic lens. He relates this to his own research on music recommendation systems like Pandora and Spotify.

Second,  Austin Toombs (@altoombs) tells us how he “fell in” to doing ethnographic research on a local hackerspace, how he has navigated the line between ethnography, participation, and activism, and what ethnography has taught him about hackers and himself.

Katie Pine (@khpine) and Max Liboiron (@maxliboiron) then discuss their work in health informatics and civil engineering cultures to show how measurement itself is performative, and how ethnography is particularly well-suited to accounting for this performativity.

Lilly U. Nguyen (@deuxlits) tells us how in her own work on the ethnography of software in Vietnam, she both studies and embodies “diaspora” – and she shares the insights that diaspora has given her.

Marisa Leavitt Cohn then considers how NASA engineers approach concerns of legacy, inheritance, and survival of computational practices as they contemplate the end of life of the mission.

Silvia Lindtner (@yunnia) and  (@femhacktweets) round out the theme with a post that shares three stories of hackers and makers in China. Their observations complicate the celebratory story of hacking/making, giving us a richly detailed look at some of the real challenges and triumphs in this very active space.

 

Tell Me More danah boyd: an interview with the author of “It’s Complicated: The Social Lives of Networked Teens”

MSR3sm-sq danah boyd (@zephoria) is a Principal Researcher at Microsoft Research, a Research Assistant Professor in Media, Culture, and Communication at New York University, and a Fellow at Harvard’s Berkman Center. In 2009 Fast Company named boyd one of the most influential women in technology. Also in 2010, Fortune named her the smartest academic in the technology field and “the reigning expert on how young people use the Internet.” Foreign Policy named boyd one of its 2012 Top 100 Global Thinkers “for showing us that Big Data isn’t necessarily better data”. danah just published, It’s Complicated: The Social Lives of Networked Teens.  

There’s this idea that hard-core techies are code geeks. But hard-core techies also look like ethnographers. A tech ethnographer not only has to understand cultural code, but the mechanisms for how software design links back up to tech practices. I sat down with one of the most well known tech ethnographers of our time, danah boyd (@zephoria). 

Over breakfast at The Ace Hotel’s Breslin, danah and I talked about her career. This fascinating and personal interview reveals danah’s journey through industry and academia.

We’re also excited to have danah’s interview launch Ethnography Matter’s second column, Tell Me More,  featuring interviews with people who are pushing the boundaries of ethnography in unconventional and exciting ways. We conduct the first interview and then post a follow up interview with crowd-sourced questions from the audience. 

Post your follow-up question for danah in the comments or tweet it with the hashtag #askdanah by March 10. danah will select her favorite questions to answer in her second interview!  

Tricia: danah, I’m super excited that we get to talk ethnography over some yummy breakfast food! Earlier last year, you were inducted into the SXSW Hall of Fame.  An ethnographer being validated by geeks! I was beyond excited when I heard this news. How did you feel when you found out?

danah: SXSW has been a very important event to me for a long time. I learned so much about the tech industry through that conference by spending late nights drinking with entrepreneurs and makers. I actually got many a job that way too. It was at SXSW where Ev Williams and I started debating blogging practices. He hired me to work for him that summer.  Oh, and SXSW was where I met my partner.

Tricia: What? Are you serious?

danah: ::laugh:: Ayup!  And now we have a baby who we’re taking back to SXSW this year.

Tricia: Shut up. That is so sweet. Where did you guys meet at SXSW?

danah. At a Sleater-Kinney show.

Tricia: That’s awesome.

danah: It’s just funny to be honored there because I’ve selfishly gotten so much out of the conference.

Tricia: Well I remember very clearly when I read the transcript of the keynote you delivered at SXSW in 2010. It was about Facebook’s issues with privacy. Your talk generated so much discussion. How did you settle on this topic?

danah: I thought, what could I do that would provoke this audience to think? I saw it as a political platform; not big P but small p. I wanted to use this opportunity to challenge norms inside tech industry. I decided to take on the underlying values and beliefs in tech industry regarding privacy because my research was showing that the rhetoric being espoused was naïve. My topic was not surprising for academics, but it was for practitioners. Read More…

Ethnography in Communities of Big Data: Contested expectations for data in the 23andme and FDA Controversy

IMG_2834 Brittany Fiore-Silfvast (@brittafiore) is a PhD candidate in Communication at the University of Washington and she holds an MA in sociocultural anthropology from Columbia University. Her research focuses on the relationship of technology and emerging cultural and organizational forms. Her work cited in this article was supported in part by an NSF Doctoral Dissertation Improvement Grant and an Intel grant.

