199 resultados para Judicial selection
em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast
Resumo:
The rank of queen's counsel, granted under the royal prerogative, has been part of the architecture of the legal profession and legal system since 1594 but has undergone many changes in that time, including most recently the adoption of new selection procedures. Recent cases in Northern Ireland have raised the question - what is the legal position of queen's counsel? By examining decided cases in context, this paper aims to explain judicial perspectives on what it means to be a QC.
Resumo:
The role of Constitutional Courts in deeply divided societies is complicated by the danger that the salient societal cleavages may influence judicial decision-making and, consequently, undermine judicial independence and impartiality. With reference to the decisions of the Constitutional Court of Bosnia-Herzegovina, this article investigates the influence of ethno-nationalism on judicial behaviour and the extent to which variation in judicial tenure amplifies or dampens that influence. Based on a statistical analysis of an original dataset of the Court’s decisions, we find that the judges do in fact divide predictably along ethno-national lines, at least in certain types of cases, and that these divisions cannot be reduced to a residual loyalty to their appointing political parties. Contrary to some theoretical expectations, however, we find that long-term tenure does little to dampen the influence of ethno-nationalism on judicial behaviour. Moreover, our findings suggest that the longer a judge serves on the Court the more ethno-national affiliation seems to influence her decision-making. We conclude by considering how alternative arrangements for the selection and tenure of judges might help to ameliorate this problem.
Litigating the Agreement: Towards a New Judicial Constitutionalism for the UK from Northern Ireland?
Resumo:
This study examines the relation between selection power and selection labor for information retrieval (IR). It is the first part of the development of a labor theoretic approach to IR. Existing models for evaluation of IR systems are reviewed and the distinction of operational from experimental systems partly dissolved. The often covert, but powerful, influence from technology on practice and theory is rendered explicit. Selection power is understood as the human ability to make informed choices between objects or representations of objects and is adopted as the primary value for IR. Selection power is conceived as a property of human consciousness, which can be assisted or frustrated by system design. The concept of selection power is further elucidated, and its value supported, by an example of the discrimination enabled by index descriptions, the discovery of analogous concepts in partly independent scholarly and wider public discourses, and its embodiment in the design and use of systems. Selection power is regarded as produced by selection labor, with the nature of that labor changing with different historical conditions and concurrent information technologies. Selection labor can itself be decomposed into description and search labor. Selection labor and its decomposition into description and search labor will be treated in a subsequent article, in a further development of a labor theoretic approach to information retrieval.
Resumo:
Feature selection and feature weighting are useful techniques for improving the classification accuracy of K-nearest-neighbor (K-NN) rule. The term feature selection refers to algorithms that select the best subset of the input feature set. In feature weighting, each feature is multiplied by a weight value proportional to the ability of the feature to distinguish pattern classes. In this paper, a novel hybrid approach is proposed for simultaneous feature selection and feature weighting of K-NN rule based on Tabu Search (TS) heuristic. The proposed TS heuristic in combination with K-NN classifier is compared with several classifiers on various available data sets. The results have indicated a significant improvement in the performance in classification accuracy. The proposed TS heuristic is also compared with various feature selection algorithms. Experiments performed revealed that the proposed hybrid TS heuristic is superior to both simple TS and sequential search algorithms. We also present results for the classification of prostate cancer using multispectral images, an important problem in biomedicine.