'Mining money': science, legal technologies & working the borderlands of global finance

This paper explores the roles of science and market devices in the commodification of ‘nature’ and the configuration of flows of speculative capital. It focuses on mineral prospecting and the market for shares in ‘junior’ mining companies. In recent years these companies have expanded the reach of their exploration activities overseas, taking advantage of innovations in exploration methodologies and the liberalisation of fiscal and property regimes in ‘emerging’ mineral rich developing countries. Recent literature has explored how the reconfiguration of notions of ‘risk’ has structured the uneven distribution of rents. It is increasingly evident that neoliberal framing of environmental, political, social and economic risks has set in motion overflows that multinational mining capital had not bargained for (e.g. nationalisation, violence and political resistance). However, the role of ‘geological risk’ in animating flows of mining finance is often assumed as a ‘technical’ given. Yet geological knowledge claims, translated locally, designed to travel globally, assemble heterogeneous elements within distanciated regimes of metrology, valuation and commodity production. This paper explores how knowledge of nature is enrolled within systems of property relations, focusing on the genealogy of the knowledge practices that animate contemporary circuits of speculative mining finance. It argues that the financing of mineral prospecting mobilises pragmatic and situated forms of knowledge rather than actuarially driven calculations that promise predictability. A Canadian public enquiry struck in the wake of scandal associated with Bre-X’s prospecting activities in Indonesia is used to glean insights into the ways in which the construction of a system of public warrant to underpin financial speculation is predicated upon particular subjectivities and the outworking of everyday practices and struggles over ‘value’. Reflection on practical investments in processes of standardisation, rituals of verification and systems of accreditation reveal much about how the materiality of things shape the ways in which regional and global financial circuits are integrated, selectively transforming existing social relations and forms of knowledge production.

Escaping the Cage of Ethno-National Conflict in Northern Ireland: The Importance of Transnational Networks

co-author; Cathal McCall

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.