![]() ![]() This paper focuses on two major approaches to relevance: linguistic pragmatism and information retrieval, and shows that the concept of optimal relevance, as understood by theories of relevance, may serve well as an underlying explanatory framework for answering the question of why judges tend to argue by referring to past case-law even in those legal systems that do not recognize a doctrine of binding precedent. Case law, also known as precedent or common law, is the body of prior judicial decisions that guide judges deciding issues before them. Approaching this concept in this manner allows me to show that this choice is explainable within the theoretical framework provided by theories of relevance. The first case-study concerns cases deemed Totally Without Merit and examines whether caseload can affect judicial decision. To this end, we consider three case-studies. ![]() It further shows that ‘importance’ of past case-law is essentially a matter of the judge’s choice. Perhaps the most pervasive and accepted theory of how judges arrive at legal decisions is that enunciated by the Realists. It is common knowledge that the main difference between the civil and the common law systems is the question of the authority of the judicial decision as a. This chapter consider how understanding immigration judicial review decision-making requires an understanding of how wider forces influence judicial decision-making. This paper argues that in the context of legal systems that do not recognize a doctrine of precedent this approach is either oversimplified, or even erroneous. Studies employing network analysis to reveal hidden mechanisms in judicial decision making, both in common law as well as civil law countries often use rather vague concepts of ‘importance’ of judicial decisions, concepts that are not always thoroughly explained, tend towards certain relativity and are used together with other similar words, with or without attempting explanation of these concepts, or relying purely on operationalization. ![]()
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