Local Events

Doctoral defense of N. Tayshete (online)

GEM PhD School doctoral fellow Neha Tayshete (LUISS Guido Carli & Université libre de Bruxelles) will publicly defend her thesis entitled:

GANDHIAN PERSPECTIVE ON “WORK ETHIC” FOR SUBSTANTIVE DISTRIBUTE JUSTICE/EQUALITY

Date & Time: Tuesday 29th September 2020, 16:30 onwards (CET)
Location: Online event on Webex, organised by LUISS Guido Carli
*Please note in connection with the online defense that the microphone and camera of all spectators must be turned off

Link to the event: https://luiss.webex.com/luiss/j.php?MTID=mebdb60f2585eca6aa74a05c7826a8674 (requires the download of the WebEx plug-in)

Research abstract

My doctoral dissertation pertains to creating a new “work ethic” , inspired by Mohandas Gandhi, Gerald Cohen, John Rawls and others, to substantially contribute to distributive justice and equality in analytical philosophy. I submit that my "work ethic" concept would plausibly be more compelling than the existing literature in this field. Following from my new ”work ethic”, it would reformulate concepts such as self-appraisal, desert, merit, incentives, responsibility, “expensive tastes”, "legitimate expectations" , Universal Basic Income (UBI) and humility for a more substantiate distributive justice and equality. The implementation of my "work ethic" is with Universal Basic Income (UBI), “effective altruism” and limited perfectionism (Gandhi's version of perfectionism as analysed by Bilgrami). It accounts for the changing economy in the twenty-first century, particularly with the research of Thomas Piketty, Gregory Mankiw, Lawrence Mishel, Alyssa Davis and others. It addresses and analyses the recent research of Scanlon and Kramer.

Jury members:

Prof. Sebastiano Maffettone (co-supervisor, LUISS Guido Carli)
Prof. Jean-Yves Pranchère (co-supervisor, Université libre de Bruxelles)
Prof. Valentina Gentile (LUISS Guido Carli)
Prof. Justine Lacroix (Université de Genève)
Prof. Stuart White (University of Oxford)

 

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This project receives funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No 722826.