Geographies of truth and power: putting the linear model in its place

From www.politifake.org

Those who study the interactions between science and politics will often speak of the ‘linear model’ of science-policy relationships. By this they refer to the underlying assumptions in science-policy arrangements which hold that good scientific knowledge must always precede good decision making, and that the latter is wholly dependent on the former. In fact, the assumptions of the model often seem to go beyond an assumed relationship of dependency between decision making and science to approach a deterministic state whereby scientific claims can actually pre-empt and resolve policy conundrums. In this post I'll discuss some of the criticisms of this model before exploring some of the geographical or spatial elements of this assumed science-policy relationship.

The ‘presence’ of the linear model (or related assumptions) has been detected in a variety of fields, most often those related to environmental or public health problems. Perhaps the classic case of linear model thinking is provided by climate change debates, where the notion abounds that if only we can get the science right, good climate policy will follow easily in its wake (see http://www.ft.com/cms/s/2/6c7263f0-1589-11e1-b9b8-00144feabdc0.html#axzz1pw12UxG1). The main weakness of the linear model is that it ignores the politics inherent in any effort to produce far-ranging environmental policy. In the case of climate change, politics is everywhere – in equity considerations, in questions about future energy security, in debates about the role of market mechanisms in mitigation efforts, and so on. All of these debates are deeply normative, and cannot be resolved by a simple scientific statement about the state of the climate (for an example from the adaptation debate, see here)

The linear model, at its worst, seeks to depoliticize what are inherently political debates. It reflects an ideology of technocratic management which is seen to trump the practice of democratic politics. Elements of this style of reasoning are troublingly evident in many geoengineering discussions, where a looming ‘planetary emergency’ is seen to justify the application of novel technologies with scant regard for questions of legitimate anticipatory governance. Thankfully, many are now taking governance questions much more seriously in this particular debate (see this Royal Society report for example).

The model also ignores the influence that 'political' factors have on science itself, for example through funding patterns, agenda-setting, the politics and sociologies of advisory bodies, and so on. According to the linear model, science and politics exist in separate domains defined by a distinction between facts and values, thus enabling science to 'speak truth to power'. In this picture, truth flows unproblematically towards power, even as a generation of philosophers and social scientists have demonstrated the role of power in not only seeking-out particular truths, but also in defining them.

What interests me about the linear model is its inherent spatiality. ‘Linear’ is a geometric term, but it is applied metaphorically to describe the deterministic flow of reasoning from the scientific to the political domain, usually over time. ‘Domain’, again, is deeply spatial, but here the tenor is a particular part of the cultural life of a society – that of organised knowledge production or that of formalised decision making. I realised in writing that last sentence how difficult it is to step outside of a spatial parlance to describe how we divide-up our cultural practices into epistemic or political groupings. Indeed, metaphors are themselves a spatial phenomenon. As Rebecca Solnit writes in her short essay Drawing the Constellations, metaphors are “a line drawn between two things, a mapping of the world by affinities and patterns”. Any geographer will tell you that stepping outside of the spatial is not really possible, when even our very language functions by tracing extant connections and forming new associations between spatially dispersed referents.

Aside from its semantic elements, what spatial forms are enacted by the linear model and its attendant modes of thinking? A cursory glance at the voluminous IPCC reports will show you one spatial expression of this model. Here, the physical science (of Working Group 1) is arranged before any discussion of the societal impacts of climate change or possible response strategies. Any encounter with the IPCC reports sees the science coming first, as your eyes move from left to right across library shelves, on websites, and down the pages of university reading lists. In fact, I just noticed that my copy of 2007’s Working Group 1 report has always sat on the far left hand side of my book shelf where it currently nestles innocently alongside a copy of ‘Future Ethics’. The linear model has come home.

The natural flow of things?

Beyond book shelf geographies, the supposed linearity of science-policy relationships finds other ways to express itself in physical and social space. In the run-up to the much anticipated climate change negotiations in Copenhagen in December 2009, a large number of scientists went to great efforts to provide the negotiators with comprehensive updates of the science. It was two years since the publication of the most recent IPCC reports, and perhaps four years since the literature cut-off date for the IPCC assessments. A number of initiatives emerged, including the Copenhagen Diagnosis and the Climate Congress. I found it interesting how these projects were clearly born of a frustration at both a lack of progress in the UN negotiations and a perceived lack of ‘science’ in the negotiating room. To remedy this, these new scientific assessments were tied to the city of Copenhagen (either nominally or practically), so that their pronouncements could be discursively linked with the upcoming political negotiations. Throughout 2009 the city of Copenhagen was colonized by a cacophony of actors all exercising their rights to express their preferences and demands for new climate change policies. Prior to the climax of the city’s politicization, the scientists too were in town to formulate collective statements which could help drive the political process forward, and in the right direction. The time-space of Copenhagen in 2009 thus became another expression of a linear approach to the science-policy relationship.

I wonder what other spatial forms this relationship takes. It would be interesting to be able to closely observe the conference halls where scientists and policymakers interact and to note the patterns, timings and moods of their discussions. Perhaps the relationship also finds expression in university and research architecture. Thomas Gieryn has argued that contemporary laboratory architecture often expresses the demands of post-Fordist political economy, but do our research institutions also somehow embody the demands we make of knowledge producers in our political processes? Perhaps we could turn that question around to consider how the geographies of research themselves shape the assumptions we make about the political application of knowledge. I believe these are interesting questions for geographers of science to ponder.