Editor’s note: One of the disciplines big data is most strongly influencing is medicine, and here Brittany Fiore-Silfvast (@brittafiore) applies her expertise to examine the interplay between health and technology to understand the implications of today’s unprecedented levels of patient data collection and analysis (although, notably, seldom including access to the data by those very patients who produced it).

Brittany hits upon a key issue with her post: seeing “big data” as a means of eliminating uncertainty through statistical analysis. While the elimination of uncertainty through statistical analysis is nothing new, the difference today is the scale at which collection and analysis of such data is unfolding and the diversity of the fields in which it is occurring.

Read on to discover the nature of conflict between the main personal genetics testing company 23andme, the importance of and difference between big data, small data, thick data, and DaM data, and the role that “Blue Suede Shoes” play in all of this.

For more posts from this EPIC edition curated by  editor Tricia Wang (who gave the opening keynoted talk at EPIC this year), follow this link.
23andme box

Scott Beale / Laughing Squid laughingsquid.com

Across the field of health and wellness there is a lot of talk about data, from consumer self-tracking and Quantified Self data, to data-driven, personalized health care, to data-intensive, crowd sourced, scientific discovery. But what are these different stakeholders talking about when they talk about data and are they talking about the same thing?

At EPIC, in the “Big Data/Ethnography or Big Data Ethnography” session, I presented on this topic drawing from our ethnography of the impact of consumer big and small data on institutions of healthcare. In this post I use the recent controversy between the FDA and personal genetics testing company, 23andme, to exemplify many of the concepts my co-author, Dr. Gina Neff, and I develop in our EPIC paper “What we talk about when we talk data: Valences and the social performance of multiple metrics in digital health”, rather than simply re-present them.  I also demonstrate how ethnography can be leveraged in the context of so-called “big data” or data intensive transformations in science and practice. Read More…

I’m Coming Out: Four Awkward Conversations for Commercial Ethnographers

459372_561559630554768_2122767149_o With an approach built on ethnography and design methodologies, Drew Smith (@drewpasmith) delights in bringing consumer and client to the conference table. In the process, he works with them to co-create game-changing products, services and businesses for some of the world’s biggest companies.  Drew shapes culture and strategy at Seren Partners. He blogs occasionally at DownsideUpDesign and posts pictures of cars, mostly side-on, here.

Editor’s Note: I asked Drew Smith (@drewpasmith) to kick off our January EPIC theme because of his background as a designer and a tweet that he had sent. Until Drew attended EPIC 2103, he was hesitant to say that he was an ethnographer in certain professional contexts. But after listening to my opening keynote for EPIC 2013, he tweeted, “Today, I’m coming out. I’m an @ethnographer!” We had an interesting chat afterwards where Drew explained to me why he would even need to “come out of the closet.” It was a fascinating conversation and one that many readers will relate to, especially if you work in a design or strategy agency where you may be the one person with very proficient ethnographic skills.

So I thought it would be interesting to hear how someone with a strong design background experienced EPIC 2013. In Drew’s first guest post on Ethnography Matters, he urges designers and strategists with ethnographic skills be brave: commercial ethnography needs to come out of the closet. Drew provides some conversations that will help us get there.

For more posts from this January EPIC edition curated by contributing editor Tricia Wang, follow this link.

Slide145Over the course of my career I’ve developed an unwavering belief in the transformative power of ethnography. I’ve used its tools and techniques to bring about positive change for my clients, shaping products, services, businesses and brands with the rich, people-centred insight it can bring to bear.

Yet until recently, I’d never called myself an ethnographer; I’ve always been an automotive designer-turned-strategist. This is the story of how that came to change.

