Category Archives: academia

Big Data: Opportunities for Computational and Social Sciences

Scott Golder recently wrote blog post at Cloudera entitled “Scaling Social Science with Hadoop” where he accounts for “how social scientists are using large scale computation.” He begins with a delightful quote from George Homans: The methods of social science are dear in time and money and getting dearer every day. He then turns to talk about the trajectory of social science:

When Homans — one of my favorite 20th century social scientists — wrote the above, one of the reasons the data needed to do social science was expensive was because collecting it didn’t scale very well. If conducting an interview or lab experiment takes an hour, two interviews or experiments takes two hours. The amount of data you can collect this way grows linearly with the number of graduate students you can send into the field (or with the number of hours you can make them work!). But as our collective body of knowledge has accumulated, and the “low-hanging fruit” questions have been answered, the complexity of our questions is growing faster than our practical capacity to answer them. Things are about to change.

This is his bouncing off point for thinking about how “computational social science” provides new opportunities because of the “large archives of naturalistically-created behavioral data.” And then he makes a very compelling claim for why looking at behavioral data is critical:

Though social scientists care what people think it’s also important to observe what people do, especially if what they think they do turns out to be different from what they actually do.

By and large, I agree with him. Big Data presents new opportunities for understanding social practice. Of course the next statement must begin with a “but.” And that “but” is simple: Just because you see traces of data doesn’t mean you always know the intention or cultural logic behind them. And just because you have a big N doesn’t mean that it’s representative or generalizable. Scott knows this, but too many people obsessed with Big Data don’t.

Increasingly, computational scientists are having a field day with Big Data. This is exemplified by the “web science” community and highly visible in conferences like CHI and WWW and ICWSM and many other communities in which I am a peripheral member. In these communities, I’ve noticed something that I find increasingly worrisome… Many computational scientists believe that because they have large N data that they know more about people’s practices than any other social scientist. Time and time again, I see computational scientists mistake behavioral traces for cultural logic. And this both saddens me and worries me, especially when we think about the politics of scholarship and funding. I’m getting ahead of myself.

Let me start with a concrete example. Just as social network sites were beginning to gain visibility, I reviewed a computational science piece (that was never published) where the authors had crawled Friendster, calculated numbers of friends, and used this to explain how social network sites were increasing friendship size. My anger in reading this article resulted in a rant that turned into a First Monday article. As is now common knowledge, there’s a big difference between why people connect on social network sites and why they declare relationships when being interviewed by a sociologist. This is the difference between articulated networks and personal networks.

On one hand, we can laugh at this and say, oh folks didn’t know how these sites would play out, isn’t that funny. But this beast hasn’t yet died. These days, the obsession is with behavioral networks. Obviously, the people who spend the most time together are the REAL “strong” ties, right? Wrong. By such a measure, I’m far closer to nearly everyone that I work with than my brother or mother who mean the world to me. Even if we can calculate time spent interacting, there’s a difference in the quality of time spent with different people.

Big Data is going to be extremely important but we can never lose track of the context in which this data is produced and the cultural logic behind its production. We must continue to ask “why” questions that cannot be answered through traces alone, that cannot be elicited purely through experiments. And we cannot automatically assume that some theoretical body of work on one data set can easily transfer to another data set if the underlying conditions are different.

As we start to address Big Data, we must begin by laying the groundwork, understanding the theoretical foundations that make sense and knowing when they don’t apply. Cherry picking from different fields without understanding where those ideas are rooted will lead us astray.

Each methodology has its strength and weaknesses. Each approach to data has its strengths and weaknesses. Each theoretical apparatus has its place in scholarship. And one of the biggest challenges in doing “interdisciplinary” work is being about to account for these differences, to know what approach works best for what question, to know what theories speak to what data and can be used in which ways.

Unfortunately, our disciplinary nature makes a mess out of this. Scholars aren’t trained to read in other fields, let alone make sense of the conditions in which that work was produced. Thus, it’s all-too-common to pick and choose from different fields and take everything out of context. This is one of the things that scares me about students trained in interdisciplinary programs.

