Getting Away With It:Corruption, Moral Indignation and the Limits of Legal Accountability

In this paper we address the idea of ‘legal but corrupt’ through a discussion of two cases: abuse scandals in the Irish Catholic Church and the financial services industry in the wake of the Global Financial Crisis. We identify two important dynamics that generated the scandals: that they were driven by strong and stable groups existing within a peculiar kind of ‘accountability space’ that we describe as ‘monastic’ and that those groups persisted with tacit or explicit support from the state. ‘Legal but corrupt’ is, we argue, a matter of insider incomprehension sustained by the ceding of sovereignty over some aspect of social or economic life.

The Corruption of Accountability

Our discussion focuses on the state’s ceding administrative power to special claimants for the state’s inattention. Legal corruption, by our lights, is less about explicit or implicit exchange relationships, and more about law being employed to carve out spaces where the state actively cedes spaces to private ‘sovereigns’ – sovereigns within the space, after it has been carved out – where they can regulate themselves as they see fit and where they can project their power over others without the state stepping in.

Robust bimodal person identification using face and speech with limited training data and corruption of both modalities

This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.

The challenge of MNCs and development: oil extraction, CSR, Nigeria and corruption

Globalisation has led to a shift in world order with the rise of the corporate non-state actor. This rise has led to an assumption that Multi-National Corporations (MNCs) must assume responsibilities beyond profit maximisation for shareholders. With the rise of the MNC as a corporate non-state actor there have been discussions around the role of business with regard to human rights.

This article looks at the case of oil extraction in Nigeria. Focussing on the historical dependency of Nigeria and the evolution of the state into a resource-dependent country, it looks at the limitations of existing human rights obligations as they relate to business. This article proposes that corporate social responsibility (CSR) policies of MNCs can act as a preliminary stage in the quest for wider human rights protections. It is in motivating MNCs to design and implement effective CSR policies in dependent states like Nigeria, that the challenge lies.