The Cost of Inaccessibility at the Margins of Relevance

I use RSS feeds to keep up with academic journals. Because of an undocumented and unexpected feature (bug?) in my (otherwise wonderful) free software newsreader NewsBlur, many articles published over the last year were marked as having been read before I saw them.

Over the last week, I caught up. I spent hours going through abstracts and downloading papers that looked interesting or relevant to my research. Because I did this for hundreds of articles, it gave me an unusual opportunity to reflect on my journal reading practices in a systematic way.

On a number of occasions, there were potentially interesting articles in non-open access journals that neither MIT nor Harvard subscribes to and that were otherwise not accessible to me. In several cases where the research was obviously important to my work, I made an interlibrary request, emailed the papers’ authors for copies, or tracked down a colleague at an institution with access.

Of course, articles that look potentially interesting from the title and abstract often end up being less relevant or well executed on closer inspection. I tend to cast a wide net, skim many articles, and put them aside when it’s clear that the study is not for me. This week, I downloaded many of these possibly relevant papers to, at least, give a skim. But only if I could download them easily. On three or four occasions, I found inaccessible articles at this margin of relevance. In these cases, I did not bother trying to track down the articles.

Of course, what appear to be marginally relevant articles sometimes end up being a great match for my research and I will end up citing and building on the work. I found several suprisingly interesting papers last week. The articles that were locked up have no chance at this.

When people suggest that open access hinders the spread of scholarship, a common retort is that the people who need the work have or can finagle access. For the papers we know we need, this might be true. As someone with access to two of the most well endowed libraries in academia who routinely requests otherwise inaccessible articles through several channels, I would have told you, a week ago, that locked-down journals were unlikely to keep me from citing anybody.

So it was interesting watching myself do a personal cost calculation in a way that sidelined published scholarship — and that open access publishing would have prevented. At the margin of relevance to ones research, open access may make a big difference.

The Remixing Dilemma: The Trade-off Between Generativity and Originality

This post was written with Andrés Monroy-Hernández. It is a summary of a paper just published in American Behavioral Scientist. You can also read the full paper: The remixing dilemma: The trade-off between generativity and originality. It is part of a series of papers I have written with Monroy-Hernández using data from Scratch. You can find the others on my academic website.

Remixing — the reworking and recombination of existing creative artifacts — represents a widespread, important, and controversial form of social creativity online. Proponents of remix culture often speak of remixing in terms of rich ecosystems where creative works are novel and highly generative. However, examples like this can be difficult to find. Although there is a steady stream of media being shared freely on the web, only a tiny fraction of these projects are remixed even once. On top of this, many remixes are not very different from the works they are built upon. Why is some content more attractive to remixers? Why are some projects remixed in deeper and more transformative ways?
Remix Diagram
We try to shed light on both of these questions using data from Scratch — a large online remixing community. Although we find support for several popular theories, we also present evidence in support of a persistent trade-off that has broad practical and theoretical implications. In what we call the remixing dilemma, we suggest that characteristics of projects that are associated with higher rates of remixing are also associated with simpler and less transformative types of derivatives.

Our study is focused on two interrelated research questions. First, we ask why some projects shared in remixing communities are more or less generative than others. “Generativity” — a term we borrow from Jonathan Zittrain — describes creative works that are likely to inspire follow-on work. Several scholars have offered suggestions for why some creative works might be more generative than others. We focus on three central theories:

  1. Projects that are moderately complicated are more generative. The free and open source software motto “release early and release often” suggests that simple projects will offer more obvious opportunities for contribution than more polished projects. That said, projects that are extremely simple (e.g., completely blank slates) may also uninspiring to would-be contributors.
  2. Projects by prominent creators are more generative. The reasoning for this claim comes from the suggestion that remixing can act as a form of cultural conversation and that the work of popular creators can act like a common medium or language.
  3. Projects that are remixes themselves are more generative. The reasoning for this final claim comes from the idea that remixing thrives through the accumulation of contributions from groups of people building on each other’s work.

Our second question focuses on the originality of remixes and asks when more or less transformative remixing occurs. For example, highly generative projects may be less exciting if the projects produced based on them are all near-identical copies of antecedent projects. For a series of reasons — including the fact that increased generativity might come by attracting less interested, skilled, or motivated individuals — we suggest that each of the factors associated with generativity will also be associated with less original forms of remixing. We call this trade-off the remixing dilemma.

