How to replicate the best bits of Academia.Edu?

Next month, Coventry University’s Centre for Disruptive Media is hosting an event entitled ‘Why Are We Not Boycotting’ The event will explore some of the issues around the adoption of a venture-capital-funded platform/social network/repository for the dissemination of scholarly research, namely:

Why have researchers been so ready to campaign against for-profit academic publishers such as Elsevier, Springer, Wiley-Blackwell, and Taylor & Francis/Informa, but not against for-profit platforms such as ResearchGate and Google Scholar?

Should academics refrain from providing free labour for these publishing companies too?

Are there non-profit alternatives to such commercial platforms academics should support instead?

Could they take inspiration from the editors of Lingua (now Glossa) and start their own scholar-owned and controlled platform cooperatives for the sharing of research?

Or are such ‘technologies of the self’ or ‘political technologies of individuals’, as we might call them following Michel Foucault, merely part of a wider process by which academics are being transformed into connected individuals who endeavour to generate social, public and professional value by acting as microentrepreneurs of their own selves and lives?

These questions are excellent starting points for interrogating the impact of Academia.Edu – or Google Scholar, Mendeley, ResearchGate, etc. – and we should rightly be suspicious of the practices of platforms whose revenue is generated from selling user data collected via a closed algorithm. Such platforms are also representative of the state of higher education in which there are fewer (and more precarious) jobs for an increasing number of trained PhDs, forcing researchers to become ‘microentrepreneurs of their own selves and lives’. This results in the elision of working and personal lives and increasing amounts of immaterial labour undertaken by researchers who are forced to think of themselves as brands.

No doubt, part of the success of Academia.Edu is its large and growing user-base that researchers are unable to ignore, something remarked upon by Kathleen Fitzpatrick in her recent post ‘Academia, Not Edu’: ‘I’ve heard many careful, thoughtful academics note that they’re sharing their work there because that’s where everybody is.’ I have also heard anecdotally of a university department requiring its researchers to upload their research to Academia.Edu or ResearchGate, most likely as another way for a university to ‘showcase’ its prestigious research outputs. Thus, many researchers are using Academia.Edu simply because their peers and colleagues are too.

But what cannot be avoided, I feel, is that Academia.Edu does offer some very useful features. Over the past month I have logged in a number of times, followed a handful of researchers and keywords, and generally tried to understand how the platform works. As a tool for research discovery, Academia.Edu is actually quite good at (seemingly) serendipitously highlighting research that I would otherwise have missed, either through keyword recommendations or other researchers uploading and/or bookmarking papers. Many of these aspects encourage a more collaborative and open way of working – not just openness about what one is writing, as in the case of working papers, but about what one is reading too. This way of working is one step away from open notebook science and provides a real-time picture of the research being conducted.

So, despite the negatives of Academia.Edu’s business model, there are many features that could be exported to an alternative. The difficulty is to unpick which of the interesting and useful features are actually embedded in the site’s business model and which can be extracted and installed in more progressive or cooperative platforms. For instance, would it be possible to build on the CoRe framework to replicate some of the more interesting features of Academia.Edu? And how in the absence of a data-centric business model would such a framework be maintained?

These are the choices that need to be made about data-driven platform capitalism in general: e.g., the precarious labour of Uber drivers means that fares are cheaper and so a worker-owned alternative might not be able to compete on price; but there are features of Uber’s technology that can be replicated by more progressive outfits to offer an ethical, but still convenient, service. In the case of Academia.Edu, the task now is to work out which of their features can be kept, which need to be let go, and which can be improved upon in an alternative.

Nevertheless, with every passing day platforms such as Academia.Edu increasingly strive towards monopolies and will become harder to unseat.




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