Ethnography by Another Name

During my student years, I’d come to know a London co-creation agency called Sense Worldwide. They had a mission to “make things better, by making better things”, a concept that was deeply appealing to an idealistic young designer.

We built trust and I allowed them to explore how I was using social networks (the early days of Facebook, the mid-life crisis of Gaydar) and why I was dreaming of upgrading my Sony Ericsson K750 to a Nokia N95. Together, we came up with ideas to make my world of mobile technology better. I loved the experience so much that I wanted to work for them.

Desperate, keen and with none of the ethnography or anthropology qualifications that usually accompanied their recruits, Sense Worldwide nevertheless took a chance. Without realising it, I became an ethnographer by the back door.

During my time there, I witnessed the profound impact that ethnographic research could have. The stories and insight pulled back from the field transformed not only  the way new products and services were developed, but also how companies were led and run.

I noticed, however, that getting ethnography on the table with prospective clients was a challenge. It was often perceived as expensive and more than a little quirky. To ease the sales process, we adopted a series of jazz-handed 1-liners that got ethnography sold, perhaps overly so. Yes, we conducted ethnographic research, but sometimes our practice failed to live up to the over-the-top expectations set by language designed to hide our commercial awkwardness. Read More…

Big Data Needs Thick Data

Tricia Wang

Tricia Wang

Editor’s Note: Tricia provides an excellent segue between last month’s “Ethnomining” Special Edition and this month’s on “Talking to Companies about Ethnography.” She offers further thoughts building on our collective discussion (perhaps bordering on obsession?) with the big data trend. With nuance she tackles and reinvents some of the terminology circulating in the various industries that wish to make use of social research. In the wake of big data, ethnographers, she suggests, can offer thick data. In the face of derisive mention of “anecdotes” we ought to stand up to defend the value of stories.

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image from Mark Smiciklas at Intersection Consulting

image from Mark Smiciklas at Intersection Consulting

Big Data can have enormous appeal. Who wants to be thought of as a small thinker when there is an opportunity to go BIG?

The positivistic bias in favor of Big Data (a term often used to describe the quantitative data that is produced through analysis of enormous datasets) as an objective way to understand our world presents challenges for ethnographers. What are ethnographers to do when our research is seen as insignificant or invaluable? Can we simply ignore Big Data as too muddled in hype to be useful?

No. Ethnographers must engage with Big Data. Otherwise our work can be all too easily shoved into another department, minimized as a small line item on a budget, and relegated to the small data corner. But how can our kind of research be seen as an equally important to algorithmically processed data? What is the ethnographer’s 10 second elevator pitch to a room of data scientists?

…and GO!

Big Data produces so much information that it needs something more to bridge and/or reveal knowledge gaps. That’s why ethnographic work holds such enormous value in the era of Big Data.

Lacking the conceptual words to quickly position the value of ethnographic work in the context of Big Data, I have begun, over the last year, to employ the term Thick Data (with a nod to Clifford Geertz!) to advocate for integrative approaches to research. Thick Data uncovers the meaning behind Big Data visualization and analysis.

Thick Data: ethnographic approaches that uncover the meaning behind Big Data visualization and analysis.

Thick Data analysis primarily relies on human brain power to process a small “N” while big data analysis requires computational power (of course with humans writing the algorithms) to process a large “N”. Big Data reveals insights with a particular range of data points, while Thick Data reveals the social context of and connections between data points. Big Data delivers numbers; thick data delivers stories. Big data relies on machine learning; thick data relies on human learning.

Read More…

Reaching Those Beyond Big Data

Editor’s Note: Opening up the Stories to Action edition is Panthea Lee’s @panthealee moving story about a human trafficking outreach campaign that her company, Reboot, designed for Safe Horizon.  In David Brook’s recent NYT column, What Data Can’t Do, he lists several things that big data is unable to accomplish. After reading the notes to Panthea’s talk below, we’d all agree that big data also leaves out people who live”off the grid.”

As Panthea tells her story about Fatou (pseudonym), a person who has been trafficked, we learn that many of the services we use to make our lives easier, like Google Maps or Hop Stop, are also used by human traffickers to maintain dominance and power over people they are controlling. Panthea shares the early prototypes in Reboot’s design and how they decided to create a campaign that would take place at cash checking shops. 

