Labs support the production of research, but what supports the production of labs? The answer is infrastructure, combined with the policy that brings that infrastructure into being and maintains it. For many scholars of media and communications, the near-synonymy of culture and infrastructure in the twenty-first century makes the study of infrastructure and policy imperative for anyone that wants to make a serious contribution to the critical tradition. While science and R&D labs seem to be ideal cases for the study of the sort of standardized, regulated, and technologically infrastructured spaces that then enable further standardized and regulated things to emerge, the hybrid labs that we investigate are also founded on various levels of infrastructure, from material technologies to gray literature (that mass of mission statements, grant applications, annual reports, and other documents that drives the creation and long term support of labs) to a multitude of protocols. This chapter discusses labs from the point of view of infrastructure and policy, highlighting the role of gray literature in how labs produce and circulate knowledge; the thick policy layer underlying lab infrastructure, with an extended case study on early home economics labs in the Canadian prairies as an example; and concludes with a discussion of a set of policy documents describing different approaches to knowledge production, university lab policy, and infrastructure in the new millennium. The first, Michael Century’s report for Rockefeller Foundation’s Arts and Humanities division, hews closely to the thread we have been pursuing throughout this book on the importance of hybrid studio-labs. The second is a study of the role of R&D lab research in the origins of contemporary policy interventions such as the “Arizona Model” for the reorganization of university strategy. The Arizona Model uses a particular series of linkages between policy, university infrastructure, and the national economy to bring about a radical transformation of the university in order to align it with neoliberal political aims.
As a concrete and contemporary example of the complexities surrounding something so foundational and subtle as infrastructure, on March 25, 2019, the US-based National Aeronautics and Space Administration (NASA) released a seemingly innocuous news brief in which the organization stated that they were updating “astronaut assignments” for the remaining two spacewalks of 2019. Christina Koch had been scheduled to conduct a spacewalk on March 29 with fellow astronaut Anne McClain in, according to NASA officials, “what would have been the first all-female spacewalk” (perhaps a gesture to Women’s History month in the US). However, after McClain learned in an earlier space walk on March 22 that a medium-sized spacesuit torso fits best, the organization found itself in the embarrassing position of only having one spacesuit that fit both women, and thus McClain was replaced with Nick Hague.1 The invisible, rarely mentioned infrastructure behind NASA consists of the many labs (as well as research and flight centers) across the world that attend to an astonishingly complex array of operations relating to aeronautics and space travel. Yet, despite its twenty-billion-dollar annual budget, the agency was unable to take into account the baseline needs of its female astronauts. Despite the “PR nightmare” that ensued, this should not be surprising considering that, as recently as 2017, according to Science magazine, “Women make up just 15% of NASA’s planetary mission science teams.”2 It is not simply a matter of how the organization needs to have equal representation amongst its employees. It concerns how the very notions of what counts as expertise and who counts as an expert are intrinsically tied to the infrastructure and administration of that crucial engine of knowledge production: the lab.
Infrastructure is a broad concept because what it describes is messy and complex. In her foundational essay, “The Ethnography of Infrastructure,” Susan Leigh Star writes that the common conception of infrastructure as “a system of substrates” which is “by definition invisible, part of the background for other kinds of work [and] ready-to-hand” works well for most purposes.3 As the embodiment of standards and protocols themselves, infrastructure is difficult to observe because it extends into and depends on other structures, technologies, and social arrangements to which it connects in a standardized way. Because it does not have to be reassembled or reinvented every time a task is performed, it really only becomes visible at moments of breakdown, lag, and other types of failure.
As Gregory Crane, Brent Seales, and Melissa Terras describe, in the context of research, infrastructure does have a materiality that we can describe, however complex it might be:
Infrastructure includes intellectual categories (e.g., literary genres, linguistic phenomena, and even the canonical book/chapter/verse/line citation schemes whereby we cite chunks of text), material artifacts such as books, maps, and photographs, buildings such as libraries and book stores, organizations such as universities and journals, business models such as subscriptions, memberships, and fee simple purchases, and social practices such as publication and peer review. Our infrastructure constrains the questions that we ask and our sense of the possible.4
In other words, infrastructure isn’t just about stuff. It is distinct from lab apparatus (see chapter 3), not simply as question of what is “inside” and “outside” of a given lab, but because of its scale. Infrastructure is larger and more nebulous than apparatus, but no less determinative of what goes on inside labs—sometimes even more so. “Infrastructure does not simply affect the countless cost/benefit decisions we make every day—it defines the universe of what cost/benefit decisions we can imagine.”5 Asking questions about infrastructure is part of the inquiry into how we relate to what’s inside a given lab, and how it structures our relations with each other, and, increasingly, with everything else.
