Cases are not objects at hand for legal decision-making; cases are not echoes from a past crime. Cases are, first of all, made within compound discourse apparatus, here the English Crown Court and the procedure/s attached to it. This book reveals the legal production of cases including their relevant features. The socio-legal ethnography visits the natural sites of adversarial case-making: law firms, barristers’ chambers, and Crown Courts. It examines the role and dynamics of client-lawyer meetings, pre-trial hearings, plea bargaining sessions, and jury trials. It focuses on the lawyers’ case-making activities, their procedural contexts, and the resulting cases. As an ethnographic discourse study, the book develops a trans-sequential perspective on the interrelated events and processes of case-making – and by doing so, overcomes the shortcomings of talk-bias and text-bias. The trans-sequential approach pays out in detailed case studies on an alibi, on guilt, or the barrister’s notes; it pays out as well in cross-case studies dealing with legal care, procedural infrastructure, or the case system in the common law tradition.

During the first half of the 19th century, the criminal trial changed beyond recognition to attain its modern adversarial form. This book discusses the dynamics of this transformation and, in particular, the role of the Prisoners' Counsel Act 1836.

Robert Kagan examines the origins and consequences of the American system of "adversarial legalism". This study aims to deepen our understanding of law and its relationship to politics, and raises questions about the future of the American legal system.

Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against

This book investigates how defendants are assessed by criminal justice decisionmakers, such as judges, lawyers, probation officers, parole board members and those involved in restorative justice. What attitudes and emotions are defendants expected to show? How are these expectations communicated? The book argues that defendants, at various stages of the criminal justice process, are expected to show a (more or less) free acceptance of guilt and individual responsibility along with a display of 'appropriate' emotions, ideally including 'genuine' remorse. It examines why such expressions of individual responsibility and remorse are so important to decision-makers and the state. With contributors from across the world, the book opens new comparative possibilities and research agendas.

Historical revisionism, far from being restricted to small groups of ‘negationists,’ has galvanized debates in the realm of recent history. The studies in this book range from general accounts of the background of recent historical revisionism to focused analyses of particular debates or social-cultural phenomena in individual Central European countries, from Germany to Ukraine and Estonia. Where is the borderline between legitimate re-examination of historical interpretations and attempts to rewrite history in a politically motivated way that downgrades or denies essential historical facts? How do the traditional ‘national historical narratives’ react to the ‘spill-over’ of international and political controversies into their ‘sphere of influence’? Technological progress, along with the overall social and cultural decentralization shatters the old hierarchies of academic historical knowledge under the banner of culture of memory, and breeds an unequalled democratization in historical representation. This book offers a unique approach based on the provocative and instigating intersection of scholarly research, its political appropriations, and social reflection from a representative sample of Central and East European countries.

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.