We answer both of our research questions using a detailed dataset from Scratch, where young people build, share, and collaborate on interactive animations and video games. The community was built to support users of the Scratch programming environment, a desktop application with functionality similar to Flash created by the Lifelong Kindergarten Group at the MIT Media Lab. Scratch is designed to allow users to build projects by integrating images, music, sound, and other media with programming code. Scratch is used by more than a million users, most of them under 18 years old.

To test our three theories about generativity, we measure whether or not, as well as how many times, Scratch projects were remixed in a dataset that includes every shared project. Although Scratch is designed as a remixing community, only around one tenth of all Scratch projects are ever remixed. Because more popular projects are remixed more frequently simply because of exposure, we control for the number of times each project is viewed.

Our analysis shows at least some support for all three theories of generativity described above. (1) Projects with moderate amounts of code are remixed more often than either very simple or very complex projects. (2) Projects by more prominent creators are more generative. (3) Remixes are more likely to attract remixers than de novo projects.

To test our theory that there is a trade-off between generativity and originality, we build a dataset that includes every Scratch remix and its antecedent. For each pair, we construct a measure of originality by comparing the remix to its antecedent and computing an “edit distance” (a concept we borrow from software engineering) to determine how much the projects differ.

We find strong evidence of a trade-off: (1) Projects of moderate complexity are remixed more lightly than more complicated projects. (2) Projects by more prominent creators tend to be remixed in less transformative ways. (3) Cumulative remixing tends to be associated with shallower and less transformative derivatives. That said, our support for (1) is qualified in that we do not find evidence of the increased originality for the simplest projects as our theory predicted.

Two plots of estimated values for prototypical projects. Panel 1 (left) display predicted probabilities of being remixed. Panel 2 (right) display predicted edit distances. Both panels show predicted values for both remixes and de novo projects from 0 to 1,204 blocks (99th percentile).
Two plots of estimated values for prototypical projects. Panel 1 (left) displays predicted probabilities of being remixed. Panel 2 (right) displays predicted edit distances. Both panels show predicted values for both remixes and de novo projects from 0 to 1,204 blocks (99th percentile).

We feel that our results raise difficult but important challenges, especially for the designers of social media systems. For example, many social media sites track and display user prominence with leaderboards or lists of aggregate views. This technique may lead to increased generativity by emphasizing and highlighting creator prominence. That said, it may also lead to a decrease in originality of the remixes elicited. Our results regarding the relationship of complexity to generativity and originality of remixes suggest that supporting increased complexity, at least for most projects, may have fewer drawbacks.

As supporters and advocates of remixing, we feel that although highly generative works that lead to highly original derivatives may be rare and difficult for system designers to support, understanding remixing dynamics and encouraging these rare projects remain a worthwhile and important goal.

Benjamin Mako Hill, Massachusetts Institute of Technology
Andrés Monroy-Hernández, Microsoft Research

For more, see our full paper, “The remixing dilemma: The trade-off between generativity and originality.” Published in American Behavioral Scientist. 57-5, Pp. 643—663. (Official Link, Pay-Walled ).

MIT LaTeX Stationery

Color MIT LetterHead Example

The MIT graphic identity website provides downloadable stationery templates for letterhead and envelopes. They provide both Microsoft Word and LaTeX templates. But although they provide both black and white and color templates for Word, they only provide the monochrome templates for LaTeX. When writing cover letters for the job market this year, I was not particularly interested in compromising on color and was completely unwilling to compromise on TeX.

As a result, I ended up modifying each of the three templates to include color. In the process, I fixed a few bugs and documented one tricky issue. I’ve published a git repository with my changes. It includes branches for each version of three of the “old” black and white templates as well as my my three new color templates. I hope others at MIT find it useful. I’ve tried to keep the changes minimal.

I’ve emailed the folks at MIT Communication Production Services to see if they want to publish my modified versions. Until then, anyone interested can help themselves to the git repository. LaTeX user that you are, you probably prefer that anyway.

Conversation on Freedom and Openness in Learning

On Monday, I was a visitor and guest speaker in a session on “Open Learning” in a class on Learning Creative Learning which aims to offer “a course for designers, technologists, and educators.” The class is being offered publicly by the combination — surprising but very close to my heart — of Peer 2 Peer University and the MIT Media Lab.