Now, of course, you might ask: But didn’t you come from an interdisciplinary program? Yes, I did. But there’s a reason that I was in grad school for 8.5 years. The first two were brutal as I received a rude awakening that I knew nothing about social science. And then I did a massive retraining as an ethnographer drawing on sociological and anthropological literatures. At this point, that’s my strength as a scholar. I know how to ask qualitative questions and I know how to employ ethnographic methods and theories to work out cultural practices. I had to specialize to have enough depth.

Of course, there’s one big advantage to an interdisciplinary program: it’s easy to gain an appreciation for diverse methodological and analytical approaches. In my path, I’ve learned to value experimental, computational, and quantitative research, but I’m by no means well trained in any of those approaches. That said, I am confident in my ability to assess which questions can be answered by which approaches. This also means that I can account for the questions I can’t answer.

Now back to Big Data… Big Data creates tremendous opportunities for those who know how to assess the context of the data and ask the right questions into it. But mucking with Big Data alone is not research. And seeing patterns in Big Data is not the same as hypothesis testing. Patterns invite more questions than they answer.

I agree with Scott that there’s the potential for social science to be transformed by Big Data. So many questions that we’ve wanted to ask but haven’t been able to. But I’m also worried that more computationally minded researchers will think that they’re answering social science questions simply by finding patterns in Big Data. It’s the same worry that I have when graph theorists think that they understand people because they can model a narrow kind of information flow given the perfect conditions.

If we’re going to actually attack Big Data, the best solution would be to combine forces between social scientists and computational scientists. In some places, this is happening. But there are also huge issues at play that need to be accounted for and addressed. First, every discipline has its arrogance and far too many scholars think that they know everything. We desperately need a little humility here. Second, we need to think about the differences in publication, collaboration, and validation across fields. Social scientists aren’t going to get tenure on ACM or IEEE publications. Hell, they’re often dismissed for anything that’s not single author. Computational scientists often see no point in the extended review cycles that go into journal publications to help produce solid articles. And don’t get me started on the messy reviewing process involved on both sides.

We need to find a way for people to start working together and continue to get validated in their work. I actually think that the funding agencies are going to play a huge role in this, not just in demanding cross-disciplinary collaboration, but in setting the stage for how research will be published. Given departmental obsessions with funding these days, they have a lot of sway over shaping the future here.

There’s also another path that needs to be used: cross-bred students. Scott Golder, our fearless critic, is a good example of this. He was trained in computational ways before going to Cornell to pursue a PhD in sociology. This is one way of doing it. Another is to start cross-breeding students early on. Computer scientists: teach courses for social scientists on how to think about Big Data from a computational perspective. Social scientists: allow computer scientists into your core courses or teach core courses for them to understand the fundamentals of social science methodology and social theory. And universities: provide incentives for your faculty to teach students outside of their departments and for departments to encourage their students to take classes in other departments.

It’s great that we have Big Data but we need to develop the intellectual apparatus to actually analyze it. Each of us has a piece to the puzzle, but stitching it together is going to take a lot of reworking of old habits. It can be done and it is important. The key is to let go of our grudges and territoriality without letting go of our analytic rigor and depth.

Choosing the Right Grad School

Lately, I’ve been getting all sorts of emails from folks applying to grad school who are seeking advice. I noticed that I was starting to say the same thing over and over again so I thought maybe it’d be better off to write some of it down in a more publicly consumable way. So here goes…

Choosing the Right Grad School

If there are faculty or students out there reading this, I’d love your comments and suggestions too. I know that we all have different advice we give to potential grad students so I know that this isn’t the end-all-be-all. Please feel free to comment, send links to your own advice columns, or just tell me that I’m wrong. There are loads of potential students out there lost and confused so hopefully this’ll help in some small way.

Also, make sure that you read PhD Comics for a good laugh and Eszter Hargittai’s Ph.Do column for some sound advice on being a PhD student.

