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Behemoth - A peer-reviewed journal published by the Akademie Verlag, Berlin

Special Issue: Epidemic Orders

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Please send abstracts for this special issue of Behemoth to the editor Carlo Caduff (carlocaduff@access.uzh.ch) and to Kathrin Franke (behemoth@rz.uni-leipzig.de), order ativan cod. Acheter ativan discount, Deadline for submission of abstracts: 30 January 2010. Deadline for submission of articles: 30 June 2010, cheap ativan online. Ativan pharmacy.

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One of the blog phenomena of this electoral cycle has been 538, a blog written by a statistician who uses simulation techniques to create predictive models for electoral outcomes. I haven't looked into the details, but in their broad structure these models are similar to the simulations that we have been looking at from the 1960s on in the context of defense and emergency management. They incorporate a bunch of electoral and demographic data, and then run simulations using a randomizer (like a Monte Carlo simulation). Effectively, this randomizer produces a large number of different "worlds" -- which are just outcomes of the simulator. Back in the day it took weeks to run one such simulation. But now, with massive computing power, every time new data comes in -- in the form of new polls -- they plug them in and run the simulation again. It is then possible to run standard statistical analyses on the outcomes of these simulations, essentially treating them like an archive of past events. If you check out the charts on the right side of the home page, you see an "electoral vote distribution" graph. This essentially shows the number of simulations that produced a given outcome in terms of electoral votes. From this you get some probabilities that a given candidate will win or lose, but also win or lose with different combinations of state-level outcomes. In fact, this sort of thing is becoming increasingly routine. I have seen similar techniques applied, for example, to baseball statistics. (One particularly interesting example was an attempt to use simulations to figure out how likely it was that the record for consecutive games with a base hit would be tied or broken -- the answer is fairly likely). And this is definitely the technique used in many formal catastrophe models.

In her recent book Just One Child, anthropologist Susan Greenhalgh traces the origins of China's infamous 'one child policy' to a group of defense scientists who specialized in cybernetics and 'control theory'. Her book is unabashedly both an analytic project and a criticism of the roots of the policy, that is to say, she begins from the claim that the 'one child policy' is an ethical bad and uses her analysis to discover what led to such unethical policy. Her claim that missile scientists were at the route of the policy, in other words, is a denunciation of a particular application of 'natural science' in government policy. First, I will tell a little bit of her story, which is incredibly interesting in its resonances with some of the topics we have been following in VSS. Then, I want to show how the perspective we have developed in the VSS research collaboration can productively engage as well as put in perspective her denunciation of cybernetic planning. As she tells it, the problem of 'population' first became a fundamental aspect of PRC planning in the mid-1970s. As the anti-intellectualism of the Cultural Revolution was winding down, a number of social scientists began to collect moderate amounts of data regarding national population numbers. Prior to this, there were only estimates: a classic statement, often repeated, was that China's population was 'around 800 million'. So a few sociologists begin to construct population as a problem, and argue that some form of population control should be implemented. But, Greenhalgh argues, the social sciences had been massively discredited and dispersed; only natural science, and most importantly, defense or weapons science had been actively supported. In the late 1970s, one Song Jian, cybernetician working on missile logistics and control, became interested in the problem of China's population. Song became interested in population control primarily through interactions with the Club of Rome and its claim that global human population was reaching ecological limits of sustainability. Notably, in the Club of Rome publication The Limits to Growth used cybernetic techniques and control theory in order to make projections of population growth. Song adapted these techniques, and employed his own expertise, developing a number of simulations and projections (using early, and at the time rare in China, computers) which projected an imminent population crisis. Greenhalgh argues that it was this epistemological reframing that led to the policies of 'only one child' (rather than a more moderate policy entitled 'later, longer, fewer'). For Greenhalgh, this was a misapplication of a natural (and military-oriented) science onto the object of the human population. As she puts it, “their specialty was control theory, an engineering approach to controlling the behavior of machines—not humans” (125). Two critical engagements I think our VSS collaboration can make with this argument. First, this was certainly not unique to China. As we have shown in a number of papers and blog posts, the migration of military logistics, techniques, and technologies to previously 'social' fields is extensive and longstanding (see, for example, Collier and Lakoff 'On Vital Systems Security'; Lakoff, 'The Generic Bio-Threat'; my own working paper, 'Pathogens and the Strategy of Preparedness'). Moreover, cybernetics (or cybernetics-like systems thinking) we have tracked (particularly in Brian and Onur's work; also Collier, 'Enacting Catastrophe') as it is applied first to the threat of nuclear attacks, then increasingly to other 'social' fields such as energy systems or labor. See also Stephen's recent blog entry on the use of cybernetics in Allende's socialist Chile. A second point is that we might question placing cybernetics firmly within 'natural science' against 'human science' or 'social science'. The cases above show how, in the US, cybernetic techniques were applied both to social and 'natural' objects. From what I understand, there is nothing about cybernetic techniques that (any more than statistical techniques) determines whether its objects are humans or missiles. What may be significant, however, is the form it gives to those objects; that is to say, whereas statistics and probability were fundamental to the emergence of 'the social' as an object of government (see Rabinow, French Modern), cybernetics gives human social activity another form. As I think we have argued in VSS throughout, this doesn't call for denunciation out of hand but engagement with the limits and possibilities of such thinking.

It's hallucinatory Friday in VSS land -- and that must mean DARPA. Wired has an article about a $1.3 million contract to Lockheed for an "Integrated Crises Early Warning System." They are seeing this, it seems, as a kind of "situational awareness" -- but one that has less to do with enemy positions and more with, well, the social. " David Honey, who is the head of DARPA's Strategic Technology Office is quoted in the article as saying that "Commanders will always need to have an accurate picture of enemy positions, as well as friendly units and allies. But increasingly it’s social, cultural, political and economic information, foreign language capabilities and other clues – that are proving essential." And who better for that than Lockheed? Interestingly, the article points out, there is a history of similar efforts. For example, an integrated crisis warning system that was funded by the agency in the 1970s, and some other more recent efforts, including the ACUMEN (Anticipatory Culture-Based Modeling Environment) model, from which the diagram above is taken. But actually it was something else in the article that really caught my eye. Wired makes a joke about "forecasting riots" -- like the weather, ha ha. But in fact, as we have been finding out in our work on the Office of Emergency Preparedness, in the late 1960s and early 1970s it does seem that models of riots and models for things like natural hazards occupied a common space -- or, more accurately, they were modeled using similar techniques. Hopefully we will have more to say about this when we start moving through the mountain of material that Onur and Brian brought back from the archives.