The hour-long session was facilitated by Philipp Schmidt and was mostly structured around a conversation with Audrey Watters and myself. The rest of the course materials and other video lectures are on the course website.

You can watch the video on YouTube or below. I thought it was a thought-provoking conversation!

If you’re interested in alternative approaches to learning and free software philosophy, I would also urge you to check out an essay I wrote in 2002: The Geek Shall Inherit the Earth: My Story of Unlearning. Keep in mind that the essay is probably the most personal thing I have ever published and I wrote it more than a decade ago it as a twenty-one year old undergraduate at Hampshire College. Although I’ve grown and learned enormously in the last ten years, and although I would not write the same document today, I am still proud of it.

The Cost of Collaboration for Code and Art

This post was written with Andrés Monroy-Hernández for the Follow the Crowd Research Blog. The post is a summary of a paper forthcoming in Computer-Supported Cooperative Work 2013. You read also read the full paper: The Cost of Collaboration for Code and Art: Evidence from Remixing. It is part of a series of papers I have written with Monroy-Hernández using data from Scratch. You can find the others on my academic website.

Does collaboration result in higher quality creative works than individuals working alone? Is working in groups better for functional works like code than for creative works like art? Although these questions lie at the heart of conversations about collaborative production on the Internet and peer production, it can be hard to find research settings where you can compare across both individual and group work and across both code and art. We set out to tackle these questions in the context of a very large remixing community.

Example of a remix in the Scratch online community, and the project it is based off. The orange arrows indicate pieces which were present in the original and reused in the remix.

Remixing platforms provide an ideal setting to answer these questions. Most support the sharing, and collaborative rating, of both individually and collaboratively authored creative works. They also frequently combine code with artistic media like sound and graphics.

We know that that increased collaboration often leads to higher quality products. For example, studies of Wikipedia have suggested that vandalism is detected and removed within minutes, and that high quality articles in Wikipedia, by several measures, tend to be produced by more collaboration. That said, we also know that collaborative work is not always better — for example, that brainstorming results in less good ideas when done in groups. We attempt to answer this broad question, asked many times before, in the context of remixing: Which is the better description, “the wisdom of crowds” or “too many cooks spoil the broth”? That, fundamentally, forms our paper’s first research question: Are remixes, on average, higher quality than single-authored works?

A number of critics of peer production, and some fans, have suggested that mass collaboration on the Internet might work much better for certain kinds of works. The argument is that free software and Wikipedia can be built by a crowd because they are functional. But more creative works — like music, a novel, or a drawing — might benefit less, or even be hurt by, participation by a crowd. Our second research question tries to get at this possibility: Are code-intensive remixes, higher quality than media-intensive remixes?

We try to answers to these questions using a detailed dataset from Scratch – a large online remixing community where young people build, share, and collaborate on interactive animations and video games. The community was built to support users of the Scratch programming environment: a desktop application with functionality similar to Flash created by the Lifelong Kindergarten Group at the MIT Media Lab. Scratch is designed to allow users to build projects by integrating images, music, sound and other media with programming code. Scratch is used by more than a million, mostly young, users.

Measuring quality is tricky and we acknowledge that there are many ways to do it. In the paper, we rely most heavily a measure of peer ratings in Scratch called loveits — very similar to “likes” on Facebook. We find similar results with several other metrics and we control for the number of views a project receives.

In answering our first research question, we find that remixes are, on average, rated as being of lower quality than works of single authorship. This finding was surprising to us but holds up across a number of alternative tests and robustness checks.

In answering our second question, we find rough support for the common wisdom that remixing tends to be more effective for functional works than for artistic media. The more code-intensive a project is, on average, the closer the gap is between a remix and a work of single authorship. But the more media-intensive a project is, the bigger the gap. You can see the relationships that our model predicts in the graph below.

Two plots of estimated values for prototypical projects showing the predicted number of loveits using our estimates. In the left panel, the x-axis varies number of blocks while holding media intensity at the sample median. The right panel varies the number of media elements while holding the number of blocks at the sample median. Ranges for each are from 0 to the 90th percentile.