(Note: I’ve created a separate page because I plan on updating this as my thoughts on the matter change.)

am I an academic?

academia (n.): The academic world or community; scholastic life.

academic (n.): 1) An ancient philosopher of the Academy.
2) A member of a college or university.
3) A member of a society for promoting art or science

At every academic conference I attend, I hear a constant refrain: “How does it feel to have left academia?” The tone changes dependent on who is doing the asking. Sometimes, it’s pure curiosity or puzzlement, fascination at my choice. At other times, there’s a hint of condescension, as though the question is actually: “Couldn’t make it in academia, eh? Stuck in industry, eh?” I try not to bristle at this but I do find myself getting defensive and trying to explain my position at Microsoft Research over and over again. So I couldn’t help but think that maybe it’s time to write it down.

Microsoft Research is an industrial research lab in the old skool sense. In the world of computer science, the industrial research lab is well understood; it has a long history of success in producing valuable, field-changing research. Like AT&T Bell Labs or Xerox PARC, the halls of MSR are filled with scientists of the highest caliber. People who invented things that you take for granted. MSR grew out of this tradition. It’s primarily filled with computer scientists (and engineers, physicists, mathematicians). Researchers are encouraged to pursue research questions that they feel are important and they are evaluated based on their publication record, contributions to the scholarly community, and innovative research that produces “tech transfer.”

Being a social scientist in one of these labs is peculiar, but not new. I have long admired the anthropological contributions Lucy Suchman made to research while at PARC. Being a social scientist at an industrial research lab can be a tricky balance. There are plenty of anthropologists and other social scientists who do applied work at Microsoft, focused on specific product needs. This is extremely important work, but it’s different than scholarly research. It’s also tricky to say what constitutes “tech transfer” as a social scientist. I don’t really produce IP in the traditional sense, but my work contributes to the company in other ways.

Yet, tech transfer is only a fraction of what I do. The vast majority of my time is spent doing the same type of research that I’ve been doing for years. I follow topics that interest me and dive head first in, regardless of whether or not it involves Microsoft’s current or future products. I publish articles without seeking approval from anyone. I blog about my research without vetting it through Microsoft. I attend academic conferences, review papers, and contribute to scholarly discourse. It looks a whole lot like academia to me. Yet, I hear all sorts of remarks that indicate that folks don’t believe that what I do is akin to academia. I feel the need to account for these and offer a different perspective.

But you’re working for a corporation! Since when are universities not corporations? Best that I can tell, most universities are fundamentally real estate barons who gain public credibility by offering higher education. The difference is that Microsoft’s products are very visible and related to the types of research that they seek to support. Both Microsoft and the university invest in research in the hopes that it will benefit the corporation as a whole, directly through the production (and protection) of IP or indirectly by creating an atmosphere where productive work can take place. The outcomes may look different, but both Microsoft and the university are large corporations with a fiscal mindset.

But a company makes you focus on the company’s bottom line! There is no doubt that Microsoft would love to have research that benefits it financially, but the dynamic is far more symbiotic than parasitic. We’re welcome to do the research we’re most passionate about, but we get financial bonuses for creating patents or for producing quality research that benefits the company. It’s an incentives system. On the contrary, I would argue that the university model is predominantly parasitic. Researchers at universities must run around begging external agencies for money so that they can do the research they love to do. When they finally succeed in getting a grant, how does the university respond? It takes 30-60% for “overhead.” And when they don’t get funding, they’re punished with lack of research resources and students. Furthermore, most university researchers don’t get to do as they please – they do what they (think they) can get funding for. I suspect I have far more freedom in terms of my research agenda than most university scholars.

Still, you have to spend time helping the company directly! Yes, I spend time working with product groups. But I like to think of it as my teaching duty. Rather than teaching Soc 101 to hung-over 18-year-olds who didn’t bother doing the reading, I teach an interactive form of Soc 101 to engineers who are filled with questions that start with “but why?” and “but how?” I have a hard time imagining that my engagement with product groups takes up more of my time than teaching, office hours, and prep. And it’s often quite fun and thought-provoking.

