The ‘Public Interest’ Agency of International Organizations? The case of the OECD Principles of Corporate Governance

This article seeks to outline and explore some of the conditions necessary for International Organizations (IOs) to perform in a public interest fashion through a case study of the Principles of corporate governance formulated by the OECD. Rather than the more commonly documented pathological and dysfunctional behavioural forms of IOs, the case of the Principles, both in their formulation by the OECD, and in their assessment by the World Bank through the ROSC process, represent an episode of IO agency protecting and promoting a wider public interest. In exercising their agency, IO staff, have made the Principles more agreeable to a wider range of interested parties, giving them a general interest orientation, in accordance with a proceduralist definition of public interest. This case should therefore encourage IPE scholars to consider carefully and systematically the sets of circumstances and conditions, which might be required for IO agency to take more socially useful forms. In the final section, three indicators are identified which might be evaluated in future research into the positive public interest agency of IOs across a range of cases.

Manipulating and protecting entanglement by means of spin environments

We study the dynamical behavior of two initially entangled qubits, each locally coupled to an environment embodied by an interacting spin chain. We consider energy-exchange qubit-environment couplings resulting in rich and highly non-trivial entanglement dynamics. We obtain exact results for the time evolution of the concurrence between the two qubits and find that, by tuning the interaction parameters, one can freeze the dynamics of entanglement, therefore inhibiting their relaxation into the spin environments, as well as activate a sudden-death phenomenon. We also discuss the effects of an environmental quantum phase transition on the features of the two-qubit entanglement dynamics.

Inquiring into Non-Accidental Child Deaths: Reviewing the Review Process

There is significant public and professional interest in the non-accidental death of children where abuse and neglect are suspected of being contributory factors. Systems for reviewing these deaths have been developed in each of the four jurisdictions within the UK. The main aims are to ensure that individuals and professionals are held to account if practice falls below the expected standard, whilst also seeking to strengthen the systems for protecting children through reflecting on what lessons, if any, can be learnt from the death of a child through abuse or neglect. Recently, the benefit of such inquiries and the quality of serious case reviews have come under scrutiny. In this paper, the authors report the findings of a Delphi study that sought to explore how the process of conducting reviews following the death of a child could be improved through seeking the views of experienced professionals responsible for child protection in Northern Ireland. The authors conclude that the system does command professional support, but could be improved through greater attention to process issues and a stronger emphasis on translating learning into action. In common with research looking at other recent practice developments, there is a need to focus on process indicators as a means to ensuring that well intentioned policies are translated into workable and functioning practices.

Neural network forecasts of input-output technology

A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.