Collaboration in electronic resource provision in university libraries: SHEDL, a Scottish case study

This case study examines the growth of collaboration among Scottish higher education institutions. Following a summary of the work of the Scottish Confederation of University and Research Libraries (SCURL), more detailed information is provided on collaboration in the fields of acquisition, licensing, selection, and purchasing. Some of the UK background is outlined, relating to NESLi2 in particular, in order to illuminate the options within Scotland. The origins of negotiations on electronic resource provision within Scotland are described, drawing on developments in other countries including Ireland and Scandinavia. After initial setbacks, the implementation of the Scottish Higher Education Digital Library (SHEDL) from 2007 to 2009 is detailed. Current benefits arising from SHEDL are explained, and some possible future developments are discussed

Morally Respectful Listening and its Epistemic Consequences

What does it mean to listen to someone respectfully, that is, insofar as they are due recognition respect? This paper addresses that question and gives the following answer: it is to listen in such a way that you are open to being surprised. A specific interpretation of this openness to surprise is then defended

Equal consideration of all – an aporetic project?

The article considers the relationships among three arguments that purport to establish the intrinsically contradictory or paradoxical nature of the modern project aiming at the equal consideration of all. The claim that the inevitable historical insertion of universal-egalitarian norms leads to always particular and untransparent interpretations of grammatically universal norms may be combined with the claim that the logic of determination of political communities tends to generate exclusions. The combination of these two claims lends specific force to the third argument according to which equal consideration perpetually requires the non-egalitarian project of understanding (excluded) individuals on their own terms. Hence, taking off from a recent debate between Christoph Menke and Jürgen Habermas, I argue that the former is right to diagnose an aporetic self-reflection in egalitarian universalism, while agreeing with the latter about the indispensability of deliberative democratic frameworks for the defence of both egalitarian and non-egalitarian norms

Authority, Autonomy and Automation: The Irreducibility of Pedagogy to Information Transactions

"This paper draws attention to the tendency of a range of technologies to reduce pedagogical interactions to a series of datafied transactions of information. This is problematic because such transactions are always by definition reducible to finite possibilities. As the ability to gather and analyse data becomes increasingly fine-grained, the threat that these datafied approaches over-determine the pedagogical space increases. Drawing on the work of Hegel, as interpreted by 20th century French radical philosopher Alexandre Kojève, this paper develops a model of relational pedagogy which highlights three points of incompatibility with a datafied learning environment reduced to finite measures. Firstly: Kojève’s accont of authority in Hegel posits two aspects to the mimetic relation between teacher and student: recognition and realisation, which belong to the ipseity or about-self-ness of the subject, and are incompatible with a general definition of data. Secondly, the Hegelian approach to human historical time, in particular the assertion that time and desire are begun in the future, not the past, renders it incompatible with mathematical time as used in data processing. Finally, from these it is possible to derive a distinctive notion of the work of pedagogy, grounded in Kojève’s realist reading of Hegel, irreducible to information processing. In consequence of this threefold irreducibility, the paper draws attention to a need for relations of human pedagogical work to be inherent in the design of educational technologies and highlights the dangers of presuming a machine intelligence model in the design of learning environments.