Well, there’s no tenure! What exactly is tenure? The promise that the university will promise you a salary in return for perpetual grant begging? Tenure guarantees a job, but it doesn’t guarantee an enjoyable one. There’s no promise of a pay raise or good classes to teach. Microsoft Research does have the right to fire me but, from what I can see, it’s more common for people to leave when they don’t gel well (just like in universities). The bigger threat is whether or not Microsoft will be around in N years (arguably, also true with many universities). I suspect that my job is just as solid as it would be in most university environments. The difference really comes down to bonuses. At the university, there are no performance-based bonuses. At Microsoft Research, a large chunk of my salary is linked to performance. Thus, I have an incentive to do well. There are also promotions that parallel university levels; Researcher = Assistant Professor, Senior Researcher = Associate Professor, Principle Researcher = Full Professor. This may not offer the on-paper guarantee of tenure, but it is pretty darn equivalent.

It’s not like you have students! Most professors love having students because of the collaboration potential. (Some enjoy the empire building but that’s not my bent.) Of course, this varies by field. Some scholars feel as though they need students to complete their work; in other fields, students are more an opportunity to mentor. My approach to students is more of collaboration and mentorship rather than slave labor. It’s true that I don’t have students, but I have the fortune of being able to take a handful of interns each year for 12 weeks each. These interns are primarily post-quals PhD students who have the skills and passion for collaboratively working on a constrained research project. No, it is not the same as 7-year students that you get to watch grow, but it’s not like I’m not engaged with younger scholars. My time with them is just more constrained and focused. There are also postdocs who come for 1-2 years. And when I’m craving collaboration, I can bring in visiting researchers to work with me. So it’s a bit more hodge-podge, but there’s still tremendous opportunities for engagement with scholars at all levels.

Whatever… it’s not real research. This is what it always comes down to… “Real” research comes from the university, suggesting that what comes out of industrial research labs is “fake.” I’m never quite sure how to best respond to this except to commit to proving folks wrong.

I feel very fortunate to have a position at Microsoft Research, even if lots of folks don’t seem to get why it’s a good deal. In many ways, this environment is far more academic than what I witnessed at MIT’s Media Lab or Berkeley’s iSchool. The biggest downside is that it’s not helping with my disciplinary identity crisis. If I had joined a specific disciplinary department, I might have had a clearer sense of the “top” journals, relevant conferences, and whether or not publishing a book is a must to succeed. Perhaps not, but I like to think so. Instead, I’m as confused as ever about where to publish and how to best disseminate my research in a manner that is generally useful. Thus, instead of becoming a proper -ist, I’m continuing to pave a strange path that may or may not bite me in the ass in the future. Of course, this identity crisis is pure academia. And one of the clearest reminders that I’m still an academic through-and-through.

I may not be a professor, but I’m still a scholar and, arguably, an academic. The title of “Researcher” may not seem very impressive or academic in social science realms, but practically speaking, it’s akin to “Assistant Professor” (and that’s even how people discuss it internally). What I do looks a lot like what any university researcher does, but with fewer restrictions. I don’t have to beg for grants. I don’t have to battle onerous IRBs (note: dealing directly with lawyers is MUCH easier than dealing with academics who are worrying about the legal repercussions of research). I can travel when I need to for research. I can do research that I think is important. I can collaborate with whomever I please. In return, I make certain that my research (and that of others) is translated into language that product people can understand. Personally, I think it’s a pretty amazing trade-off.

Does money equal time? (Regarding proposed NSF funding of qualitative research)

Following a conference about qualitative methods, the National Science Foundation issued a report that provided “general guidance for developing qualitative research projects” and “recommendations for designing, evaluating, and strengthening qualitative research” (along with a bunch of papers from the workshop). This report has made a bunch of social scientists giddy over the (very real) possibility that the NSF might start funding more qualitative social science research.

