Working with INGOs as an Academic: The Pros and Cons

While scanning Twitter this morning I came across a post from Duncan Greene that caught my eye:

The blogpost he was linking to raises some excellent questions about the benefits of closer relations between academics and practitioners in the development space, and how to increase the overlapping parts of the academic/practice Venn Diagram. It resonated with me because if I hadn’t had a close relationship with institutions like the World Bank, TechChange Inc, UNDP, the U.S. Institute of Peace and many smaller NGOs during my PhD studies, I wouldn’t have been able to develop my dissertation topic, gather my dissertation data, or have a policy audience that would find my dissertation results useful. Greene proposes some good points about how to create these linkages that I completely agree with, and as an academic that has spent time as a practitioner in INGOs and IOs I felt motivated to chime in.

So why is it so hard to get academics to work with international organizations, NGOs and policy bodies? Greene’s post makes two major points about larger mandates (knowledge for the sake of knowledge versus knowledge to make evidence-based decisions) and time scale (academic research isn’t responsive to what’s happening in real time) that I think will forever dog the ability for practitioners and academics to work together. While there are more academic departments that are recognizing the value of research that feeds into policy development, for the most part academics receive little to no benefit (and indeed sometimes incur a negative cost) for engaging with government/international agencies and INGOs. This doesn’t mean there’s no space to collaborate, but it’s an issue that I think will always be there.

This gets at a major point that is critical for folks at INGOs and IOs to recognize. Academia is quite stringent about what counts toward advancement. With some rare exceptions, there’s little if any institutional reward for working on policy issues. Even if a department is supportive of it, tenure and rank decisions are made at the university level, so any policy work has to be on top of the expected publications and research funding that count in the eyes of the wider university. I’d argue the way to work around this as an INGO is to focus on relationships with PhD students and senior faculty. PhD students benefit from being ‘out there’ and having their research be seen more broadly – it’s been a huge help in my academic experience to have a wide range of contacts in INGOs and IOs who know my work. For senior (tenured) faculty the advantage is building relationships that can be useful to their students (many of whom won’t go into academia, but would love to work at Oxfam!), as well as having access to things like public service sabbaticals which makes it easier for them to take time off the research production line.

Indeed, Greene mentions having a PhD student who was doing his topic in coordination with with an Oxfam thematic policy. This is a fantastic way to bring academia and practice closer together, and it’s what I did a lot of during my PhD. It was great: I got the occasional nice consultant’s payday, got interesting feedback from non-academics, helped with policy issues, and still did work that is academically relevant. The main issue I found though was that this was not systematic at all – every INGO, IO, or agency I worked with was based on specific personal relationships. As long as the colleague was in that agency, I had a good relationship with that agency. When they left, the relationship with the agency ended (or more accurately, followed that colleague to their new agency). There are some good systemic efforts in the U.S. Government to bring academics into the policy fold, such as the AAAS fellowships which place social and natural science PhDs in government agencies for 1-2 years. To bring academics and policy people closer, there need to be more of these kind of system-level programs in place that cover the costs of having researchers working in organizations that are funded primarily to respond to current events.

It’s not impossible to work with junior faculty, but this is where understanding the idiosyncrasies of academia is crucial. One example is the idea of 50/50 action/research funding; it’s a good idea, but it’s hard to pull off in a way that mutually benefits the academic party. If an academic puts in many hours drafting a proposal and the only money they see is through a consulting arrangement, then it doesn’t count as grant money for them departmentally. If the research that then comes out of that money isn’t peer-review grade then they’ve potentially spent months of time working on a proposal and project that won’t move them toward tenure or their next academic rank. Most academic departments won’t count consulting work, even if it’s in-field, toward a junior faculty member’s tenure file. The way to solve this is for the INGO and an academic department to be co-applicants, so that the research side of the funding goes straight to the academic department with the academic’s name on it as a principal investigator. This allows the academic, at the very least, to count it on their CV as research money that was brought into the university even if the research outputs never see peer review.

The discussion about how to find new, better ways to bring academia and practice into a mutually beneficial relationship is important – a lot of public money goes into research, and the results should have public as well as theoretical value. While many departments are recognizing the importance of professors being involved in real-world work, it’s also important that INGOs and NGOs recognize that academia places very specific, often idiosyncratic, demands on researchers. By understanding those demands and working with academics to shape projects that meet those demands, I think there will be many more opportunities for academia and the practice community to create an increasingly overlapped venn diagram.

