An Alternative to India’s Reservation Policy: A Unified Framework for Rigorous and Adaptive Measurement of Socio-Economic Status


Authors: Dhruv Sinha, Ojas Sahasrabudhe, Dhruv Agarwal, Debayan Gupta
Venue: Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies 2020
Link: https://dl.acm.org/doi/pdf/10.1145/3378393.3402240

Affirmative action in the form of reservations is a divisive and contentious topic of policy in India. In this paper, we aim to create a principled and data-driven model to design the reservations policy in India. We look at some arguments against current policy and try to resolve them. We use statistical modeling to create our new framework, RAMSES (Rigorous and Adaptive Measurement of Socio-Economic Status). RAMSES measures the multidimensional disadvantage faced by an individual as an” adjusted income”, which attempts to calibrate the quantum of compensatory aid in the form of reservations for that individual to have a level playing field. We illustrate our model using a case study.

 

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