Both of us are supporters and advocates of remixing. As a result, we were initially a little troubled by our result in this paper. We think the finding suggests an important limit to the broadest claims of the benefit of collaboration in remixing and peer production.

That said, we also reject the blind repetition of the mantra that collaboration is always better — for every definition of “better,” and for every type of work. We think it’s crucial to learn and understand the limitations and challenges associated with remixing and we’re optimistic that this work can influence the design of social media and collaboration systems to help remixing and peer production thrive.

For more, see our full paper, The Cost of Collaboration for Code and Art: Evidence from Remixing.

Heading West

University of Washington Quad in Cherry Blossom Season

This week, I accepted a job on the faculty of at the University of Washington Department of Communication. I’ve arranged for a post-doc during the 2013-2014 academic year which I will spend at UW as an Acting Assistant Professor. I’ll start the tenure-track Assistant Professor position in September 2014. The hire is part of a "big data" push across UW. I will be setting up a lab and research projects, as well as easing into a teaching program, over the next couple years.

I’m not going to try to list all the great people in the department, but UW Communication has an incredible faculty with a strong background in studying the effect of communication technology on society, looking at political communication, enagement, and collective action, and tracing out the implications of new communication technologies — in addition to very strong work in other areas. Years ago, I nearly joined the department as a graduate student. I am unbelievably happy that their faculty has invited me to join as a colleague.

Outside of my new department, the University of Washington has a superb group of folks working across the school on issues of quantitative and computational social science, human-computer interaction, and computer-supported cooperative work. They are hiring a whole bunch of folks, across the university, who specialize in data-driven social science. I already have a bunch of relationships with UW faculty and students and am looking forward to expanding and deepening those.

On a personal level, Mika and I are also very excited to return to Seattle. I grew up in the city and I’ve missed it, deeply, since I left — now nearly half my lifetime ago! It will be wonderful to be much closer to many of my family members.

But I know that I will miss the community of friends and colleagues that I’ve built in Boston over the last 7+ years just as deeply. I’m going to miss the intellectual resources, and the intellectual community, that folks in Cambridge get to take for granted. That said, I plan to maintain affiliations and collaborations with folks at Harvard and MIT and will have resources that let me spend time in Boston doing that.

If you are curious what I’m going to be up to — and what the future is likely to hold in terms of my research — you should check the material I’ve put online as part of the job market this year. I’ve posted just about everything on my academic website. This includes a little four page research statement which describes the work I’ve done and the directions I’ve been thinking about taking it.

The academic job market is challenging and confusing. But it’s given me a lot of opportunity to reflect, at length, on both the substance of my research and the academy and its structures and processes. I’ve got a list of blog topics queued up based on that thinking. I’ll be posting them here on my blog over the next few months.

A Model of Free Software Success

Last week I helped organize the Open and User Innovation Conference at Harvard Business School. One of many interesting papers presented there was an essay on Institutional Change and Information Production by Fabio Landini from the University of Siena.

At the core of the paper is an economic model of the relationship between rights protection and technologies that affects the way that cognitive labor can be divided and aggregated. Although that may sound very abstract (and it is in the paper), it is basically a theory that tries to explain the growth of free software.

The old story about free software and free culture (at least among economists and many other academics) is that the movements surged to prominence over the last decade because improvements in communication technology made new forms of mass-collaboration — like GNU/Linux and Wikipedia — possible. "Possible", for these types of models, usually means profit-maximizing for rational, profit-seeking, actors like capitalist firms. You can basically think of these attempts as trying to explain why open source claims that free licensing leads to "better quality, higher reliability, more flexibility, lower cost" are correct: new technology makes possible an open development process which leads to collaboration which leads to higher quality work which leads to profit.

Landini suggests there are problems with this story. One problem is that it treats technology as being taken for granted and technological changes as effectively being dropped in from outside (i.e., exogenous). Landini points out that software businesses build an enormous amount of technology to help organize their work and to help themselves succeed in what they see as their ideal property rights regime. The key feature of Landini’s alternate model is that it considers this possibility. What comes out the other end of the model is a prediction for a multiple equilibrium system — a situation where there are several strategies that can be stable and profitable. This can help explain why, although free software has succeeded in some areas, its success has hardly been total and usually has not led to change within existing proprietary software firms. After all, there are still plenty of companies selling proprietary software. In Landini’s model, free is just one of several winning options.