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Summer Plans and Updates

I’ve arrived and settled into Munich until early July, and along with a few trips to other parts of Germany and Brussels, it should be a good stay on the Continent. At the moment version two of the dissertation is under review, so hopefully by early June I’ll have feedback and an idea of when a defense will be scheduled. *Fingers crossed*

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In the meantime, I’m gearing up for the academic job market with a search primarily focused on Europe. The fun part of the search will be developing job market papers, of which a few are underway:

“Peace Durability, ICTs and Peacekeeping: Technology investments and post-conflict economic growth through peacekeeping operations,” with Nicholas Bodanac.

My colleague Nicholas Bodanac and I propose that peacekeeping missions use of ICTs can play a significant role in spurring economic development, by providing initial capital to encourage ICT infrastructure investment in post-conflict settings. This initial investment in ICT infrastructure can continue to have benefits, as education, business and government make increasing use of communications systems over time. This can support economic and political development, supporting more durable peace during and after a peacekeeping mission.

“Peacekeeping and the ‘Crowd’: How does Crowdsourcing Technology Support United Nations Peacekeeping Operations?”

I presented this paper at ISA back in 2014: “Multi-dimensional peacekeeping operations have evolved significantly since the late 1990s, but the capacity to meet the needs of local populations has lagged behind the political expectations of operational capacity. Efforts to improve data on local-level violence in Liberia, and local reporting of violence via SMS text messaging in eastern Democratic Republic of Congo have demonstrated the United Nations Department of Peacekeeping Operations’s (UNDPKO) interest in improving local-level information collection and public opinion. This paper will use these two cases to frame methods for localized data collection, then extend them by discussion how different crowdsourcing technologies and methods can be used by the UNDPKO. It will close with an analysis of the theoretical issues associated with technology-aided peacekeeping, and policy challenges that come with integrating crowdsourcing into the UNDPKO’s information collection and management processes.”

“Is the (Technology) Tail Wagging the (Development) Dog: How do private technology partners affect the goals of development programming?”

I’m revisiting this paper, which I presented in Singapore in early 2015: “Communications technologies (ICTs) have played an increased role in development programming since the early 2000s. Chief among these technologies are mobile phones, which have been integrated into everything from public health, education, disaster management, and public administration. The key question from the standpoint of how these programs affect local populations is whether they are designed based on the needs of the beneficiaries, or on path-dependent organizational decisions to use particular technologies based on popular trends or commercial availability. This paper will explore the political economy of using privately held technology and data services for international development, laying out theoretical and policy implications related to privacy issues, digital divides and ownership.”

“When Information Becomes Action: Information Technology Use in Kenya and Samoa when Managing Collective Action Problems During Crisis.”

Basically my dissertation research, but shortened and tightened up for a comparative politics journal.

“Are We Innovating Yet? Understanding how organizations and project leaders design crowdsourcing programs in conflict settings”

Also from my dissertation, a deeper look at a selection of crowdsourcing projects implemented for disaster response, conflict analysis, and violence prevention. The main question I ask is: How have organizations and project designers integrated mobile technologies into their interventions, and have these programs led to institutional innovation in humanitarian response and violence prevention? Does the use of these types of technologies lead to greater interaction between local and international actors, or is crowdsourcing merely an alternative mechanism for surveillance and data collection?

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Other than writing, I’ll be up in Berlin getting acquainted with the peacebuilding/conflict research scene June 7-11, and I’ll be in Brussels June 22-26 for the European Political Science Association meeting presenting the paper on peace durability, ICTs and peacekeeping. Should be a fun June!

 

The Blog Will be Fuller

After a lovely year in Sydney as a research fellow with IEP I’ll be headed back to the Northern Hemisphere to finish my dissertation. I should be defending it this summer – once it’s done, it’ll be on to new and exciting research!

This also means that I now have the freedom and time to start posting here again. While the year was fun it was also busy, which meant limited time to blog. I’m planning on some data-oriented posts, which will be fun.

The schedule the next month or two includes a presenting at the Midwest Political Science Association meeting, hopefully popping into the Tech4Dev conference on short notice, giving a paper with the inimitable Nicholas Bodanac  at the European Political Science Association meeting in June, and hopefully circling all the way back to the Build Peace Conference in September. If you’re going to be at any of these, or anywhere in between, give me a shout!

Build Peace 2015

I was invited to be a speaker on the panel on behavior change and technology in peacebuilding and Build Peace 2015. The panel was a lot of fun, with some fascinating presentations! You can find them on the Build Peace YouTube page. Here’s mine:

This was a particularly fun conference, pulling together practitioners, activists and academics in a setting that breaks away from the usual paper/panel/questions format of most conferences. Looking forward to next year!

