Why we love data


As Jane Bennett points out, globalization has turned the earth into a unit of political analysis. Social scientists use a variety of tools to theorize about it, including images  (here Mitchell’s analysis I think could be helpful), and of course, data. I have thought quite a bit about data and graphical representations of it as things over the past few weeks as they come up frequently as representations of social inequality and poor health in some of my other classes. I wonder if we could consider graphs, and in particular a map of trade relations, as a representation of what Bennett terms the “radical kinship of people and things” (463):


Chase-Dunn:Average Trade Openness 1830-1992

Chase-Dunn:Average Trade Openness 1830-1992

A graph of trade relations specifically is particularly salient to Bennett’s article. Trade is an action that is regulated by humans, yet the effects of these trade flows and regulations often do thwart human agency, as seen for example by the economic crisis that unfair regulations have contributed to. It is perhaps an example of distributed agency on many accounts as the effects of trade (and the reasons why it is so tightly regulated) is not just about the banana or microchip, but rather much larger political systems of power. The political will behind trade laws is indicative of larger political issues, as such the effects of trade regulations on material commodities like bananas goes far beyond what you pay for one at Fairway. 

In short, I would argue that international trade is also an assemblage in which human agency is often thwarted by the agency of nonhumans. In the example of trade, the clearest example of this would be drought, pests, “natural disasters” that affect the production of commodities to be traded. A less clearer perhaps example is the economic inequality caused by many trade policies which benefit the few over others.  At the present times of globalization, these sorts of occurrences are much like the power outage in that they are felt in places far from where they occur, similar to the concept of the “cascade of effects”  as presented by Bennett. I would argue that social scientists love data because we believe that data demonstrates these cascades of effects. 

I could go on and on, yet I am afraid I will just become even more incoherent…

So to close, and to return to graphs which is where I began, I wonder:  How would a distributive understanding of agency affect our reading then of the following graphs of tax breaks and income distribution?


(Maps from David Harvey’s book: A Brief History of Neoliberalism, 2005).


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