Open science and platform capitalism: a love story?

My notes on Mirowski, P. (2018). The future (s) of open science. Social studies of science, 48(2), 171-203.

In this provocative paper, Philip he takes issue with the “taken-for-granted premise that modern science is in crying need of top-to-bottom restructuring and reform” which underpins much of the open science movement, as well as its tendency to obscure the key question of the sense in which it was ever closed and who is now intent on opening it up (pg 172)? Doing so runs contrary to a popular teleology in which a fixed scientific method is now being forced open by the inherent promise of digital technology. If we instead treat science historically, with distinct periods defined by specific orientations, it becomes possible to see that “the open science movement is an artefact of the current neoliberal regime of science, one that reconfigures both the institutions and the nature of knowledge so as to better conform to market imperatives” (pg 172).

Doing so cuts through the semantic ambiguity of openness, allowing distinct phenomena (open access, open data, citizen science, different formats for publication etc) to coalesce in a quasi-unified way, making it possible for advocates to slide between these various expressions of an open science which is rarely, if ever, precisely defined as an integrated project. He argues that this new regime combines an ethos of radical collaboration with the infrastructure of platform capitalism. Its moral force rests upon a whole range of inditement of modern science:

1. Distrust of science is rampant in the general population: he takes issue in an interesting way with the assumption that more contact with scientists and more exposure to the practice of science will reverse this trend. Could it not do the opposite by personalising science through the mechanism of blogging and social media, making it even harder to convince the sceptical that its a disinterested pursuit? The precise form this scepticism takes varies (Mirowski’s example of educated neoliberals who believe scientists needs to feel market discipline before they can be trusted was particularly striking) but it’s a broad trend which can’t be wished away as a product of a reversible ignorance. This section reminded me a lot of the arguments Will Davies makes in Nervous States about the evisceration of representation as intermediaries are no longer trusted to act impersonally.
2. Science suffers a democracy deficit: he suggests this fails to recognise how ‘science’ and ‘democracy’ have both been transformed since figures like Dewey first made this argument in the early 20th century. The freedom of scientists, won in relation to a military-industrial complex in which they were embedded, came at the cost of the freedom of the public to influence science. The former apparatus has given way to a market complex such that “science has been recast as a primarily commercial endeavor distributed widely across many different corporate entities and organizations, and not confined to disciplinary or academic boundaries” (pg 176). What it is taken to mean to democratise science has changed radically in this context, reducing it to a ‘scripted participation’ (citizen social science) in the research process as part of an extended marketplace of ideas, as opposed to meaningful participation in the governance of science. In fact I wonder if populist attacks on ‘wasteful research’ and ‘mickey mouse subjects’ should be interpreted as a (pathological) attempt to democratise science? He is scathing about equating “a greater quantity of people enrolled in minor (and unremunerated) support roles with a higher degree of democratic participation, when, in fact, they primarily serve as the passive reserve army of labor in the marketplace of ideas” (pg 177).
3. The slowdown in scientific productivity: the promise suggested in open science to counteract a fall in actionable scientific outcomes (if I’ve glossed that correctly?) is belied by the form which openness takes within the regime of knowledge production found within commercial scientific research. If I understand him correctly, he’s saying that the organisational apparatus of contemporary science can’t support the openness advocated (e.g. intellectual property restrictions get in the way, the proletarianised condition of bench scientists within commercial organisations) and the “stunted and shriveled” openness it can support doesn’t seem to work anyway. Though I’m not sure I’ve interpreted this section correctly.
4. The explosion of retractions and the falling rate of falsification: many epistemic problems are ascribed by advocates of openness to the perverse incentives of the existing journal system. These problems can be seen most dramatically in the huge growth of retractions by journals of work which had passed the peer view process, with Retraction Watch currently identifying 600-700 retractions per year. A parallel problem is the basis against publishing falsifications in favour of positive additions to the knowledge system. The hope has been that the shift to a different business model might solve both problems.

If I understand correctly, his point is that a focus upon the deficiencies of science imputes to scientific practice what has its origins elsewhere. He offers a powerful inditement of the role of neoliberalism in producing the pathologies of contemporary science, listed on pg 188. But it’s unclear to me why this is either/or because the criticisms which open science advocates raise could be the outgrowths of neoliberalism’s influence? The point can be overstressed because in some cases there’s an active misdiagnosis correctly identified in his appraisal of these critiques but these are not universal and he seemingly misses the possibility of both/and:

The ailments and crises of modern science described in this paper were largely brought about by neoliberal initiatives in the first place. First off, it was neoliberal think tanks that first stoked the fires of science distrust amongst the populace that have led to the current predicament, a fact brought to our attention by Oreskes and Conway (2011), among others. It was neoliberals who provided the justification for the strengthening of intellectual property; it was neoliberals who drove a wedge between state funding of research and state provision of findings of universities for the public good; it was neoliberal administrators who began to fragment the university into ‘cash cows’ and loss leader disciplines; it was neoliberal corporate officers who sought to wrest clinical trials away from academic health centers and towards contract research organizations to better control the disclosure or nondisclosure of the data generated. In some universities, students now have to sign nondisclosure agreements if they want initiation into the mysteries of faculty startups. It is no longer a matter of what you know; rather, success these days is your ability to position yourself with regard to the gatekeepers of what is known. Knowledge is everywhere hedged round with walls, legal prohibitions, and high market barriers breached only by those blessed with riches required to be enrolled into the elect circles of modern science. Further, belief in the Market as the ultimate arbiter of truth has served to loosen the fetters of more conscious vetting of knowledge through promulgation of negative results and the need to reprise research protocols.

But he’s certainly correct that these overstatements legitimise platform initiatives which aim to reengineer science from the bottom up. The apparent diversity of these space is likely to decline over time, as a few platforms come to dominate. This opens up the worrying possibility that “Google or some similar corporate entity or some state-supported public/private partnership will come along with its deep pockets, and integrate each segment into one grand proprietary Science 2.0 platform” (pg 190). This platformization is likely to have unintended consequences, such a rendering science an individualised pursuit (he cites Orcid ID as an example of this – unfairly?) and setting up data repositories to fail if they are insufficiently succesful in attracting the data donors on whom their ultimate viability will depend.

He correctly identifies these platforms as facilitating a form of managerless control but I have an issue with the claim that “one automatically learns to internalize these seemingly objective market-like valuations, and to abjure (say) a tenacious belief in a set of ideas, or a particular research program” (pg 191). How automatic is the process really? If he means it as a short hand to say that it tends to happen to most users over time then I withdraw my objection. But if it happens in different ways and different degrees, we need to open up the blackbox of automaticity in order to see what causal mechanisms are operating within it.

He closes the paper by concretely laying out his case about why the platformization of science is a neoliberal process. Firstly, it breaks up the research process into distinct segments which permit of rationalisation. Secondly, the focus upon radical collaboration gradually subsumed the author into collaboration, in apparent contradiction of his earlier point about the individualisation of science. Thirdly, the openness for the user goes hand in hand with an opaque surveillance for the platform provider with monetisation assumed to follow further down the line. The most interesting part of this paper is how description of the ambition towards building a unified platform portfolio (mega platform?) for research and how this fits into the longer term strategy of publishers. There’s a lot to think about here and I suspect this is a paper I will come back to multiple times.