Dissertation Proposal Defense

No, I won’t be ‘Dr.’ tomorrow, but the proposal defense is a milestone none the less. For those who are interested in my dissertation research, and can’t make it to my proposal defense tomorrow at 12:00PM at the School for Conflict Analysis and Resolution, below is a sound file you can listen to. You can download my slideshow here and follow along that way as well!

Upcoming events!

Unfortunately the last few months have been fairly low output in terms of blog posts. This can be credited to resettling after returning from Samoa, getting back to work with the tech community in D.C, and of course getting a dissertation written. I have had the chance to get myself on a few panels this month and next to discuss my research, though. I’ll be joined by some awesome people too, so hopefully if you’re in D.C. you can come out and join us!

October 15: Brownbag lunch panel at the OpenGovHub hosted by the Social Innovation Lab, FrontlineSMS, and Ushahidi.

November 5: Guest talk at Georgetown University’s School of Foreign Service about my research in Samoa, and larger issues of using ICTs for crisis response.

Later in November: Dissertation proposal defense at the School for Conflict Analysis and Resolution (exact date TBD). Open to the public!

Hopefully you can make it out to one or more of these, I think they’ll be really interesting!

 

Big News: The GDELT Global Dashboard

GDELT just released their new Global Visualization dashboard, and it’s pretty cool. It blinks and flashes, glows and pulses, and is really interesting to navigate. Naturally, as a social scientist who studies conflict, I have some thoughts.

1) This is really cool. The user interface is attractive, it’s easy to navigate, and it’s intuitive. I don’t need a raft of instructions on how to use it, and I don’t need to be a programmer or have any background in programming to make use of all its functionality. If the technology and data sectors are going to make inroads into the conflict analysis space, they should take note of how GDELT did this, since most conflict specialists don’t have programming backgrounds and will ignore tools that are too programming intensive. Basically, if it takes more than about 10 minutes for me to get a tool or data program functioning, I’m probably not going to use it since I have other analytic techniques at my disposal that can achieve the same outcome that I’ve already mastered.

2) Beware the desire to forecast! As I dug through the data a bit, I realized something important. This is not a database of information that will be particularly useful for forecasting or predictive analysis. Well, replicable predictive analysis at least. You might be able to identify some trends, but since the data itself is news reports there’s going to be a lot of variation across tone, lag between event and publication, and a whole host of other things that will make quasi-experiments difficult. The example I gave to a friend who I was discussing this with was the challenge of predicting election results using Twitter; it worked when political scientists tried to predict the distribution of seats in the German Bundestag by party, but then when they replicated the experiment in the 2010 U.S. midterm elections it didn’t work at all. Most of this stemmed from the socio-linguistics of political commentary in the two countries. Germans aren’t particularly snarky or sarcastic in their political tweeting (apparently), while Americans are. This caused a major problem for the algorithm that was tracking key words and phrases during the American campaign season. Consider, if we have trouble predicting relatively uniform events like elections using language-based data, how much harder will it be to predict something like violence, which is far more complex?

3) Do look for qualitative details in the data! A friend of mine pointed out that the data contained on this map is treasure trove of sentiment, perception and narrative about how the media at a very local level conceptualizes violence. Understanding how media, especially local media, perceive things like risk or frame political issues is incredibly valuable for conflict analysts or peacebuilding professionals. I would argue that this is actually more valuable than forecasting or predictive modeling; if we’re honest with ourselves I think we’d have to admit that ‘predicting’ conflict and then rushing to stop it before it starts has proven to be a pretty lost endeavor. But if we understand at a deeper level why people would turn to violence, and how their context helps distill their perception of risk into something hard enough to fight over, then interventions such as negotiation, mediation and political settlements are going to be better tailored to the specific conflict. This is where the GDELT dashboard really shines as an analytic tool.

I’m excited to see how GDELT continues to make the dashboard better – there are already plans to provide more options for layering and filtering data, which will be helpful. Overall though, I’m excited to see what can be done with some creative qualitative research using this data, particularly for understanding sentiment and perception in the media during conflict.

Quick thoughts from the #Tech4PP Twitter chat

I followed (and even participated!) in NDI’s Twitter chat today on using technology to increase political party and electoral participation. If you’re interested you can find the thread by searching the hashtag ‘#Tech4PP’. There were a lot of good examples of tech being used to increase participation, make processes more transparent, and boost inclusion in the political process. Below are a few quick thoughts that supersede the character limit:

1) I thought it was interesting that the chat tended to center around software and hardware, of which there were many interesting examples, but I tended to see less about the human or legal components of the process. I think it’s going to get really interesting to do experimental and empirical research on changes in political participation as social media and mobile based tools become increasingly available. ProTip for my academic friends who study political participation: look at this thread since it has a ton of examples you’d be interested in.

