About Charles Martin-Shields

I'm a doctoral student at the School for Conflict Analysis and Resolution at George Mason and a director at TechChange. I research and work on solutions for using mobile tech and social media for conflict prevention, peacebuilding, and development. The goal of this space is to spur conversation, crowdsource responses to my research, and geek out on theories of social change and technology. Views on this site are my own, and I take editorial responsibility for cross-posted content.

The Prevention Problem: Thinking about Rwanda 20 years later

Of my areas of interest, the two that stand out are violence prevention and technology. This year marks the 20th anniversary of the Rwanda genocide, and I’ve been keeping track of the media coverage which has included the usual themes of never again, and a call to seek the tools and capacity to prevent such events in the future. To really make this happen though there needs to be a differentiation between patterns of smaller atrocities and genocide. This presents a challenge for localizing peacebuilding, especially for those of us who work in the technology space.

First, we have to differentiate atrocities from genocides. There are books upon books worth of arguments about semantics (which are important from a legal standpoint!), but I want to generally focus on differences in scale and intent. A militant group might commit a one-time atrocity to make a political statement, a riot could lead to a military crackdown that spins out of control, one ethnic group might target another over land rights, etc. These can be atrocities, especially if there’s a pattern of events. Genocide, what happened in Rwanda 20 years ago, is different in scale and intent. The scope of violence is an entire identity group, and the intent is the elimination of that group. Unlike an atrocity, this requires state-grade organization and capacity. Indeed, these are rather blunt definitions that ignore a lot of semantic detail, but bear with me.

If our goal is the prevention of atrocities and genocide, and our preferred method is to empower local communities with the tools and skills to prevent violence before it starts, then scale and intention matter. If we take the example of election violence in Kenya in 2007/8, there were many atrocities committed, but the intent wasn’t overtly genocidal. Since that election there have been efforts made to reinforce peace keeping (not ‘peacekeeping’) capacity at the local level through training programs and innovative approaches to information sharing using mobile phones and social media. In this scenario the communities that would be affected by discrete events of violence could prevent the spark at the local level. Compare this to Rwanda in 1994, where the Hutu-led government provided the weapons and logistics to the militias that did the killing, and the aim was the elimination of the Tutsi ethnic group. There had been atrocities at the local level leading up to the genocide (particularly in the north where the Tutsi RPF militia was fighting Rwandan government forces), but when the genocide started in earnest the violence was top-down and totalizing. Local-level violence prevention and peacebuilding methods weren’t going to stop that level of organized killing.

So where does this leave us now? If the goal is violence prevention, then we have to recognize where the local strategies work, and be willing to push for international intervention when necessary. Start by asking,”is the violence extrinsically motivated, and localized?” Are people fighting over a tangible thing (e.g. land, access to water, representation in government)? If so, there are going to be opportunities for local-level peacebuilding and violence prevention. Public information and discourse will play a major role in this kind of peacebuilding, and communication technology can have a significant positive multiplier effect. Is the violence extrinsic and national, for example election violence? This is where intervention from the international community probably needs to happen, but there’s also a large place for localized peacebuilding too. For example, peacekeepers might come to enforce stability but local level peacebuilding needs to happen if the gains from a ceasefire are going to hold up in communities. Communication technology can play a role in linking communities to each other, as well as providing a conduit for sharing needs and information with the national government and international intervenors.

What about intrinsically motivated national level violence? This where local solutions start to lose impact, especially when we’re talking about the violence being carried out by the state against a minority. At this point, it’s unlikely communication technologies are going to be much use; either they’ll amplify negative messages in an already politically volatile space, or they won’t matter as violence becomes ubiquitous. Large, international intervention becomes necessary at this point to force the sides apart and impose stability while a peace process is undertaken.

Localized peacebuilding and technology are at their most effective before large scale violence starts. Communication technology in particular can play a powerful role in connecting communities, and breaking down narratives that can reinforce the kinds of intrinsic, dehumanizing narratives of violence that open the door to genocide. When we think about ‘preventing genocide’ we actually need to be thinking about how we prevent or intervene in the small atrocities which build up to a Genocidal event, because once that event has started it’s too late.

