Reflections on certain religious issues; particularly with reference to India.

Cet article s’intéresse aux gestes performatifs et aux pas de danse à travers lesquels les femmes colonisées de la bourgeoisie négocièrent les tensions profondes entre le patriarcat indien et la domination coloniale au Bengale (en Inde) à la fin du xixe et au début du xxe siècle. La première partie examine la contribution du Prix Nobel de poésie, Rabindranath Tagore (1861-1941), au développement de la danse au Bengale et replace sa pratique de danse au sein d’une discussion plus large sur (...) le genre et le nationalisme indien. La seconde partie explore l’intérêt de Tagore pour la mise-en-scène du genre et la décolonisation de la scène indienne à travers l’étude de ses lettres de voyage en Asie du Sud-Est. La troisième partie déplace le regard au-delà de l’idée d’auteur célèbre qui influence la plupart des écrits sur Tagore – poète et romancier, reconnu internationalement, notamment pour ses spectacles mettant les femmes au centre de la scène. À la place, cet article privilégie une lecture donnant à voir le travail et l’écriture sur la danse de sa belle-fille, Pratima Devi. Cette dernière conçut, supervisa, et travailla sur beaucoup des œuvres dramatiques et dansées de Tagore au Bengale, renversant ainsi beaucoup des normes qui étaient imposées par un nationalisme indien patriarcal sur les femmes issues de la bourgeoisie. Ainsi, cette étude incite à comprendre les relations entre le travail du corps des femmes dans et hors de la scène colonisée de la danse du xxe siècle bengali. (shrink)

Study of Saṅkṣepaśārīraka of Sarvajñātman, condensed version of Śārīrakamīmāṃsābhāṣya of Śaṅkarācārya, work on Advaita Vedanta philosophy.

When encountering a set of alternatives displayed in the form of a list, the decision maker usually determines a particular alternative, after which she stops checking the remaining ones, and chooses an alternative from those observed so far. We present a framework in which both decision problems are explicitly modeled, and axiomatically characterize a ‘divide-and-choose’ rule which unifies successive choice and satisficing choice.

The task of rhetorical role labeling is to assign labels (such as Fact, Argument, Final Judgement, etc.) to sentences of a court case document. Rhetorical role labeling is an important problem in the field of Legal Analytics, since it can aid in various downstream tasks as well as enhances the readability of lengthy case documents. The task is challenging as case documents are highly various in structure and the rhetorical labels are often subjective. Previous works for automatic rhetorical role identification (...) (i) mainly used Conditional Random Fields over manually handcrafted features, and (ii) focused on certain law domains only (e.g., Immigration cases, Rent law), and a particular jurisdiction/country (e.g., US, Canada, India). In this work, we improve upon the prior works on rhetorical role identification by proposing novel Deep Learning models for automatically identifying rhetorical roles, which substantially outperform the prior methods. Additionally, we show the effectiveness of the proposed models over documents from five different law domains, and from two different jurisdictions—the Supreme Court of India and the Supreme Court of the UK. Through extensive experiments over different variations of the Deep Learning models, including Transformer models based on BERT and LegalBERT, we show the robustness of the methods for the task. We also perform an extensive inter-annotator study and analyse the agreement of the predictions of the proposed model with the annotations by domain experts. We find that some rhetorical labels are inherently hard/subjective and both law experts and neural models frequently get confused in predicting them correctly. (shrink)

In the domain of legal information retrieval, an important challenge is to compute similarity between two legal documents. Precedents play an important role in The Common Law system, where lawyers need to frequently refer to relevant prior cases. Measuring document similarity is one of the most crucial aspects of any document retrieval system which decides the speed, scalability and accuracy of the system. Text-based and network-based methods for computing similarity among case reports have already been proposed in prior works but (...) not without a few pitfalls. Since legal citation networks are generally highly disconnected, network based metrics are not suited for them. Till date, only a few text-based and predominant embedding based methods have been employed, for instance, TF-IDF based approaches, Word2Vec and Doc2Vec based approaches. We investigate the performance of 56 different methodologies for computing textual similarity across court case statements when applied on a dataset of Indian Supreme Court Cases. Among the 56 different methods, thirty are adaptations of existing methods and twenty-six are our proposed methods. The methods studied include models such as BERT and Law2Vec. It is observed that the more traditional methods that rely on a bag-of-words representation performs better than the more advanced context-aware methods for computing document-level similarity. Finally we nominate, via empirical validation, five of our best performing methods as appropriate for measuring similarity between case reports. Among these five, two are adaptations of existing methods and the other three are our proposed methods. (shrink)

Summarization of legal case judgement documents is a practical and challenging problem, for which many summarization algorithms of different varieties have been tried. In this work, rather than developing yet another summarization algorithm, we investigate if intelligently ensembling (combining) the outputs of multiple (base) summarization algorithms can lead to better summaries of legal case judgements than any of the base algorithms. Using two datasets of case judgement documents from the Indian Supreme Court, one with extractive gold standard summaries and the (...) other with abstractive gold standard summaries, we apply various ensembling techniques on summaries generated by a wide variety of summarization algorithms. The ensembling methods applied range from simple voting-based methods to ranking-based and graph-based ensembling methods. We show that many of our ensembling methods yield summaries that are better than the summaries produced by any of the individual base algorithms, in terms of ROUGE and METEOR scores. (shrink)

In a Common Law system, legal practitioners need frequent access to prior case documents that discuss relevant legal issues. Case documents are generally very lengthy, containing complex sentence structures, and reading them fully is a strenuous task even for legal practitioners. Having a concise overview of these documents can relieve legal practitioners from the task of reading the complete case statements. Legal catchphrases are (multi-word) phrases that provide a concise overview of the contents of a case document, and automated generation (...) of catchphrases is a challenging problem in legal analytics. In this paper, we propose a novel supervised neural sequence tagging model for the extraction of catchphrases from legal case documents. Specifically, we show that incorporating document-specific information along with a sequence tagging model can enhance the performance of catchphrase extraction. We perform experiments over a set of Indian Supreme Court case documents, for which the gold-standard catchphrases (annotated by legal practitioners) are obtained from a popular legal information system. The performance of our proposed method is compared with that of several existing supervised and unsupervised methods, and our proposed method is empirically shown to be superior to all baselines. (shrink)

The main purpose of this article is to broaden U.S. scholars' awareness of the similarities and differences of gender literature in another part of the world. In providing this partial review of gender scholarship in India, the authors hope to foster critical reflection on the inequities of global knowledge production and consumption and the role of U.S. academic institutions and scholars in this project. The article is written not by scholars who are based in India but by those who are (...) based in U.S. academies. Given their location, linguistic and cultural competencies, and scholarly expertise, the review, at best, can be described as a glimpse of gender scholarship in India. The four sections of this article feature theoretical and methodological issues, the women's movement, and violence against women in India. (shrink)