2) I saw a theme in the chat that asked about how we transition from digital outreach to human participation. I thought the framing was interesting since it set up technology as the causal mechanism of participation. I’m not sure I buy that directionality in a generalizable way; perhaps there are examples of this, but on average across cases I’d be inclined to think that the technology/participation relationship hinges more on the intervening variable of pre-existing political interest and knowledge of the issues within the community. I see a use for regression analysis here.

3) I threw a comment into the mix about the need to understand the regulatory and legal environment in a country where any kind of digital political participation software is being used. I’ll admit I’m surprised I didn’t see more on this topic, since it’s a pretty fraught space. Some of the more interesting questions around data ownership, regulatory effects on access to technology, and the cost of broadband could play a significant role in the overall impact of technology on political participation.

These are just a few questions that came to mind as I followed the thread – it was a good one, and I think there are some really good examples of tech for political participation that can be pulled out of it by researchers who are interested in learning more about the space.

Rigor Versus Reality: Balancing the field with the lab

I am finally able to respond (add) to a post by Chris Moore about the problem of mathematicization and formalization of political science, and social science more generally, as it relates to how the social sciences inform real policy issues.  As I’m finishing a Fulbright fellowship in Samoa, where I worked specifically on research supporting policy making in the ICT sector, Chris’s analysis was particularly apropos. As I read his post I thought “indeed, I’ve seen many an article in APSR that fall into the trap he describes,” articles with formal mathematics and econometrics that are logically infallible, use superbly defined instrumental variables, but have little explanatory value outside of the ontological bubble of theoretical political science. Why do academics do this? How can they (we…I’m sort of one myself) make academic research useful to non-academics, or at least bring some real-world perspective to the development of theory.

Qian and Nunn’s 2012 article on food aid’s effect on conflict is a good example of how formal methods can drive the question, instead of the question driving the method. Food aid indeed has an effect on conflict, and vice versa. To tease out a causal path from food aid to conflict though requires a logical stream that while formally correct, adds a lot of complexity to the argument. The thing that sticks out to me is they have to use an instrumental variable to make their argument. U.S. wheat production fits the requirements to be the variable they use, but do we really think that bumper crops in wheat actually lead to an increased risk of conflict? If so, is the policy prescription for decreasing conflict risk not allowing bumper crops of wheat? In the end they do a fair amount of complex logical modeling, then conclude by saying the data’s not good enough, we don’t really know the interactive effects of other aid on conflict, and that to really understand the relationship between food aid and conflict likelihood we need to explore the question in a different way.

Is there value in this type of exercise? Perhaps, but it’s probably limited to a number of academics who specialize in this type of intellectual exercise. Is this article useful to non-specialist readers or policy makers? Highly (99%) unlikely. Most policy makers don’t have the mathematical/statistical training to really understand the authors’ empirical strategy. If they do, they probably don’t have time to really digest it. That’s a fundamental problem, but it’s compounded by the use of an instrumental variable, which is a pretty abstract thing in itself. It’s not that it’s wrong, it’s that when we step outside the methodological confines the authors are working in, their analysis begins to lack inherent value. I don’t say this to shame or castigate Qian and Nunn; academics write for their peers since that’s who gives them job security.

So how do we derive value from this work if we want to inform policy? One way to do this is for academic departments to encourage doctoral students to try policy work during summers during the coursework phase. The summers between years one and two are good times for this; they’re pre-dissertation, so a student isn’t in a research mode yet, and the lessons learned during a summer in the field during coursework can feed into the writing of a dissertation. If we’re talking about faculty, departments can look for ways to reward writing for a general audience (about one’s field of specialization). Making public intellectualism part of the tenure file would probably be welcomed by many of the academics I know, who have a passion for their fields and would happily share their insights with public.

This has the added benefit of reducing groupthink or herd mentality, which academics are prone to like any other professional group. Possibly more so, since academic work is internally referential (academics cite each other). It’s easy in such an environment to stop asking why we’re adding a variable to a statistical analysis, or what value it has in a practical sense. By having to step out of the academic intellectual bubble, whether as a summer intern or to write an op-ed that has to be understood by a non-expert, it’s a chance to be in the field either physically or intellectually and re-assess why we’re analyzing particular variables and using particular methods.

At the very least it gives academics some raw material to take back to the lab, even if the ‘field’ is a disconcerting, statistically noisy place.