Learnings from ISA

Another March, another ISA conference. 2014 has been good, especially since the networking and socializing was matched by excellent feedback on what I presented. The highlights:

What I thought was a failed experiment in getting Twitter to love me actually teased out some interesting methodological challenges that other panelists on the Crowdsourcing Violence panel faced. Basically, the problem is how to encourage participation in the crowd when there isn’t an emergency. Whether it was crowdsourcing using Twitter or crowdseeding using trusted reporters, we all faced a challenge in getting participants to respond. This makes crowdsourcing and crowdseeding difficult to use as research methods. It’ll be interesting seeing how we all approach this challenge in our different papers and projects, to see if there are ways that incentives or networks can be tapped to get more consistent participation.

My paper on using crowdsourcing to support peacekeeping operations also got some good feedback. The paper was my attempt to think about technology in the context of peacekeeping operations, as opposed to peacekeeping being responsive to the technology available (e.g. how do we avoid deploying a technology solution seeking a problem). I’m going to take this in an institutional analysis direction, and focus on interviews with peacekeeping staff and experts since there is a paucity of documentation on the few crowdsourcing and crowdseeding projects that have been undertaken by missions.

This was an overall excellent week, with solid panels, fascinating topics and good conversation. If you have thoughts or feedback on my papers, feel free to share in the comments section, or shoot me an email!

Laying over, all over

I’ll be headed to the ISA conference in Toronto tonight, and since I’m coming from the South Pacific the journey will be full of layovers long and short. If you are in:

- Auckland, New Zealand! I will be there tomorrow all day and all day on April 1 wandering the streets and looking at things. I aways enjoy company when I wander streets and look at things, and my American phone number should be working (if you don’t have it and want to get in touch, email me or ping me on Facebook).

- San Francisco, United States of America! I already have plans, but my U.S. phone will be working and I will happily chat with you.

See you in April Samoa!

Kristof, Columbia, and the ‘Public Intellectual-Professor’: Part 2

Earlier this week I wrote the first half of this pair of posts, focusing on the problems in Nicholas Kristof’s piece on why professors should be more engaged in the public debate. I came down pretty hard on it, not because I disagree with the general sentiment (my doctoral research and interests are very policy relevant and I make an effort to be in the policy space as much as the academic), but because his logic was surprisingly faulty and he didn’t seem to have any understanding of the institutional culture and expectations of academia. In effect, he missed an opportunity to discuss the actual problems facing the academy, and how these prevent professors from being more publicly engaged.

Fortunately, Michelle Goldberg wrote an excellent rejoinder about the plight of two highly respected public intellectual-professors being let go after long careers with Columbia’s Mailman School of Public Health for failing to raise 80% of their salaries in external grants. While Kristof went off on confused, ill-informed tangents about what makes an academic or academic field relevant in to the public space, Goldberg focused on what Kristof should have been writing about: the corporatization of universities, where pulling in external funding is the difference between having a job and not. Doing ground-breaking research counts for nothing it seems, unless you hit the your fundraising target. I’ll take this a step further; the problem facing universities and researchers isn’t just the outcome of bad business planning at the university level. It’s the politicization of research, and by extension validity and truth.

To start: I don’t have a problem with the idea of encouraging professors in research-oriented fields to seek external funding. Part of my dissertation studies were funded by money my dissertation supervisor pulled in; he was able to hire me as a research assistant when the department didn’t have funds immediately available to give me a stipend. At a much larger scale pulling in something like a National Science Foundation (or National Institutes of Health) grant can give a department the latitude to fund students (saving money in the core budget), hire post-docs, pay visiting scholars, and generally increase the capacity to do research. This can be a useful model for certain projects, especially in the natural sciences where the costs of equipment and logistics can run into the millions of dollars. But there’s a danger to universities placing a demand that professors raise significant portions of their salaries through external grants, while not maintaining core budgets to keep them on during lean times.

One is the business model. The Mailman School, like many large research schools, relies heavily on government research grants. These days its not good to be relying on federal research grants, especially if you’re in the social and behavioral sciences. If an academic institution decided to hitch its financial wagon to the soft money strategy of external funding, then politics in Washington is currently delivering a harsh lesson in how the political economy of ridiculous budget battles affects university staffing. But this isn’t merely a technical budgeting and forecasting issue; budgets and Federal spending don’t live in an otological bubble, disconnected from politics and popular sentiment. This is where Kristof fell off the wagon and Goldberg hit the nail on the head. To quote:

“Kristof is right that universities have become inhospitable places for public intellectuals, but he misses the ultimate cause. The real problem isn’t culture. It’s money.”

