Marc Ventresca and I wrote a quickie article for the London Times a few years back, a short what’s-what of economic sociology. In it, we wrote the following:
Intermediaries are vivid in these cultural and organizational studies of markets. They are, at the individual level: brokers, experts, consultants, analysts, and appraisers. They also work at the organizational level, as: mediating organizations, independent ratings agencies, standardized testing services. The role of intermediaries extend beyond the role of information broker, reducing uncertainty. Instead, they work to resolve ambiguity. Resolving ambiguity is necessary classificatory and commensuration work that allows markets to achieve settlement – of buyers and sellers, of rules and regulations, of the fungibility and legitimacy of commodities. The broader wisdom in this studies is a turn away from a comfortable and domesticated concern with uncertainty reduction. It is a core engagement with the myriad forms of ambiguity that stymie efficient “markets” in the standard economic sense and provide the challenges whose resolutions configure markets in particular ways. Traditional brokers address problems of information uncertainty. We emphasize the work of cultural intermediaries who manage core ambiguities in markets that make comparisons possible, such as the terms of valuation, metrics and categories.
This is what I want to take from the entanglement discussion. I’m not quite as interested in a doing to economics what STS has done to scientists, but I can certainly see it. I just don’t have as much a dog in that fight.
By contrast, I do think that this kind of category construction, valuation, metric-making, and the like are all less provocative but more productive. They are, as a number of us in this area have said, the sociology of the invisible, the infrastructure, the boring. Accounting systems, valuation, categorization, these are things which reduce ambiguity to a sufficient degree that we can have uncertainty. And then we can argue over price, efficiency, markets. This is where there is work to do. It’s not enough to say that the work of making categories, commensurating, disentanglement is all prior. You can’t set that in place and then look at how markets unfold from them. They are prior and ongoing, but relatively invisible. That’s important.
Comments
I would say that a ‘sociology of the invisible’ is as compelling a way of identifying a number of practices and arrangements that are integrated into and embedded within a diversity of institutionalized contexts and not just markets (my own field is education and health studies). As you say, they get short shrift because they are boring – boring, that is, until they ‘inexplicably’ fail, like infrastructure. So thanks for this observation, which crystallized some thoughts I was only able to express inchoately until now.
Still, I’m a little confused when you write:
“They are, as a number of us in this area have said, the sociology of the invisible, the infrastructure, the boring. Accounting systems, valuation, categorization, these are things which reduce ambiguity to a sufficient degree that we can have uncertainty.”
For the uninitiated and unsophisticated (that’s me), the distinction between uncertainty and ambiguity you’re drawing here is subtle, so I was wondering if you’d provide clarification. Ambiguity appears to be a type of situation where commensurability of objects/practices, etc. isn’t even established, so that we don’t even have stable entities about which to be certain or uncertain. Is that it? So here we’re dealing with ambiguity as a very specific type of uncertainty?
Good point, and let me try to clarify. More theoretically, this owes major debt to James March. His argument is (in part) concerned with decision-making. Uncertainty is something like saying, we know what our preferences/goals are, and there are lots of different paths to get there – what is the best path? You can reduce uncertainty (perhaps) with additional information, to get to an ideal decision.
Ambiguity is more like saying, even our preferences are unstable and we don’t know them; any of these paths are likely to change both our likelihood of getting there, but might also change the goal itself. So additional information is actually not going to solve the problem. Instead, we need to make enough things stable in order for ambiguity to be transformed into uncertainty, from where we might be able to move towards optimal solutions.
Now, for March, what’s interesting is that the world is ambiguous, and the best we can do is move forward and be flexible. For my purposes, the categories, commensuration, etc., is all work that gives enough stability of some things (criteria for evaluation), so that you can have movement of other things (price).
An interesting example is happening with regard to finance right now, and some of the market meltdown per mortgages and quantitative finance. Pablo Triana hits it on the head here:
I think the ‘total darkness’ is interesting, and he suggests that plugging in hypothetical numbers is not even possible at this point. It’s not totally parallel, but it captures some of what I’m thinking about.
Thanks for the clarification. I should have recognized the point from March. Finance and economics are far beyond my ken, but my elementary understanding of prices is that it’s a way of not only observing positions in a market but ‘getting’ observations in turn (in an almost Leiferian sense). So, if there is total darkness it raises the question of whether it’s a matter of not being able to see, or not being able to be seen, and why.