Wirtbarkeit : Cosmopolitan Right and Innkeeping

After defining Cosmopolitan Right as being limited to the conditions of “hospitality,” Kant includes “Wirtbarkeit” in brackets, a word which connotes innkeeping. Moreover, significant similarities obtain between the relevant passages of the Perpetual Peace and those of the Digest of Justinian on the obligations of ships’ masters, innkeepers, and stable keepers. Unlike ordinary householders, hospitality for innkeepers is a legal obligation, not a matter of philanthropy: they are deemed public officials with limited discretion to refuse travelers, and as fiduciaries of their guests strictly liable for losses to their property. Accordingly, this article attempts to explain Cosmopolitan Right at least in part by analogy to the private law of innkeeping. On this basis, it engages in the central philosophical debate about Cosmopolitan Right by accounting for Cosmopolitan Right solely from the “innate” right to freedom, rather than from “acquired” facts such as land or resource distributions or historical injustices

Traversing Racial Distance in Hip-hop Culture: The Ethics and Politics of Listening

Hip-hop is often studied as a ‘political’ culture. Listeners, however, often contest the attachment of a political nature to hip-hop. After the ‘dilution’ of “real” hip-hop by record labels seeking to package the sound for mainstream consumption, is it fair to say that hip-hop retains political relevance? To address this question I make two moves. In the first, I approach hip-hop from a perspective that moves beyond lyrics, seeking to understand what the music ‘does’ rather than what it represents. In the second, I take this approach to the study of race in hip-hop culture, examining how phenotypical variation affects the affordances and subject-positions available to a given body in hip-hop culture. In approaching hip-hop through the materiality of racial difference, I find that the “political” in hip-hop emerges in moments of creative and ethical experimentation in the face of alterity

Improving Distributed Representations of Tweets - Present and Future

Unsupervised representation learning for tweets is an important research field which helps in solving several business applications such as sentiment analysis, hashtag prediction, paraphrase detection and microblog ranking. A good tweet representation learning model must handle the idiosyncratic nature of tweets which poses several challenges such as short length, informal words, unusual grammar and misspellings. However, there is a lack of prior work which surveys the representation learning models with a focus on tweets. In this work, we organize the models based on its objective function which aids the understanding of the literature. We also provide interesting future directions, which we believe are fruitful in advancing this field by building high-quality tweet representation learning models.Comment: To be presented in Student Research Workshop (SRW) at ACL 201

OrganiZational communication and organiSational communication: Binaries and the fragments of a field

In this paper, I employ personal narrative to help cast light on connections and tensions between organiZational communication research, as produced in the United States, and organiSational communication research, as produced in Aotearoa New Zealand. I address the issue by highlighting three sets of differences between these bodies of research: canonical, institutional and theoretical. I then unpack how these differences are apparent in my own university before sketching out three ways in which we might productively use such tensions to achieve radical engagement, and critique disciplinary others, identities, and locations

Improving Distributed Representations of Tweets - Present and Future

Unsupervised representation learning for tweets is an important research field which helps in solving several business applications such as sentiment analysis, hashtag prediction, paraphrase detection and microblog ranking. A good tweet representation learning model must handle the idiosyncratic nature of tweets which poses several challenges such as short length, informal words, unusual grammar and misspellings. However, there is a lack of prior work which surveys the representation learning models with a focus on tweets. In this work, we organize the models based on its objective function which aids the understanding of the literature. We also provide interesting future directions, which we believe are fruitful in advancing this field by building high-quality tweet representation learning models.Comment: To be presented in Student Research Workshop (SRW) at ACL 201