I’ve been thinking a lot recently about how the social sciences are proving too slow in catching up to developments in digital technology. This means that engagements with new possibilities are often piecemeal and ad hoc, pushing the threshold of innovation in methods while methodological and theoretical discussion lags further behind. We see changes at the level of platforms, infrastructures, devices and practices which allow new techniques to be developed but discussion of the implications of these techniques, how we should understand what they’re doing and how they fit with older and more established techniques struggles to catch up.
I’ve argued that the reasons for this are largely to do with the structure of scholarly communication. The proliferation of publications, with an estimated 28,100 journals publishing 2.5 million articles a year, encourages specialisation in both writing and reading. I’ve watched this happen first hand with the asexuality literature, something which has grown from literally a handful of articles seven or eight years ago to a topic which would have to now be my primary focus to ‘keep up with the literature’. This is a microcosm of a much broader trend which I think it’s important for us to understand.
This is compounded by a norm for much longer articles in many social science disciplines vis-a-vis scientific reports. The imperative to ‘keep up with the literature’ militates against exploration and experimentation, while established forms of social scientific writing make it difficult to get important technical details included in substantive articles in mainstream disciplinary journals. Furthermore, publication is slow and this compounds the inter-journal competition which inculcates intellectual conservatism all around by discouraging epistemic risk taking on behalf of those seeking to be published in the highest status journals and instrumental strategies from lower status journals seeking to raise their impact factors. The more that’s published, the more markers of prestige get fought over in order to ensure that one’s intellectual wares stand out in a crowded market place.
Established structures of scholarly communication engender slowness in catching up with technical developments. Is the solution therefore to find structures which facilitate faster communication? Two obvious examples stand out here: open science practices and social media. It’s surely a positive thing that open science is becoming better established within the social sciences, such as a journal like Big Data & Society requiring authors to publish datasets and self-archiving of pre-prints becoming an established practice now mandated in the UK in the case of papers. Likewise I think it’s a good thing that social media has been taken up by so many social scientists. It reduces the opportunity costs of exploring outside one’s own area e.g. it’s much less onerous to follow a data science blog then it is to keep up with the latest data science papers. As a corollary, it also makes it easier to form connections outside one’s own circles, both by making it easier to have things in common to talk about and also simply making contact with these people in the first place.
But the idea these practices would fix the problems of scholarly communication appears to me to rest on a fallacy: ‘slow’ communication is problematic because it entails friction and lag in what would otherwise be ‘fast’ communication. If we break down the barriers, will everything flow more freely and these seemingly intractable problems might be solved? There’s a rich imagery of ‘fast’ & ‘slow’, ‘open’ and ‘closed’, lurking in the background here which we need to be critical of on a political level. But in a more prosaic sense, I think it straight forwardly distracts from the fact that the problem with slow scholarship isn’t simply a structural matter, such that the established system of scholarly communication (aided and abetted by the incentive structures of the contemporary academy) moulds academics to be ‘slow’ and that if we ‘hack the system’ then it might then mould academics to be ‘fast’.
Under present conditions, I can see how ‘open science’ might lead to all sorts of new pathologies, particularly if the transition from ‘filter then publish’ to ‘publish then filter’ is tied up with the commercial logic of platforms like Academia.Edu, Mendeley and now SSRN. If monetisation of these platforms is dependent on user attention and user data, it stands to reason that engineering strategies serving to maximise both will become a commercial imperative, if they’re not already (and we shouldn’t underestimate how long tech companies can be propped up with capital while making zero profit). The in itself entirely reasonable proposition that non-traditional forms of influence should be incorporated into scholarly metrics is likely to compound such a move, naturalising the algorithmic black boxes of social media and open science platforms and creating new forms of prestige available for fast scholars.
These mechanisms might not dominate the platform, but the idea of fast, free, openscholarly communication allowing a million flowers to bloom away from the disciplinary structures of the contemporary academy is a dangerous illusion. It represents the common sense of the ‘market’, the epistemic superiority of the crowd, creeping into how we view scholarship. We can need to be profoundly critical about how attention, reward and hierarchy work on these new platforms without jettisoning their affordances entirely in our rush to critique. I’m not saying we shouldn’t use social media, only that we shouldn’t culturally embrace it as the superior ‘new’ in relation to the inferior ‘old’. It should be both/and rather than either/or. This is something which I think will be much harder if we continue to think in terms of ‘fast’ and ‘slow’, at least as an abstract dichotomy we apply to complex systems.
Nonetheless, I do think we need to in some way hack the structures of scholarly communication if the social sciences are going to reliably keep up in anything more than a narrowly technique-driven way to emerging technologies. But rather than ‘fast’ and ‘slow’, we should perhaps see this in terms of ‘collaborative’ and ‘atomised’: resisting the algorithmic incentives of platforms while embracing the affordances they offer for new forms of working together, even within the constraining structures of the accelerated academy.