But Landini’s model raises what might be an even bigger question. If free software can be as efficient as proprietary software, how would anybody ever find out? If all the successful software companies out there are doing proprietary software, which greedy capitalist is going to take the risk of seeing if they could also be successful by throwing exclusive rights out the window? In the early days, new paths are always unclear, unsure, and unproven.

Landini suggests that ethically motivated free software hackers provide what he calls a "cultural subsidy." Essentially, a few hackers are motivated enough by the ethical principles behind free software that they are willing to contribute to it even when it isn’t clearly better than proprietary alternatives. And in fact, historically speaking, many free software hackers were willing to contribute to free software even when they thought it was likely less profitable than the proprietary alternative models. As Landini suggests, this group was able to build technological platforms and find new social and business arrangements where the free model actually is competitive.

I think that the idea of an "cultural subsidy" is a nice way to think about the important role that ethical arguments play in movements like free software and free culture. "Open source" style efficiency arguments persuade a lot of people. Especially when they are true. But those arguments are only ever true because a group of ethically motivated people fought to find a way to make them true. Free software didn’t start out as competitive with proprietary software. It became so only because a bunch of ethically motivated hackers were willing to "subsidize" the movement with their failed, and successful, attempts at free software and free culture projects and businesses.

Of course, the folks attracted by "open source" style superiority arguments can find the ethical motivated folks shrill, off-putting, and annoying. The ethically motivated folks often think the "efficiency" group is shortsighted and mercenary. But as awkward as this marriage might be, it has some huge upsides. In Landini’s model, the ethical folks can build their better world without convincing everyone else that they are right and by relying, at least in part, on the self-interest of others who don’t share their principles. Just as the free software movement has done.

I think that Landini’s paper is a good description of the critically important role that the free software movement, and the FSF in particular, can play. The influence and importance of individuals motivated by principles can go far beyond the groups of people who take an ethical stand. They can make involvement possible for large groups of people who do not think that taking a stand on a particular ethical issue is even a good idea.

User Innovation on NPR Radio

I was invited onto NPR in Boston this week for a segment on user innovation alongside Eric von Hippel (my advisor at MIT) and Carliss Baldwin from Harvard Business School.

I talked about innovation that has happened on the CHDK platform — a cool firmware hack for Canon cameras example I use in some of my teaching — plus a little bit about free software, the democratization of development and design tools, and a little bit about user communities that LEGO has cultivated.

I would have liked the conversation and terminology to do more to emphasize user freedom and free software, but I’m otherwise pretty happy with the result. The segment will be aired again on NPR in Boston this weekend and is available on the WGBH website.

Wiki Conferencing

I am in Berlin for the Wikipedia Academy, a very cool hybrid free culture community plus refereed academic conference organized, in part, by Wikimedia Deutschland. On Friday, I was very excited to have been invited to give the conference’s opening keynote based on my own hybrid take on learning from failures in peer production and incorporating a bunch of my own research. Today, I was on a panel at the conference about free culture and sharing practices. I’ll post talks materials and videos when the conference puts them online.

I will be in Berlin for the next week or so before I head to directly to Washington, DC for Wikimania between the 11th and 15th. I’ll be giving three talks there:

Between then and now, I’m taking the next week in Berlin to catch up on work, and with friends. If you’re in either place and want to meet up, please get in touch and lets try to arrange something.

Advice for Prospective Doctoral Students

There is tons of advice on the Internet (e.g., on the academic blogs I read) for prospective doctoral students. I am very happy with my own graduate school choices but I feel that I basically got lucky. Few people are saying the two things I really wish someone had told me before I made the decision to get a PhD:

  • Most people getting doctorates would probably be better off doing something else.
  • Evaluating potential programs can basically be done by looking at and talking with a program’s recent graduates.

Most People Getting Doctorates Probably Shouldn’t

In most fields, the only thing you need a PhD for is to become a professor — and even this requirement can be flexible. You can have almost any job in any company or non-profit without a PhD. You can teach without a PhD. You can write books without a PhD. You can do research and work in thinktanks without a PhD. You don’t even always need a PhD to grant PhDs to other people: two of my advisors at the Media Lab supervised PhD work but did not have doctorates themselves! Becoming a tenured professor is more difficult without a doctorate, but it is not impossible. There are grants and jobs outside of universities that require doctorates, but not nearly as many as most people applying for PhDs programs think.