This week, the brilliant sociologist Howie Becker (best known outside of sociology for his article “Becoming a Marihuana User” and best known to panicked grad students for his book Writing for Social Scientists: How to Start and Finish Your Thesis, Book, or Article) penned a critique of the giddiness over the NSF report in an essay titled “How to Find Out How to Do Qualitative Research.” His sentiments are wonderfully summed up in his concluding paragraph:

On the other hand, it may well be–time will tell–that the methods recommended in the 2009 report will produce one result many people have long hoped for: an NSF grant for their research. Anyone wishing for such good fortune should remember one of the other criticisms many times repeated during the earlier meeting. NSF has an apparently inflexible rule that grants will not be given for faculty time released from teaching. But the chief expense of any qualitative research is always the researcher’s time. To do what Whyte and Goffman and Duneier and Hughes and Vaughan and the others cited above did doesn’t really cost much. The materials for recording, storing and analyzing interviews and field notes are cheap. Qualitative researchers need money to pay for their time, so that they can make observations and conduct interviews and get those data down in a permanent form. And NSF won’t pay for that.

Grants are a messy element of contemporary academic life. For some disciplines, grants are necessary to get funding for lab equipment and grad student labor (for the benefits of the “lab” – a.k.a. professor). Yet, increasingly, grants are needed to prove one’s worth in the academic hierarchy. Given the high levels of overheard at most institutions, universities put tremendous pressure on faculty to bring in the grants simply to pay for collective resources. Thus, faculty are often scrambling to get grants. Unfortunately, grants benefit some disciplines more than others. And it makes sense to get many multi-million dollar grants when you need to buy a crazy contraption to do your research, but does the same thing make sense in the social sciences?

Should scholars who don’t need much funding to produce quality research feel pressured to get grants even when they’re not necessary for the work? Sure, it’s uber nice when social sciences and humanities can pay for grad students (and none of us from those worlds would complain about this), but does pressure to get many grants actually create more research in these domains? Or does the lack of high value overhead from the social sciences make work in these areas look less worthy to money-strapped institutions because it doesn’t bring in the bacon? In other words, are we recognizing the perceived value of research findings or the costs of doing the research?

And how does this relate to faculty teaching load? In the sciences, it’s quite common for grad students to also do the bulk of that labor and for faculty to simply teach the main lecture class. Because of the dynamics of social sciences classes, I would bet that they are more of a load on faculty than in the sciences. So do grants without options for getting teaching relief actually add more of a burden on social science researchers?

More than anything, I’m curious if any of you have been privy to these discussions and have thoughts on the matter. I know that many of you come from different disciplinary trajectories so I’d be curious what your response is to this discussion of NSF funding of the social sciences.

(Tx Joe and Yuri)

discussion of “impact” at the CHI conference

Yesterday, I attended the CHI conference (an ACM conference for those studying and working in the area of human-computer interaction). I had the privilege of speaking on a panel discussing the paper entitled “Scientometric Analysis of the CHI Proceedings” by Christoph Bartneck and Jun Hu. The other panelists were Gilbert Cockton, Robert Kraut, and Louise Barkhuus. Because of the nature of this panel, I prepared seven minutes of commentary ahead of time. Although my notes from this are really rough, I decided that I should share them because others might find them to be helpful:

Remarks from Panel on “Scientometric Analysis of the CHI Proceedings” at CHI 2009

My main argument is that we should think about what kinds of impact we as academics intend to make with our work. Different scholars take different approaches, but we’re increasingly obsessed with how we can measure scholars’ “impact” and the focus on measurement distorts the actual impact being made. So, as we think about citation count, best paper awards, and the politics of our field, are we really talking about the way that we can have impact or the way that we can get tenure?

licensing your dissertation under Creative Commons

When I wrote my dissertation, it didn’t dawn on me that using the Creative Commons license might be remotely controversial. There’s a template for dissertations at Berkeley and one of those pages is the copyright page. Initially, I edited the copyright page to match the CC license that Cory Doctorow uses in all of his books on the copyright page. Shortly before I was set to file, I talked to another grad student in my department who had just filed his dissertation. Much to my horror, I learned that he was the first student to file his dissertation at Berkeley under the Creative Commons license and that it had been a disaster. He went through many iterations before they accepted it, complete with the CC license as an Appendix. Not wanting to pick a fight, I copied his approach verbatim. I went to file my dissertation and hit a stumbling block. They told me they had never seen such a thing. I told them that Joe Hall had filed that way only a few months back. They told me that it would need approval from high up and that I’d have to wait a long time to get that approval. Frantic, I started texting and emailing Joe. Luckily, he had all of the emails on hand and forwarded them to me. As it turns out, the person that I was trying to file with as the one who filed Joe’s and when I showed her emails that she sent negotiating this process with Joe, she let me file. I suggested she might want to take note since there would be plenty more students like me and Joe.

