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Dynamics Among Nations: The Evolution of Legitimacy and Development in Modern States

Root, Hilton L.
MIT Press: London, 2013
ISBN 978-0-262-01970-5 (pb)

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Reviewed by Armando Geller
Scensei, LLC and George Mason University

Cover of book "Forget complexity. It doesn’t lead anywhere." This was the discouraging missive I would often receive when trying out nuggets of complexity science in sociology, international relations, anthropology and economics for my dissertation research. I could not find a satisfying – or rather satisficing – rationale for this advice, so I ignored it. A steady stream of research in the intervening years strengthened the notion that complexity, even with as diverse a grounding in the social sciences as it currently enjoys, can lead to better research paradigms (Axtell 2000; Moss 2004; Sawyer 2005). Hilton Root’s Dynamics among Nations supports this conjecture forcefully.

Dynamics among Nations sets out to contrast “the analytical framework of modernization theory with that of the evolutionary theory of complexity to explain unforeseen development failures, governance trends, and alliance shifts.” (p. 1) Root’s questions challenge conventional wisdom in international relations and political economy: He not only examines stability in a world where rising non-Western powers share hegemony with liberal democracies, but also addresses specific economic dynamics on other spheres of social life. For example, “As the South increases its share of interregional trade, what will the implications be for the evolution of networks of belief, ideas, and policy?” (p. 7) This framing of research questions reflects Root’s empirical work in South and East Asia where he worked for many decades with decision makers at the World Bank, U.S. Government, and the U.K. Department for International Development, among others.

The book shines where it prepares the ground for empirical social simulations to be employed as effective alternatives to toy models of all kinds. (Yes, sophisticated mathematical and statistical models are also toy models.) Unlike other arguments for using social simulations claiming that these models are better constructed than other models, Root’s implicates that such models will be in need because they can be better applied: Social simulations should be used in the world of policy, not because they are built better than other types of models (they are in most cases), but because they can change the way the social sciences are applied in practice. According to Root institution-centric approaches to development fail (p. 16) unless proper metrics capturing characteristics of social complexity and plausible behaviors representing human agency are introduced. To date, social simulations are the only models that satisfy both conditions. For policy makers, employing toy models in policy planning and evaluation brings about possibly irreversible impacts on the ground; a sharp contrast to the benign consequences of academic debates. Thus, Root’s call to take complexity into account in order to produce measurable insights into policy impacts is music to many a social simulation practitioners’ ears – and should be to many a policy makers’ ears. Yet, he gives no examples for how empirical social simulations can be built and used. This is a lacuna and missed opportunity to further move the field ahead, not least because examples do exist (Geller et al. 2014; Root et al. 2014).

The ideas introduced in this book are already having impact. A future edition should showcase Root’s work – full disclosure: some of which has been done in partnership with this reviewer – and subsequently aim at promoting adoption among practitioners. For those eager to read ahead, I suggest taking a look at Root et al. (2015). A number of collaborations fruitful for both policy folks and academics-cum-practitioners are already underway, providing decision support with high fidelity social simulations. Dynamics among Nations contributes to this important and long overdue development.

* References

AXTELL, R. (2000). Why Agents? On the Varied Motivations for Agent Computing in the Social Sciences. Report. Center on Social and Economic Dynamics. Brookings. Available at: http://www.brookings.edu/research/reports/2000/11/technology-axtell

GELLER, A. & Latek, M. M. (2014). Afghans in Iran: Measuring Prospects for Livelihoods and Sustainable Return. Unpublished technical paper produced on behalf of the Norwegian Refugee Council.

MOSS, S. (2004). Search for Good Science: A Personal Memoir. The New School Economic Review 1(1). Available at: http://www.newschooljournal.com/files/NSER01/03-08.pdf

ROOT, H., Jones, H., Wild, L. (2015). Managing complexity and uncertainty in development policy and practice. Overseas Development Institute. Available at: http://www.odi.org/sites/odi.org.uk/files/odi-assets/events-documents/5191.pdf

ROOT, H., Geller, A., Mussavi Rizi, S. M., Latek, M. M., Ramaligan, B., Jones, H. (2014). The Dynamics of Economic Policy Reform in Nepal: Modelling the Energy Sector. Unpublished report.

SAWYER, R. K. (2005). Social Emergence. Societies as Complex Systems. Cambridge University Press.


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