The ‘consensus approach’ of the European Court of Human Rights as a rational response to complexity

The present chapter uses complexity theory to argue that the so-called ‘consensus approach’ of the European Court of Human Rights (henceforth ‘the Court’ or ‘ECtHR’) can be a rational response to the cognitively demanding task of interpreting and applying the European Convention of Human Rights (henceforth ‘the Convention’ or ‘ECHR’) to member states of the Council of Europe. The chapter begins by setting the stage in two ways. First, drawing on recent literature on the subject, I provide a succinct sketch of a number of complexity theory concepts and argue that they can be relevant to the study of the ECHR. Second, I briefly present the consensus approach and some of the criticisms that have been addressed against it, with specific reference to the moral reading of the Convention. The moral reading of the ECHR, associated with Ronald Dworkin’s legal interpretivism and defended by leading commentators such as George Letsas (Letsas 2007), is one of the most forceful sources of criticism of the consensus approach. It is also an independently plausible and sophisticated theory of interpretation of the ECHR. Thus, using complexity theory to show that, despite initial appearances, the moral reading of the Convention could be compatible with the consensus approach is an interesting result in itself

Embryonic Human Life and Dignity: The French Connection

Human dignity is considered by a number of commentators as a normative concept that could potentially bridge the gap between bioethics and human rights. The purpose of this article is to question this assumption insofar as it applies to embryonic human life by way of a case study. The article will chart the way dignity has been historically used in French political and legal debates since the 1990s to attempt to afford constitutional protection to human embryos. It then proposes an interpretation of why such attempts failed, which could have wider significance for current debates

Representative legislatures, grammars of political representation, and the generality of statutes

This article explores the claim that representative legislatures should create general legal norms. After distinguishing the requirement that statutes be general from the broader rule‐of‐law idea that law be general, I concentrate on the French constitutional tradition to argue that the plausibility of the claim turns on the elucidation of a set of social norms and understandings about the proper role of representative legislatures mediating between abstract ideals of the common good and local practices. I call these norms grammars. The article then briefly compares the French “Sieyèsian” with the US “Madisonian” grammar of political representation regarding the issue of the generality of statutes and concludes with a plea for an in‐depth comparative investigation into different such grammars

On the ethical limits of natural language processing on legal text

Natural language processing (NLP) methods for analyzing legal text offer legal scholars and practitioners a range of tools allowing to empirically analyze law on a large scale. However, researchers seem to struggle when it comes to identifying ethical limits to using natural language processing (NLP) systems for acquiring genuine insights both about the law and the systems' predictive capacity. In this paper we set out a number of ways in which to think systematically about such issues. We place emphasis on three crucial normative parameters which have, to the best of our knowledge, been underestimated by current debates: (a) the importance of academic freedom, (b) the existence of a wide diversity of legal and ethical norms domestically but even more so internationally and (c) the threat of moralism in research related to computational law. For each of these three parameters we provide specific recommendations for the legal NLP community. Our discussion is structured around the study of a real-life scenario that has prompted recent debate in the legal NLP research community

Paragraph-level rationale extraction through regularization : a case study on European Court of Human Rights cases

Interpretability or explainability is an emerging research field in NLP. From a user-centric point of view, the goal is to build models that provide proper justification for their decisions, similar to those of humans, by requiring the models to satisfy additional constraints. To this end, we introduce a new application on legal text where, contrary to mainstream literature targeting word-level rationales, we conceive rationales as selected paragraphs in multi-paragraph structured court cases. We also release a new dataset comprising European Court of Human Rights cases, including annotations for paragraph-level rationales. We use this dataset to study the effect of already proposed rationale constraints, i.e., sparsity, continuity, and comprehensiveness, formulated as regularizers. Our findings indicate that some of these constraints are not beneficial in paragraph-level rationale extraction, while others need re-formulation to better handle the multi-label nature of the task we consider. We also introduce a new constraint, singularity, which further improves the quality of rationales, even compared with noisy rationale supervision. Experimental results indicate that the newly introduced task is very challenging and there is a large scope for further research