Today, the Daily Cal ran a story about our adventures in filing. I was pleased to learn that the Dean of the Grad Division committed to making CC licenses available to students in the future. This is truly good news!

But I also want to make a plea to all of you grad students out there who are slaving away on your dissertations… Use Creative Commons. The forms you fill out when you file your diss under ProQuest encourage you to make sure to copyright your dissertation. While theft is part of the framing, it is also framed as being about you profiting off of doing so (and ProQuest brokering the sale of your diss). Realistically, 99% of all grad students are never going to see a dime directly from their dissertation. What’s the advantage of keeping “all rights reserved”? Why not let folks use it for whatever non-commercial purposes they deem fit (like teaching a chapter or two in class)? I mean… I would LOVE it if someone translated my dissertation. Or remixed it. Or turned it into a movie. That ain’t ever gonna happen, but still… why actively prevent it?

And while we’re at it… why not make it freely available? Part way through my dissertation, I realized that I had never read a dissertation. I was surprised to find that very few people make their dissertations easily available. Why? In some senses, the diss is quite embarrassing. It’s imperfect. You’re sick of it. But there are huge advantages to making it available. At the very least, it allows future students to get a sense of what they should expect. (There was nothing more nerve-calming than realizing that my mentors’ dissertations were totally sloppy at points.)

Anyhow, if you’re a student out there, consider licensing your dissertation under Creative Commons and making your diss freely available either on your website or through services like SSRN or arXiv. I’m sure that there are many others out there doing similar things, but perhaps our story and template can help you persuade your school to allow CC-licensed dissertations.

My dissertation: Taken Out of Context

Joe’s dissertation: Policy Mechanisms for Increasing Transparency in Electronic Voting

seeking research intern

Connected to my role in the Internet Safety Technical Task Force, I’m seeking a research intern. The intern would be responsible for:

  1. Creating an annotated bibliography of all scholarly research related to the issues taken up by the Task Force (e.g., Internet sexual predators, bullying, identity theft, COPPA, etc.)
  2. Creating an annotated list of scholars and institutes working in the field and reaching out to them to see if new research is about to be published
  3. Writing the first draft of a literature review of the relevant research
  4. Other things that might come up…

The ideal intern will have strong research skills, strong writing skills, and an interest in the topic. Timeliness is also crucial – much is needed to be done by mid-June. The ability to self-motivate/self-direct is also critical; I will be doing virtually no micromanagement and the deadline is not movable.

The intern would officially be an intern at the Harvard Berkman Center and will receive the standard Harvard intern wage; living in Cambridge is not a requirement – most interactions with me will take place through email/AIM. The intern must be a student at a university (either undergrad or graduate level) and have full library access. Preference will be given to those in social science fields who are familiar with and can evaluate quantitative methods. The most ideal candidate would probably be a pre-quals graduate student who is working in this area and would love to be paid to do the literature review they have to do anyhow, but I’m not sure that this person exists.

This position will start the moment I find the right person. It will definitely last through June and can last much longer depending on the person’s interest (there’s plenty of related work through December). Hours are flexible; all that matters is getting the job done.

To apply, send me an email to zephoria at zephoria dot org. Include your CV, the names and emails of 2 professors who can attest to your research skills, a sample piece of writing (class assignments are fine) and a cover letter that includes: why you are interested in this internship, some background on your research skills, and whatever else you think that I might want to know.

Feel free to forward this announcement to anyone you think might be interested.

Update: This position has been filled. To my shock and excitement, there was an absolute plethora of amazing candidates that I had to turn down. Of course, that makes it really hard. But thank you to everyone who applied!

