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Despite the centrality of the contributory negligence doctrine in practice, very little is known about how it functions in reality. This volume provides legal practitioners with a one-stop-shop where they can find a clear and succinct exposition of the legal principles governing contributory negligence alongside an empirically informed analysis of the way that the doctrine operates in various recurrent factual scenarios, based on cases decided between 1998 and 2017. For each of the given recurring acts of contributory negligence, the average discount, the range of discounts, and the distribution of discounts are reported. These statistics are supplemented by way of illustrations drawn from the case law. Short summaries of typical cases for the relevant act of contributory negligence are given, along with summaries of cases that fall towards the higher and lower ends of the range of discounts. "This concise book will assist courts and practitioners in understanding this area of the law, and in applying a consistent approach when assessing, in the most common types of case, the extent to which damages should be reduced for contributory negligence. It is greatly to be welcomed." - The Rt Hon Lord Reed (from the Foreword)
This volume investigates the practical application and functional reality of the contributory negligence doctrine within the legal system. Authors Donal Nolan and James Goudkamp, both established legal scholars, utilize a comprehensive dataset of case law spanning from 1998 to 2017 to bridge the gap between abstract legal principles and courtroom outcomes. The text argues for a more consistent, empirically informed approach to assessing damages, providing practitioners with a structured framework for evaluating recurrent factual scenarios.
What You Will Find
Scope Limits
Legal practitioners and members of the judiciary identify this work as a practical resource for achieving consistency in damage assessments. Experts highlight the text for its unique combination of doctrinal exposition and quantitative data analysis.
Page Count:
152
Publication Date:
2018-01-01
Publisher:
OUP Oxford
ISBN-10:
0192545418
ISBN-13:
9780192545411
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