As Alan Liu points out, our current experience of infrastructure is practically synonymous with the idea of culture itself because the substance of most of our lives, both inside and outside of work, is structured by how various kinds of institutions organize it.6 In its recursive mode, infrastructure gives shape to specific communities of practice which modify the shape of that infrastructure in turn. Often, the only way to learn its intricacies is through membership in those communities (where, in tandem with space and people, as we discuss in chapters 2 and 5, it often also performs a gatekeeping function, indicating who does or does not have membership and therefore access). In other words, to study infrastructure is to study the organization of social practices and relations as well as networks of things.7
Complicating things even further, infrastructure is time-critical in that it always involves practices taking place in a particular setting at a particular historical moment. Sheila Anderson, in her conclusion to “What Are Research Infrastructures?” picks up on this notion, observing that infrastructure is always about when as well as what:
infrastructure becomes research infrastructure as part of a process of change, collaboration, and engagement. In these infrastructures, collection-holding institutions act as creators, curators, and bearers of knowledge about their holdings; technical development seeks not only to capture and represent digital information and content but also the processes by which that knowledge is created and continues to be created as it is analysed and used; researchers act not just as users but also as ‘readers,’ of both the collection holding institutions and of the holdings, possessing both archival and artifactual intelligence, and weaving narratives based on interpretive and analytical research methods and processes.8
Considering the temporal aspect of infrastructure, as Foka et al. contend, allows us to consider how labs and the organizations that contain and fund them change over time.9 Studying the infrastructure of hybrid labs also requires us to think about the intertwined systems of substrates that structure the social and technical relations in, around, and through them that enable the production and circulation of knowledge at a particular time and place. As Foka et al. point out, though, this will require humanities scholars in particular “to review the categories that have so far helped us make sense of the sociotechnical reality we study. As technology progresses, we need to invent new concepts, relationships, and vocabularies to understand its impact. The concept of digital research infrastructure is, in this regard, especially challenging, as it cuts across and integrates concerns at multiple levels and across multiple temporal scales.”10
This review process is already underway. To assist in its study, Star, along with Karen Ruhleder, developed a list of properties to assist scholars thinking about infrastructure: it is embedded into various technologies and cultural assemblages; it is transparent and redundant because it does not have to be built from scratch every time it is needed; it extends beyond unique locales and events; it is inseparable from communities of practice that shape it and are shaped in turn by it; it uses standards and protocols to connect to other infrastructures; it is built on an installed base; it becomes most visible during breakdown; and it becomes fixed incrementally rather than in a totalizing manner because, although things like international standards bodies exist, “nobody is really in charge of infrastructure.”11
The perception that no one is in charge of it is precisely why studying infrastructure requires a critical perspective. As Liu has observed, digital humanities in particular tends to be “lightly antifoundationalist,” in that its scholars recognize that organizations and their attendant infrastructures might present themselves as orderly and rational, but they are just as messy as any other aspect of culture. However, Liu argues that these scholars are “less interested in exposing the ungrounded nature of organizational institutions and infrastructures (as if it were possible to avoid or get outside them) than in illuminating, and pragmatically guiding, the agencies and factors involved in their making and remaking.”12 Liu argues that a lightly antifoundationalist approach is of limited use because it ultimately supports the status quo, and we concur. Academic infrastructure has always been connected to other societal institutions, but these connections have become increasingly bushy and dendritic, complicating critical judgement.
We contend that hybrid labs are a product of the desire to use infrastructural affordances tactically, often for ethical reasons (Stone’s codeswitching umbrella, as we discuss in chapter 5, is a prime example). The fact that labs are products of a desire for tactical intervention of a sort also implies that critique of their infrastructure needs to be complemented by other forms of practice that produce alternatives in the course of lab work. There is, then, an opportunity to see labs as supported by and creative of novel sorts of infrastructures for academic practices that is relevant to a wider set of social contexts. Working in and around hybrid labs can and should lead to new ways of being a scholar, of training new scholars, and of connecting what happens in the academy to the larger world with all of its ambivalences, including the private sector.