If you are a scholar who is publishing in this area who is jumping up and down with excitement, feel free to add citations and names to the comments. I will do a proper call for biblio bits and researchers a bit down the road.

why I am not going on the academic job market

I have decided not to go on the academic job market this year. I’ve wanted to be a professor for a long time. I still want to be a professor. Just not now.

Making that decision was quite hard for me. If all goes well, I will have my PhD next summer. Thus, it is this fall when I should go on the academic job market. To be proper, I signed up to go to every academic conference in my field this fall. (For those not in academia, academic job opportunities are posted in the fall, with applications due throughout the fall, and interviews taking place in the winter/spring. Finishing graduate students normally go on the market during their final year. Academic conferences are key places for being seen and feeling out different departments and practicing job talks.)

Before he passed away, my advisor and I had many long conversations about whether or not I belonged in academia. He told me that I had too much energy to do research and that I would find academia maddening at this stage in my career. The more I thought about it, the more I agreed with his logic. My reasons for wanting to go on the job market were simple: I *love* teaching, I *love* students, I *love* research. Peter kindly reminded me that this is not what academia is about – he used to joke that the University paid him to attend meetings so that he could keep up his hobby of teaching. Peter was infinitely patient about most things, but boy did he hate bureaucracy.

I feel the need to explain why I’m not going on the job market in a public way, mainly because everyone keeps asking and I expect that it’ll be ten times worse at 4S, AOIR, ASIS&T, and the smaller academic things I’m doing this fall. By no means am I rejecting academic research. Last time I quit academia, I published more academic papers and attended more academic conferences as a non-academic than ever before. I love scholarship and I love the research that academics do and I love academics, especially when they wear tweed coats. I have every intention of doing research when I finish my PhD. I just don’t think that I can stomach doing it as a 1st year assistant professor right now.

There are multiple reasons for which I think that going on the academic job market doesn’t make sense for me right now. The major ones are:

1. IRB/human subjects. I am a huge supporter of ethics in research, but my experiences with IRBs (at multiple universities) have been nothing short of miserable. I feel extremely claustrophobic right now because of it. I will save the details of my anti-IRB rant for another time, but the short synopsis is that I think that IRBs are destroying social scientists’ ability to do good qualitative research and ethnographic research in particular. In theory IRBs are about ethics; in reality, they are about protecting universities from being sued. Qualitative (and especially ethnographic) research is seen as risky because it’s not controlled and structured and formulaic. I do not believe you can do true ethnography under an IRB and it depresses me to think about all of the data that I’ve collected that I cannot use in my dissertation because it didn’t fit into an IRB-approved protocol. I’m told that not all IRBs are as bad as the ones that I’ve faced, but “not as bad” is not good enough right now. I want to do research that is guided by ethics, not institutions.

2. The tenure process. I have been watching friends go through the tenure process and it makes me sick. There’s no room for innovation, for playing outside of the rules. You have 7 years to publish X articles in the *right* journals in the *right* way. My favorite phrase associated with this is “Least Publishable Unit.” In other words, what’s the minimum contribution you can make to get a good publication out of it. I don’t write like that and I don’t want to. I also think that most of the “respected” journals are so locked down as to be inaccessible to broader audiences. I want to be an academic, not a hermit. I believe that academia is an institution built on knowledge creation AND dissemination. My goal is to write for public audiences, to make knowledge palatable and interesting and accessible. I want to contribute big ideas that will make a difference, and to leave the mini-contributions for my blog.

3. Overhead. I had this intense conversation with a young professor about the hells of starting up a new lab, applying for grants, starting new syllabuses, advising students, attending meetings, being stuck on the shitty committees, constantly reviewing, etc. He lamented that there was no time for research. I’ve heard this over and over and over again. Becoming a professor at a top tier university seems to mean death to research. Being a professor at less prestigious institutions seems to mean unengaged or unmotivated students. I’m not ready for either. I do a lot of “community service” right now (Nicole and my JCMC special issue will be done next month!), but I need to do research. I have too much energy to do research right now. And I need to work with brilliant students who are just as enthusiastic as I am.