Getting a doctorate can even hurt: If you want to work in a company or non-profit, you are usually better off with 4-6 years of experience doing the kind of work you want to do than with the doctorate and the less relevant experience of getting one. Starting salaries for people with doctorates are often higher than for people with masters degrees. But salaries for people with masters degrees and 5 years of experience are even higher — and that’s before you take into account the opportunity costs of working for relatively low graduate student wages for half a decade.

PhD take an enormous amount of time and, in most programs, you spend a huge amount of this time doing academic busy work, teaching, applying for grants or fellowships, and writing academic papers that very few people read. These are skills you’ll need to be a successful professor. They are useful skills for other jobs too, but not as useful as the experience of actually doing those other jobs for the time it takes to get the degree.

Evaluating Graduate Programs

If you are still convinced you need a doctorate, or any graduate degree for that matter, you will need to pick a program. Plenty of people will offer advice on how to pick the right program and trying to balance all the complicated and contradictory advice can be difficult. Although I love my program and advisors, I’ve known many less happy students. Toward that end, there are two pieces of meta-advice that I wish everybody was told before they applied:

  1. Find recent graduates of the program you are considering, and the faculty advisor(s) you are planning on working with, and look at where they are now. Are these ex-students doing the kind of work that you want to do? Are they at great programs at great universities?

    Chances are good that a PhD program and its faculty will prepare future students to be like, and do work like, the students they have trained in the past. Programs that consistently make good placements are preparing their students well, supporting them, making sure they have the resources necessary to do good work, and helping their students when they are on the job market. A program whose students do poorly, or just end doing work that isn’t like the kind you want to do, will probably fail you too.

  2. If recent graduates seem to be generally successful and doing the kind of work you want to do, find one who looks most like the kind of academic you want to become and talk to them about their experience. Chances are, your faculty advisors will overlap with theirs and your experience will be similar. Ex-students can tell you the strengths of weaknesses of the program you are considering and what to watch out for. If they had a horrible experience, there’s a decent chance you will too, and they will tell you so.

Doing these two things means you don’t have to worry about trying to think of all the axes on which you want to evaluate a program or pour through admissions material which is only tangentially connected to the reality you’ll live for a long time. What matters most is the outcomes, of course, because you’re be living the rest of your life for a lot longer than you’ll be in the PhD program.

Science as Dance

The following selected bibliography showcases only a small portion of the academics who have demonstrated that while it may take two to tango, it only takes one to give a scholarly paper a silly cliche title:

Briganti, G. 2006. “It Takes Two to Tango-The CH-53K is arguably the first serious US attempt to open the defense cooperation NATO has been seeking.Rotor and Wing 40(7):60–63.

Coehran, J. 2006. “It Takes Two to Tango: Problems with Community Property Ownership of Copyrights and Patents in Texas.Baylor L. Rev. 58:407.

Diamond, M.J. 1984. “It takes two to tango: Some thoughts on the neglected importance of the hypnotist in an interactive hypnotherapeutic relationship.American Journal of Clinical Hypnosis 27(1):3–13.

Kraack, A. 1999. “It takes two to tango: The place of women in the construction of hegemonic masculinity in a student pub.Masculinities in Aotearoa/New Zealand 153–165.

Lackey, J. 2006. “It takes two to tango: beyond reductionism and non-reductionism in the epistemology of testimony.The Epistemology of testimony 160–89.

Miller, C.A. 1998. “It takes two to tango: understanding and acquiring symmetrical verbs.Journal of psycholinguistic research 27(3):385–411.

Modiano, N. 1984. “It Takes Two to Tango, or… Transmission is a Two-Way Street.Anthropology & Education Quarterly 15(4):326–330.

Ott, M.A. 2008. “It Takes Two to Tango: Ethical Issues Raised by the Study of Topical Microbicides with Adolescent Dyads.The Journal of adolescent health: official publication of the Society for Adolescent Medicine 42(6):541.

Rubenstein, J.H. 2009. “It takes two to tango: dance steps for diagnosing Barrett’s esophagus.Respiratory Care Clinics of North America 69(6):1011–1013.

