Legislative Jurisdiction

Reese, Willis L. M.

doi:10.2307/1121857

Cited by 8 publications

(2 citation statements)

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“…Ford (1999: 843) refers to this as territorial jurisdiction, defining it in his influential analysis as ‘the rigidly mapped territories within which formally defined legal powers are exercised by formally organized governmental institutions’. ‘Black letter’ 2 legal analyses of jurisdiction tend to focus on the application of jurisdictional boundaries in relation to legal process (see, inter alia , Reese (1978) on legislative and judicial jurisdiction and Hall (2006) on the territorial limits on provincial legislative jurisdiction in Canada). These analyses acknowledge the relationship between territory, sovereignty and law but are not especially concerned with the nature of territorial sovereignty or the processes of boundary creation it engenders.…”

Section: Jurisdiction Legal Theory and Legal Geographiesmentioning

confidence: 99%

Sorting victims from workers

Strauss

2016

Progress in Human Geography

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This paper builds on work on forced labour and human trafficking to argue for the value of geographical approaches to legal scale, and for more geographical research on the process of jurisdiction. Vulnerability to forced labour and human trafficking is related to processes of social and political categorization and legal characterization. Yet territorial understandings of jurisdiction, and those which conceptualize jurisdiction as a process of sorting, often imply a relatively straightforward correspondence between legal scales and legal subjects. I propose an approach to legal scale that builds on feminist analyses in labour law and human geography.

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Section: Jurisdiction Legal Theory and Legal Geographiesmentioning

confidence: 99%

Sorting victims from workers

Strauss

2016

Progress in Human Geography

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“…Limited historical case law data reflects the reality across many branches of law, specifically due to the fact that different jurisdictions may have variations in regulations (Reese 1978). Mosbach, Andriushchenko, and Klakow (2021) provide a study on fine-tuning models for better generalization on small datasets.…”

Section: Introductionmentioning

confidence: 99%

Interpretable Low-Resource Legal Decision Making

Bhambhoria

Liu

Dahan

et al. 2022

AAAI

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Over the past several years, legal applications of deep learning have been on the rise. However, as with other high-stakes decision making areas, the requirement for interpretability is of crucial importance. Current models utilized by legal practitioners are more of the conventional machine learning type, wherein they are inherently interpretable, yet unable to harness the performance capabilities of data-driven deep learning models. In this work, we utilize deep learning models in the area of trademark law to shed light on the issue of likelihood of confusion between trademarks. Specifically, we introduce a model-agnostic interpretable intermediate layer, a technique which proves to be effective for legal documents. Furthermore, we utilize weakly supervised learning by means of a curriculum learning strategy, effectively demonstrating the improved performance of a deep learning model. This is in contrast to the conventional models which are only able to utilize the limited number of expensive manually-annotated samples by legal experts. Although the methods presented in this work tackles the task of risk of confusion for trademarks, it is straightforward to extend them to other fields of law, or more generally, to other similar high-stakes application scenarios.

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Jurisdiction, venue, and choice of law in medical malpractice litigation

Trail

Maney

1986

Journal of Legal Medicine

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Legislative Jurisdiction

Cited by 8 publications

References 0 publications

Sorting victims from workers

Sorting victims from workers

Interpretable Low-Resource Legal Decision Making

Jurisdiction, venue, and choice of law in medical malpractice litigation

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