4. Geography. One of the hardest lessons that I learned was that geography *really* matters to my sanity. I need to live in a city, where I can go dancing at 2AM just to work out some raw energy or grab sushi at midnight. I like to joke that I need the people around me to be more crazy, most intense than me, just so that I feel calm. Living near a major international airport increases my sanity tremendously. And having a beach nearby is extremely important for helping me feel grounded. I need sun because being seasonally affective isn’t so good for being productive. I also want to be surrounded by Big Industry both for consulting reasons and to remind myself of what the corporate world looks like. Right now, I can’t imagine living anywhere in the U.S. outside of NY or LA. That’s not very useful for going on the academic job market. And besides, there’s a part of me that wants to live abroad for a while anyhow.

5. Lack of flexibility. I want to do research – fieldwork – outside of the U.S. This means traveling and having the flexibility to travel. I want to consult and speak whenever it’ll be interesting and helpful to do so. I want to run to DC whenever a bill gets proposed that is nightmarish. I don’t see how this is manageable as a first-year prof. To complicate matters, academia is all about long-term. That’s why tenure is seen as such a reward. I’m not sure that I’m ready to be in a single place for the rest of my life, or even for 5 years in a row. I want the flexibility to jump around and that’s just not fair to academic colleagues.

These are the major issues. The worst is really the IRB. I can’t tell if the pain in my stomach when I think about IRBs is nausea or a murderous desire. Either way, it ain’t pleasant. But any which way you read it, I can’t imagine a full-time academic position that would make sense for me now. And I don’t think that I’d be good for an academic institution right now either. I think I’d make a great advisor, teacher, and researcher. But I don’t think that I’d make a good colleague right now. I need to work out some raw energy first. I still hope to go back to academia, but I need to wait. I can imagine a future where I’ll find the tenure game entertaining, know tricks to manage the overhead, and need less flexibility. And maybe IRBs will one day wake up and get it. OK, maybe not. But still, I can imagine a way in which I’d be a good colleague, but right now, I fear that wouldn’t be the case and I’ve already burnt enough bridges by being a punk-ass public grad student.

Don’t get me wrong – I’m not saying that it’s academia OR industry. I think that industry research is equally FUBAR, but for different reasons and I can’t imagine having my research locked down inside of one company. I just think that there has to be another way. I’m toiling with ideas of consulting, independent research, ::shrug:: I don’t know. What I do know is that I’ve decided to let the wind take me where it will. I will focus on my dissertation this year and then I will see where I end up. My only plan post-graduation is a desperately-needed vacation. And then I will look for what’s next. I will not even entertain the possibility of jobs until after a vacation. That’s kinda terrifying (especially since I need to figure out health insurance), but I’m looking forward to it. Freedom…

Berkman Fellowship

I am excited to announce that I will be a Fellow at the Berkman Center for Internet & Society at Harvard Law School during the 2007-2008 school year. I will not be in-residence although I will visit Cambridge regularly. I am truly inspired by the Berkman community and honored by the fellowship. My hope is that, alongside other Fellows at Berkman, I can take some of what I’ve been doing concerning youth culture and figure out how to affect policy and social change.

Also, for those who aren’t aware, I’m no longer a USC Annenberg Center Fellow because there is no longer a USC Annenberg Center. To the best that I can suss out, this has to do with academic politics and poor decision making on the part of the USC leadership. Regardless of why, the closure of the USC Annenberg Center has devastated (or embittered) many who were hoping that interdisciplinarity would flourish at USC. I count myself amongst that group. When it comes to mourning the loss of the Annenberg Center, I’m trying to move beyond the anger phase, so I’ll stop now.

the edublog awards

Henry Jenkins and i are honored to have been nominated for the EduBlog awards under the category “Most Influential Post, Resource or Presentation” for our Discussion: MySpace and Deleting Online Predators Act (DOPA). If you would like to support us, feel free to vote for us by midnight GMT tonite (December 16) from the EduBlog finalists list. Regardless, i encourage you to check out all of the great finalists in all of the categories over at the EduBlog awards. This is a community of bloggers that is often unknown in other crowds which is unfortunate.