Settersten Jr, R.A. 2009. “It takes two to tango: the (un) easy dance between life-course sociology and life-span psychology.Advances in Life Course Research 14(1-2):74–81.

Skaerbaek, E. 2004. “It takes two to tango–on knowledge production and intersubjectivity.NORA: Nordic Journal of Women’s Studies 12(2):93–101.

Spencer, M. 2005. “It takes two to tango.Journal of Business Strategy 26(5):62–68.

Vanaerschot, G. 2004. “It Takes Two to Tango: On Empathy With Fragile Processes.Psychotherapy: Theory, Research, Practice, Training 41(2):112.

Viskochil, D.H. 2003. “It takes two to tango: mast cell and Schwann cell interactions in neurofibromas.Journal of Clinical Investigation 112(12):1791–1792.

Weiner, A. 2001. “It Takes Two to Tango:: Information, Metabolism, and the Origins of Life.Cell 105(3):307–308.

Wittman, M.L. 1990. It Takes Two to Tango: Your Simplistic System for Self-survival. Witmark Pub. Co.

There are also a few hundred groups who have demonstrated that larger groups can so as well.

Berkman Fellowship

Last week, the Berkman Center for Internet and Society announced it’s 2011-2012 list of fellows. I’m honored and excited that they elected to include me in a pretty incredible list of fellows, faculty associates, and other affiliates. It seems I’ll be at Harvard next year.

In my first year as an undergraduate — when fights over Napster were raging — I took a class taught by a Berkman Fellow on the political and social implications of Internet technology. The next year, I worked part-time as a teaching assistant for Harvard Law professor (and Berkman director) Jonathan Zittrain. These experiences had a enormous influence on my life and work. Before, my goal was to study and teach English literature.

I’ve hung around on the fringes of the center for much of the last decade and I’ve grown immeasurably from the experience. Most recently, I’ve been working closely with Berkman director Yochai Benkler and current fellow Aaron Shaw on research in online cooperation. The new crop of fellows includes a pretty great group of people working on similar stuff and I’m looking forward to expanding the online cooperation research at the center and to a year of fascinating talks and discussions. I also hope that, after all these, years, I’ll be able to give a bit back to an organization that has given me so much.

AcaMako

As I mentioned recently, I’ve been writing summaries of academic articles I read over on AcaWiki. You should join me and write summaries of academic articles you read or help improve the summaries other folks have shared!

Of course, you can also just read AcaWiki summaries. But while reading summaries takes less time that reading the full articles and books, a 500-1000 word summary is still too much for some very busy people. That’s why I created a new microblog on Identica where I post summaries of the summaries I post to AcaWiki. You can subscribe to AcaMako to follow along.

On Feminism and Microcontrollers

A month or so ago, I published a paper with Leah Buechley that is mostly an analysis of how the LilyPad Arduino has been used. I read an earlier draft last year and loved it so, when the opportunity arose, I was honored to help out as the paper evolved.

LilyPad is a microcontroller platform that Leah created a few years back and that is specifically designed to be more useful than other microcontroller platforms (like normal Arduino) in the context of crafting practices like textiles or painting. Leah’s design goal with LilyPad was to create a sewable microcontroller that could be useful for making things that were qualitatively different from what most people made with microcontrollers and that, she hoped, would be of interest to women and girls.

Our paper tries to measure the breadth of LilyPad’s appeal and the degree to which it accomplished her goals. We used sales data from SparkFun (the largest retail source for both Arduino and LilyPad in the US) and a crowd-sourced dataset of high-visibility microcontroller projects. Our goal was to get a better sense of who it is that is using the two platforms and how these groups and their projects differ.

We found evidence to support the suggestion that LilyPad is disproportionally appealing to women, as compared to Arduino (we estimated that about 9% of Arduino purchasers were female while 35% of LilyPad purchasers were). We found evidence that suggests that a very large proportion of people making high-visibility projects using LilyPad are female as compared to Arduino (65% for LilyPad, versus 2% for Arduino).

Digging deeper, qualitative evidence suggests a reason. LilyPad users aren’t just different. The projects they are making are different too. Although LilyPad and Arduino are the same chips and the same code, we suggest that LilyPad’s design, and the way the platform is framed, leads to different types of projects that appeal to different types of people. For example, Arduino seems likely to find its way into an interaction design project or a fighting robot. LilyPad seems more likely to find its way into a smart and responsive textile. Very often, different types of people want to make these projects.