Basically it was the only thing Kristof was right about, which is why it’s unfortunate that he only dedicated one short paragraph at the beginning of his article to it. But it’s not just money, it’s the interplay between Congressional politics and how we proxy the public interest with Federal (and State) budgets. Congress is the policy representation of our societal id, and as Kristof notes there’s a strong current of anti-intellectualism in that id these days. This is where the political economy of how we define validity, truth and public good comes in, and why we’re in such a pickle even though at times we’ve been leaders in natural and social science research.

Let’s start with the obvious; a Senator or House member doesn’t get elected by telling their rabidly anti-intellectual constituents that they’re wrong or ignorant. They also don’t get elected by telling their corporate funders that truly empirical research based on first principles has indicated that their business model or industry is god-awful for the public good. In combination, this is a solid reason for a member of Congress to be unsupportive of Federally funded research, since most of it points out uncomfortable truths about our economic system, global warming, poverty, infrastructure, system of government, etc. But let’s assume that a member of congress really wanted to understand what was going on in all that natural and social science research. How many are trained to properly evaluate science (social and natural) research?

Thanks to Business Week, we can find out. In the House, we have 1 microbiologist, 2 engineers, and 1 physicist, out of 433. In the Senate, there’s 1 engineer, out of 100. That’s a grand total of 5 out of 533 members of the Legislative branch. It’s important that we know this, since Senator Tom Coburn passed a bill that effectively gives Congress the ability to pick and choose with research gets funded through the National Science Foundation. Essentially, Coburn politicized the process of scientific and empirical inquiry. Don’t like research about homeless people because it shows that your anti-poverty policy prescriptions are fanciful lies? You can cut funding for it. Running for office and your petroleum industry donors find climate research distasteful? No problem, you can eliminate that in that NSF funding stream. We have allowed politicians, only 1% of whom might be even remotely qualified to understand science research, to be the ones who decide what is worthy of scientific inquiry even if they have no idea what a P-value or co-linearity is.

This is what was so infuriating about Kristof’s article; while peddling insulting caricatures of zany academics and their ethereal models and theories, it failed to address the real problems facing academia and universities. Goldberg hit on the problem of funding and what it means for the vibrancy of a research community, but the problem goes farther than that. As a nation we’ve allowed ourselves to be duped into believing that we can be world leaders in research, commerce, and foreign policy among other things, while simultaneously dismantling and defunding the institutions that for the last 70 years have been key to our success.

Fundamentally this isn’t a problem of university funding structures or academics doing their jobs, those are just symptoms. At it’s core, this is a problem of an American society that has given into cynicism and handed the reigns to politicians who prey on fear and ignorance. The only way to beat this slump is to regain our national spirit of inquiry, adventure, and critical thinking, the exact things made us leaders in research and discovery for much of the last 70 years.

Kristof, Columbia, and the ‘Public Intellectual-Professor’: Part 1

This will be a two-parter since there’s a lot in it. It’s been interesting reading the initial article about why professors need to be involved in public debate from Nicholas Kristof and seeing the rejoinders, particularly Michelle Goldbergs’ article about Columbia University’s decision to let two of their best professors of public health go. I’m a doctoral candidate whose research agenda is a hybrid between political science and public policy, and I haven’t decided yet on whether I want to go into academia or public policy, so I’ve found this debate interesting. Starting with Kristof, who I usually enjoy reading, I agreed with his sentiment at a meta level, but found the article generally ill-informed and at times oddly contradictory. Continue reading

Headed to Toronto soon…

I’ll be at the International Studies Association annual convention from March 26-30 presenting two papers (never again will I submit two abstracts for papers that have to be written from scratch…) on Crowdsourcing methodology and technology in peacekeeping operations. Should be a lot of fun – feel free to give me feedback on the papers as I get them posted and let me know if you’ll be in Toronto. I’m always up for a coffee, beer or lunch!

Finding Big Data’s Place in Conflict Analysis

Daniel Solomon recently posted a piece on how we conceptualize (and often misconceptualize) the role of big data in conflict event prediction. His post got me thinking about what role big data plays in conflict analysis. This comes on the heels of Chris Neu’s post on the TechChange blog about the limits of using crowdsourcing to track violence in South Sudan.

