How does infrastructure shape global governance? I am addressing this large question through a focus on the infrastructure of measurement at the global level. This work is part of a project in collaboration with Benedict Kingsbury, Paul Mertenskoetter, Thomas Streinz and Nahuel Maisley in which we hope to establish a network of scholars working on the role of infrastructure in global governance. In this talk, I take the lens of infrastructure as a way of understanding global practices of measurement and their political implications.
As I have argued elsewhere, counting is a deeply political process despite its claims to rationality and objectivity (2016). The political dimensions include decisions about what to count and what to ignore, which variables to disaggregate by characteristics such as race and gender to reveal biases in behavior, and how much to spend on collecting and analyzing information. Decisions about which categories to use to measure complicated concepts such as race or access to justice have political implications. Whether surveys should assume that respondents can simply check a box identifying themselves as male or female without considering the range of gendered identities that individuals claim is also a political question. Should a state invest more resources in setting up torture documentation centers in poor neighborhoods or simply expect all torture victims to report to established centers whether or not the poor can and will get there? These and endless other questions reveal the extent to which measurement is inescapably political. Although those who measure social life seek to measure existing patterns, they end up creating the world they are measuring.
Given the inevitably political dimension of measurement, however, I want to understand its operation through another, but not unconnected lens: that of infrastructure. The infrastructure of measurement is, to a large extent, shaped by access to resources which in turn reflects political decisions. My argument is that seeing measurement as a kind of infrastructure helps to explain its stability over time and its resistance to contestation once it has been established. This is a phenomenon often described as path-dependency, but I will focus on the material basis for this pattern as well as the forms of expertise and bureaucratic management that create measurement and resist change. I described this tendency to continue in the same path as data inertia and expertise inertia in my book.
Here I will build on that analysis by showing how thinking about the infrastructure of measurement explains these forms of inertia. Infrastructure also explains to some extent what gets measured and what does not and therefore what becomes politically salient and what is ignored. Infrastructure includes resources, templates for questionnaires, the cost of training data collectors, digital resources for data collection and analysis, expertise in framing data collection and analysis, and bureaucracies for managing, analyzing, and disseminating data. Big data has opened up a new terrain of measurement infrastructure. Since quantification is increasingly fundamental to questions of governance and accountability, issues surrounding the production of quantitative knowledge have enormous significance for governance.