Leah and I believe that there’s a more general lesson to be learned about designing technologies for communities underrepresented in science, technology, engineering, and mathematics (STEM) — and for women in particular.

The dominant metaphor in the discussion on women in computer science is Margolis and Fisher’s idea of "unlocking the clubhouse." The phrase provides a good description of the path that most projects aimed at broadening participation of women in computing projects seem to take. The metaphor is based around the idea that computing culture is a boys’ club that is unfriendly to women. The solution is finding ways to make this club more accessible to those locked outside.

It should go without saying that we share Margolis and Fisher’s goal of increasing participation of women in STEM. That’s LilyPad’s point, after all. It it hopefully also clear that we’re supportive of, and involved in, projects working to remove systematic barriers to participation by women and other groups. That work must continue. But I also think that Leah’s work with LilyPad suggests another way forward based on addressing issues of self-selection that will affect even the most welcoming technological communities. Here’s what we say in our paper:

Our experience suggests a different approach, one we call Building New Clubhouses. Instead of trying to fit people into existing engineering cultures, it may be more constructive to try to spark and support new cultures, to build new clubhouses. Our experiences have led us to believe that the problem is not so much that communities are prejudiced or exclusive but that they’re limited in breadth–both intellectually and culturally. Some of the most revealing research in diversity in STEM found that women and other minorities don’t join STEM communities not because they are intimidated or unqualified but rather because they’re simply uninterested in these disciplines.

One of our current research goals is thus to question traditional disciplinary boundaries and to expand disciplines to make room for more diverse interests and passions. To show, for example, that it is possible to build complex, innovative, technological artifacts that are colorful, soft, and beautiful. We want to provide alternative pathways to the rich intellectual possibilities of computation and engineering. We hope that our research shows that disciplines can grow both technically and culturally when we re-envision and re-contextualize them. When we build new clubhouses, new, surprising, and valuable things happen. As our findings on shared LilyPad projects seem to support, a new female-dominated electrical engineering/computer science community may emerge.

I have a strong belief that computing can be an empowering tool and that expanding users’ control over technology is a critically important issue. Our paper argues that we should attempt to expand participation in computing by broadening the possibilities of computing, rather than only by broadening participation in extant, computing organizations, projects, and genres.

Even if computing and electrical engineering communities were perfectly welcoming (which they are not) most people (both male and female, but disproportionately female) will choose not to participate. Building new clubhouses requires creativity of its proponents and risks charges of reinforcing stereotypes and existing status hierarchies. But, executed carefully and well (as I believe LilyPad has been), it suggests ways to reach the majority of people that no "unlocking" project will ever seem relevant to.

Contribute to AcaWiki

In the process of studying for my PhD general examinations this year, I ended up writing summaries about 200 academic books and articles.

AcaWiki is a wiki designed to host summaries of academic articles so it seemed like a great place to host these things. Over the last few months, I’ve uploaded all these summaries. Since I’ve finished, I’ve continued to add summaries of other articles as I read them.

My summaries tend to be rough. I write them, run them through a spellchecker, and then post them. I don’t even reread them before publishing. I hope to improve them as I reread them over time. Of course, because I’ve uploaded them to wiki, I hope others will add to and improve the summaries as well.

AcaWiki uses Semantic Mediawiki and provides nice platform for publishing, editing, and collaboration. Although there are still ways in which the platform can be better, what is needed now is, quite simply, more contributors. I am sad to see that my summaries make up a big chunk of all summaries on the site.

So if you are a student, an academic, or anyone else who writes or has written summaries of articles or books or if you might want to do so, you should consider contributing your summaries, in whatever form, to AcaWiki. I’ve done a little work to help integrate AcaWiki and Zotero which might make things easier.

Doctoral students reading for qualifying or general examinations in particular should should consider taking notes and studying with AcaWiki. From the student’s perspective, writing summaries can be one of the best way to reflect on and learn a literature. In the process, one can create a great resource for the rest of the world. If a single doctoral student from each of twenty diverse fields of study published summaries of the 200 key articles in their area, AcaWiki would have the critical core of what is most relevant in academia. Help us build it!