This is one of my favorite parts of Daniel’s post: “Acts of violence don’t create data, but rather destroy them. Both local and global information economies suffer during conflict, as warring rumors proliferate and trickle into the exchange of information–knowledge, data–beyond a community’s borders. Observers create complex categories to simplify events, and to (barely) fathom violence as it scales and fragments and coheres and collapses.”

The key question for me becomes: is there a role for Big Data in conflict analysis? Is it something that will empower communities to prevent violence locally, as Letouze, Meier and Vinck propose? Will it be used by the international community for real-time information to speed responses to crises? Could it be leveraged into huge datasets and used to predict outbreaks of violence, so that we can be better prepared to prevent conflict? All of these scenarios are possible, but I’ve yet to see them come to fruition (not to say that they won’t!). The first two are hampered by practicalities of local access to information, and bureaucratic decision making speed; thus, for me the interesting one is the third since it deals directly with an analytic process, which is what I’ll focus on.

When we talk about prediction, we’re talking about using observed information to inform what will happen in the future. In American political science, there has been a trend toward using econometric methods to develop models of conflict risk. There are other methods, such as time-series analysis, that can be used as well. But the efficacy of these methods hinges on the quality and attributes of the data itself. Daniel’s post got me to think about a key issue that has to be dealt with if big data is going to generate valid statistical results. This key issue is the problem of endogeneity.

To start, what is endogeneity? Basically, it means that the data we’re using to predict an event is part of the event we’re trying to predict. As Daniel points out, the volume of data coming out of a region goes down as violence goes up; what we end up with is information that is shaped out of the conflict itself. If we rely on that data to be our predictor of conflict likelihood, we have a major logical problem – that data is endogenous to (part of) conflict. Does data collected during conflict predict conflict? Of course it does, because the only time we see that stream of data appear is when there’s already a conflict. Thus we don’t achieve our end goal, which is predicting what causes conflict to break out. Big Data doesn’t tell us anything useful if the underlying analytic logic that was used in the data collection is faulty.

So what do we do? There’s all kids of dirty, painful math that can be used to address problems in data, such as instrumental variables, robustness checks, etc. But these are post hoc methods, things you do when you’ve got data that’s not quite right. The first step to solving the problem of endogeneity is good first principles. We have to define what are we looking for, and state a falsifiable* hypothesis for how and when it happens. We’re trying to determine what causes violence to break out (this is what we’re looking for). We think that it breaks out because political tensions rise over concerns that public goods and revenues will not be democratically shared (I just made this up, but I think it’s probably a good starting place). Now we know what we’re looking for, and a hypothesis for what causes it and when.

If the violence has already started, real-time data probably won’t help us figure out what caused the violence to break out, so we should perhaps look elsewhere in the timeline. This relates to another point Daniel made: don’t think of big events as a big event. Big events are the outcome of many sequential events over time. There was a time before violence – this would be a good place to look for data about what led to the violence.

Using good first principles and well thought out data collection methods, Big Data might yet make conflict analysis as much science as art.

*This is so important that it deserves a separate blog post. Fortunately, if you’re feeling saucy and have some time on your hands Rene Decartes does the topic far more justice than I could (just read the bit on Cartesian Doubt). Basically, if someone says “I used big data and found this statistical relationship” but they didn’t start from a falsifiable proposition, be very wary of the validity of their results.

New post on the TechChange blog!

I just had a new post go up on the TechChange blog – I haven’t written for them in a while, so it feels good to be writing for them again!

Here’s a brief intro, and you can read the rest here:

“In recent years, mobile phones have drawn tremendous interest from the conflict management community. Given the successful, high profile uses of mobile phone-based violence prevention in Kenya in voting during 2010 and 2013, what can the global peacebuilding community learn from Kenya’s application of mobile technology to promote peace in other conflict areas around the world? What are the social and political factors that explain why mobile phones can have a positive effect on conflict prevention efforts in general?…”

Nancy Ngo, one of the TechChange staff members helped get it written, so a big thanks to her for getting it up!

Samoa Post: End of semester observations

So I’ve been in Samoa for a semester now, working with the Ministry of Communications and Information Technology and getting things in order to do dissertation fieldwork. I’ll probably post again before the end of the year, but here are a few key themes that have emerged in conversation as I’ve developed relationships with my counterparts.

Continue reading