Below, Panthea shares her notes to the talk that she gave at Microsoft’s annual Social Computing Symposium organized by Lily Cheng at NYU’s ITP. You can also view the video version of her talk

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We’ve made great strides in data-driven policymaking, open government, and civic technology –– many of the folks in this room have made significant contributions in these domains. But, as we know, many people, even here in New York City, still live “off the grid”––and the issues of access go beyond “digital divide”.

As a designer working on governance and development issues––fields where economists regularly eat anthropologists for lunch––this is something I think a lot about.

In the era of Big Data, as we become increasingly reliant on capital-d Data, I wonder what might exist in the negative space? Who are we not capturing in our datasets? And how might we reach them?

Slide02

A few months ago, I met a young woman from Benin who I will call Fatou (not her real name). Fatou had been adopted by an American preacher on mission in Benin, and brought to the United States. She and her family were overjoyed at her good fortune.

Fatou was pleased, she felt taken care of with her new “mother” and “father” in Queens. They started her on English lessons to help her adjust to the US and to allow her to enroll in school, a longtime dream.

But even from the outset, some things seemed strange to her.

Whenever they left the house, “to keep her safe”, her mother always held her by the wrist, keeping a firm grip. She wasn’t allowed any possessions beyond clothing. Her belongings were regularly searched for any material she kept, particularly information (pamphlets, papers). If found, they were confiscated. She worked long hours at a school the family owned. She was never herself enrolled in school, as promised, and when she inquired about her education, she was told to stop being ungrateful.

At first, Fatou thought these were just US customs. But then things got worse. Read More…

In between is the place where you have to understand people: Social science, stigma, and data big or small

Judd and Tamar

Editor’s Note: Judd Antin @juddantin is a social psychologist and user experience researcher who studies motivations for online participation. In 2011, he was named an MIT Technology Review Innovator Under 35. Prior to joining Facebook, he worked with Yahoo Research.  His educational background includes Applied Anthropology, Information Science, and training at the French Culinary Institute. One of my favorite papers of his is Readers are Not Free Riders: Reading as a form of participation on Wikpedia (pdf) [1].

Tamar Antin is a research scientist who uses mixed and especially qualitative methods to critically examine public health policies and narratives. She has several years of experience in public health research. One of her recent publications is Food Choice As a Multidimensional Experience [2].   Her dissertation [3] combining three papers on food choices and body image is excellent reading for any student of qualitative methods. 

I’ve known Tamar and Judd for several years now, and Tamar has been a mentor to me. Every time Tamar and I talk about research and ethnography, it never seems to last long enough; I just want to ask her more questions. And every time I see Judd, I want to ask him a million questions too. So a post for Ethnography Matters was a great excuse to get together with them for a chat on anthropology, Big Data and Small Data, and other interesting things.  –  Rachelle

P.S. This isn’t a straight transcript of our conversation but a sort of Frankenstein transcript made out of chopped up pieces sewn back together. 

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1. Two Ethnographers
2. What they’re working on
3. Stigma and hacking
4. Qualitative research as art, science and handmaiden
5. Big Data and Small Data

1. Two Ethnographers

What’s your background in anthropology?.

Judd: I have an undergraduate degree in anthro from Johns Hopkins, where I was one of seven anthropology majors I think, like in the whole university. It was a small department. I got interested in anthro primarily because of my adviser, who became our friend, Felicity Northcott. Coincidentally she also married Tamar and I. She was internet ordained and she officiated our wedding. She’s awesome.  She was just a very down to earth, foul-mouthed, passionate anthropologist.

Tamar: And for me, I have an undergraduate degree in anthropology also, from the University of Texas. I was having this conversation with the undergraduate adviser there at the end of my senior year, like okay now I have this degree, but I didn’t really know what to do with it. I went to the career center, and they had a list of all the jobs that you could do with certain majors, and I think the only job that was listed for anthropology majors was travel agent.

Judd: What?

Tamar: Oh yeah. I was thinking, well I don’t want to do that.

Judd: Travel agent?!

Read More…