Secret Codes: The Hidden Curriculum of Semantic Web Technologies

There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate learning through information technologies, and emerging ‘semantic technologies’ in particular. Drawing upon an empirical study of case-based pedagogy in higher education, we examine the ways in which code becomes an actor in both enabling and constraining knowledge, reasoning, representation and students. The article argues that how this occurs, and to what effect, is largely left unexamined and becomes part of the hidden curriculum of electronically mediated learning that can be more explicitly examined by positioning technologies in general, and code in particular, as actors rather than tools. This points to a significant research agenda in technology enhanced learning

The construction of marketing measures: the case of viewability

This study seeks to develop a critical understanding of marketing measures. Marketing measures inform a variety of marketing practices and have been subject to ethical, discursive and epistemological critique. Informed by a range of theoretical work, this study sheds light on the construction of a key marketing measure in digital advertising: viewability. It shows how a range of competing interests can be mobilized and aligned; how an object of interest can be stabilized; and how standards for measurement can be reconciled. Across this account, we can see how issues of accuracy, ideology and ethics are bracketed off as participants agree on which things matter and which things count

Governing PatientsLikeMe: information production and research through an open, distributed, and data-based social media network

Many organizations develop social media networks with the aim of engaging a wide range of social groups in the production of information that fuels their processes. This effort appears to crucially depend on complex data structures that allow the organization to connect and collect data from a myriad of local contexts and actors. One such organization, PatientsLikeMe, is developing a platform with the aim of connecting patients with one another while collecting self-reported medical data, which it uses for scientific and commercial medical research. Here the question of how technology and the underlying data structures shape the kind of information and medical evidence that can be produced through social media-based arrangements comes powerfully to the fore. In this observational case study, I introduce the concepts of information cultivation and social denomination to explicate how the development of such a data collection architecture requires a continuous exercise of balancing between the conflicting demands of patient engagement, necessary for collecting data in scale, and data semantic context, necessary for effective capture of health phenomena in informative and specific data. The study extends the understanding of the context-embeddedness of information phenomena and discusses some of the social consequences of social media models for knowledge making