The 2027 census will include caste information, along with other demographic characteristics. Although the Supreme Court has ruled against stopping the caste census several times, it has not questioned the validity of the instruments to be used in the census operations—and therein lies the slip. It is important that the validity of the caste claimed by respondents be officially verified. India’s earlier engagement with a caste census is not encouraging.
Independent India conducted its first nationwide caste enumeration in 2011 through the Socio-Economic Caste Census, but the caste data was never published citing technical flaws arising from self-reported information that recorded more than 46 lakh distinct caste entries. Reports suggest that the pre-testing questionnaire for Census 2027 includes a self-reporting column for respondents to mark their caste, but the actual methodology will be revealed during the population enumeration phase.
Though a census provides a good snapshot of the population composition, understanding the dynamics of socio-economic and educational status by caste could also give rise to new conflicts. If a state disagrees with either the list of castes or the relative measure of educational and social backwardness, the question of an authentic database—the census or a state caste survey—would arise. Yet the enumeration by the census authorities shall be the basis for determining the proportion of reservation. This can be achieved more effectively through other means, and even better if the states conduct such operations.
We suggest that states be allowed to conduct caste surveys, because reservation policies differ across states. A state caste survey should answer five fundamental questions to decide the quantum of reservation. One, what proportion of the state’s population a caste constitutes? Two, how is a caste geographically distributed in the state? Three, what is the quantifiable measure of the educational and social backwardness of a caste? Four, what is the proportional representation of a caste group in employment in the public sector? And five, what is the proportional representation of a caste in higher education in government, government-aided and in self-financing institutions where reservation is implemented.
The purpose of a state caste survey should be to answer these questions based on authentic and verifiable facts, and not to identify beneficiaries for a reservation scheme. For this purpose, a well-planned sample survey or an extensive use of administrative data shall suffice.
Let us draw a parallel from food subsidy programmes. The National Sample Survey Office’s quinquennial consumer expenditure survey is a large-sample exercise to quantify the poverty ratio in each state and determine the food subsidy. The actual beneficiaries of the food subsidy are identified through an administrative survey and record verification. This process is not without pitfalls. The lack of political will to exclude the rich and the volatility in household incomes typically raise the proportion of beneficiary households well above the poverty ratio. Obviously, such a sample survey for quantifying relative backwardness of castes is much more complex.
To overcome this difficulty, combining administrative data from different sources to quantify the educational and social backwardness of castes in a state is a better way out. A state issues caste certificates to several lakhs of people every year through e-seva centres. All states have digitised this process. Except for those from social groups that do not receive reservations in education and employment, most people obtain such certificates. For a caste certificate issued to an individual, we can conclusively say that their parents and siblings belong to the same caste. Such information can be obtained in the application itself. This serves as a sample for collecting additional information from other records.
Normally, applications for a caste certificate require information such as the applicant’s and parents’ Aadhaar, parents’ caste certificates, residential address and parents’ occupations. Other individual beneficiary schemes, such as public distribution cards, LPG connections, income support for women, elderly, destitute, and widows, and scholarships scheme, collect information including Aadhaar, bank details, educational qualifications and income details. With this huge volume of information, state governments cross-verify the information provided by an applicant under different schemes using Aadhaar.
Further, states have access to other administrative data, including driving licenses, land holdings, electricity consumption, history of tax payment. Apart from this, states also have caste data on its employees and students. By collating all this, it is easier to answer the five questions listed above.
One missing link is information on the castes that have not been given reservations to date. A good sample survey of those excluded caste groups should help complete a comprehensive survey.
The Tamil Nadu government’s announcement for a ‘social justice’ survey is a good move. As an experiment, it can collate these administrative databases and publish anonymised datasets for researchers to analyse and answer the questions. Well-documented, authentic information on castes, population proportions, geographical profiles and relative backwardness can be created and revisited at frequent intervals to gauge the effectiveness of various schemes. That would truly present a sharper picture than we are currently seeking.
S Raja Sethu Durai | Professor of economics, University of Hyderabad
R Srinivasan | Former Professor, University of Madras
(Views are personal)