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Distributed Open Collaborative Scholarship

DOCS is a necessary addition to the current landscape because much of the current activity either sits within or fails to challenge neoliberal values that apply across the entire ecology of teaching and learning, research and publishing.

Published onMay 28, 2020
Distributed Open Collaborative Scholarship
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Introduction

Technologies of communication, from the printing press to the digital platform contribute significantly to the transformation of knowledge. Digital technology is in the process of reshaping teaching and learning, research and publishing. Key features of the changing knowledge landscape include: distance learning, MOOCS, the development of open educational resources (including video, podcasts and other media),1 open access online courses and textbooks (MIT Open Courseware, Cambridge Core), the emergence of new scholar-led and university presses and the development of new disciplines such as digital humanities.

Over the last forty years, taking the 1980s and the development of the personal computer as a watershed in the development of digital communications, the pace of change has been relatively slow due to a combination of institutional and infrastructural factors. Transformational practices have remained marginal and incremental, introducing, for example, the digital classroom as an adjunct to the conventional lecture and seminar and subordinating open access publications to more traditional journal articles and monographs. However, in conjunction with the consolidation of a neoliberal model for higher education – characterized by funding cuts, rising tuition fees, casual and precarious labor, the marketization of courses, institutional and individual competition, the conflation of training and education, consumer relations between academics and students, instrumental research (impact), increased used of metrics and the development of an audit culture (UK) – technology is now accelerating the potential for change.

In a neoliberal context, market values dominate knowledge and culture as well as the economy, and, in the academic context values are currently limited to efficiency, transparency and compliance. Technology promotes efficiency by, for example, massively expanding the consumer base for marketable courses and academics (MOOCS); standardizing and systematizing research outputs (templates, protocols) and automating publishing processes and practices such as editing and peer review. Technology promotes transparency by implementing open access policies and mandates and through new forms of tracking and measurement from digital object identifiers (DOIs) to article based metrics. Various forms of monitoring, audit and surveillance, within what is rapidly becoming an obligatory digital enclosure, enable compliance to become more widespread.

The entanglement of technology and neoliberalism is detrimental to the present and future flourishing of knowledge in as far as knowledge is restricted and reduced to a limited set of values. These values are designed by and for a marketplace that is conflated with, but by no means equivalent to any notion of the public good. By extension, the first step towards reestablishing knowledge as a public good, and specifically as an urgently needed form of social and environmental justice involves disentangling technology from the limiting values of efficiency, transparency and compliance and promoting instead, values such as equality, diversity, care and inclusion. Ultimately, a new, post-neoliberal, ecological economics of scholarly publishing, teaching and research (representing the whole ecology of knowledge) should be founded on cooperation, collaboration and sustainability instead of growth and competition; responsible house-holding, or careful management of the environment, rather than the extraction of resource and exploitation of labor; and on the fair sharing of finite resources (labor and materials).

Distributed Open Collaborative Scholarship (DOCS) is a major new initiative that aims to redirect the technologization of knowledge by building structures (disciplines, practices, ethics) and infrastructures around a new ecological economics of teaching and learning, research and publishing. It builds on existing interventions such as FemTechNet, a Distributed Open Collaborative Course for students, scholars and artists working on feminist science and technology studies2; Fembot/Ada, a research collective and associated open access publication3; Goldsmiths Press, a new university press in the UK, dedicated to challenging the restrictions of neoliberal scholarship;4 Humanities Commons, a US project bringing together open access scholarship and teaching materials in the humanities5 and open access platforms such as arXiv.org and SOCarXiv.6

DOCS is a necessary addition to the current landscape because much of the current activity either sits within or fails to challenge neoliberal values that apply across the entire ecology of teaching and learning, research and publishing and incorporate both the sciences and humanities. Neoliberal economies promote and support open science at the expense of open humanities and globally, Arts, Humanities and Social Science disciplines are under threat. The development of commercial platform based publishing and scholarship, such as academia.edu, tends to be parasitic on both publishers and the academy, extracting published research with no reciprocal financial contribution. Moreover, by selling data based on research hits and trends, it represents something like the Twitter model for the future dystopia of scholarly communications in which the value of knowledge itself, and its social and environmental agency is subordinated to its economic value. Commercial platforms represent the next phase in the capitalization of knowledge and tend towards replacing old monopolies for new, the giants of commercial journal publishing with tech giants such as Amazon and Google.

Distributed

Distributed structures and infrastructures of knowledge, that work transversally across disciplines, research cultures (notably Science, Technology, Engineering and Math or STEM and Arts, Humanities and Social Sciences – AHSS), institutions and organizations (such as universities, archives, museums, galleries, publishers and non-commercial platforms) can, if they scale sufficiently, remain open sourced and develop community forms of governance, provide an antidote to the rise of knowledge monopolies.

Distributed models do not seek to break up or disrupt for example, the vertical integration of publishing houses in favor of a range of outsourced, user-centric publishing services that in any case will transit from an open competitive market towards a more monopolistic one.7 Rather, they seek to promote collaboration between mission-driven university press publishers, their respective institutions of teaching, learning and research and allied organizations in order to sustain and enable a more diverse ecology of public knowledge, necessary to fulfill the goals of social and environmental justice.

Neoliberal forms of knowledge, driven by market values, are narrowing, becoming systematized as well as standardized by disciplines, discourses and norms of communication. The process of systematization is both rapid and largely invisible, being a facet of technological infrastructures and of market-based values that are working their way “upstream” in the research cycle, redesigning knowledge, automatically pre-fitting it for an economy based on efficiency, competition, performance, growth, engagement or impact. The drift towards fully tech based, platform publishing captures the ideology of automation. In addition to automated text and data mining and automated peer review selection (in STEM) there is also the prospect of machine-generated text.

Machine-generated text is produced using the same software as deepfake videos. Generative adversarial networks or GANs are composed of two neural networks, one generator and one discriminator working against each other in order to create new data, stories, images or text. Given a specific training set, the discriminator will get better at distinguishing fake from real, so the generator has to improve the plausibility of its output. What is interesting here is the internalization and systematization of an adversarial process that is creative but ultimately indiscriminate, one that will give rise to technological forms of knowledge that are self-enclosed, self-generating and decontextualized. Where improved regulatory frameworks and digital literacy have a role to play, it is worth recalling a long cultural history of fakes and hoaxes, many of which have been satirical and politicized and the fact that machine, like human agency is relational, not autonomous and often – truly – antagonistic. GANS, however enclosed, are unlikely to remain unopposed.

Writing and publishing technologies are evolving, but automation remains a longstanding reach that will always exceed its grasp. While machine-generated texts and images still reside in the uncanny valley (that is, close, but not quite convincing), the ideology of automation promises to make scholarship homogeneous and systematic. It may never actually do this, but, without intervention, it will do something like this, because the technological imaginary works performatively, contributing to the construction of its own vision.

Distributed models are both machinic and humanistic, recognizing the relational, or transversal nature of both machine and human forms of agency. They are collaborative across all scales of knowledge and communication, applying to institutions, disciplines and (post-human) subjects. The value of distributed structures and infrastructures should be understood in strategic rather than essentialist terms, not as the ontology of digital technology but rather as a means of mutual support and symbiotic evolution.

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