Inclusion of Caste information in our Census

• As the 2011 Census approached, demands for inclusion of data on caste in Census increased.
• The then Union Home Minister, P. Chidambaram, opposed to collect caste data and blocked it by claiming that it was logistically impossible for the Census. But, suggested caste information could be collected via the planned Below Poverty Line (BPL) Census, later renamed the Socio-Economic and Caste Census (SECC).
• However, hasty inclusion of the caste question in the SECC has resulted in largely unusable data.
• The government tasked former NITI Aayog chairman Arvind Panagariya to look into this, but the effort has stalled.

Can 2021 Census provide effective data on caste?

• There will be demand again for the inclusion of data on caste in 2021 Census.
• It also seems likely that once again India will be unprepared for a full caste census.
• If India really want to collect data on caste and not let the discourse about Indian society be shaped by the political exigencies of colonial India, the time to plan is now.
• Consequently, if we want information regarding the size and characteristics of various castes in India, we must continue to look to the Census of 1931.

Big question: Should India collect data on caste?

Arguments opposing Caste Census

• Some argue that simple act of asking about caste creates a chasm or rift within society.
• Part of this resistance comes from reaction to the preoccupation of colonial administrators-turned-arm-chair anthropologists who saw caste as the defining feature of Indian society.
• We know that, the first Census began in 1871 under Colonial Rule.
• Colonial censuses included questions about caste and used these data to divide and conquer India by first privileging Brahmins as interpreters of Indian culture and then targeting them as the roots of caste-based oppression and inequality.

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• G.S. Ghurye, the early 20th century Indian sociologist, reacted sharply by identifying this passion for caste classification as the source of anti-Brahmin movements.
• Veena Das, Indian anthropologist, also notes that the colonial Censuses via the process of recording caste generated a conception of community as a homogeneous and classifiable community and thereby influenced the processes of political representation. Consequently, post-Independence Censuses have shied away from including questions about caste.
• Critics argue that – On one hand we say that India is growing and becoming a developed nation while on the other we are agreeing to the caste based census.
• Are we really trying to show to the world that we are still tied in the ropes of a caste based society? In a secular and independent country like India, is there still any scope for the old caste based census that used to be followed during the British rule?
• The policy of the government to give quotas and reservation on the basis of caste rather than on the basis of economic status is discriminatory towards people of other caste and is often condemned by the common people.

Arguments in favour for Caste Census –

• If caste information is not collected, we will have denied ourselves an opportunity to make quotas function in an equitable manner, says Prof. Indira Rajaraman (who was member of the Thirteenth Finance Commission)
• Our political systems, civil society and courts continue to assume that broad caste-based social categories — Dalits, Adivasis, Other Backward Classes (OBCs) and upper castes — defined largely using data from 1931 Census and a few special purpose surveys continue to shape economic conditions in 21st century India.
• Without accurate data at a granular level for each of these categories consisting of thousands of jatis (castes) and upjatis (subcastes), we have no way of knowing whether this is correct.
• Indian society has undergone a tremendous transformation since 1931.
• Land ownership that bolstered the power of upper castes has lost its hold.
• Land fragmentation and decades of agricultural stagnation have turned many upper caste landowners into marginal farmers barely eking out a subsistence.
• While landlessness, once the bane of Dalit existence, has left the landless better poised to take advantage of rising rural wages, particularly construction wages.
• Consequently, the National Sample Survey (NSS) shows that mean consumption expenditure of forward castes is higher than that of Dalits, clusters of poverty persist among forward castes.
• According to NSS data, the bottom fourth of forward castes are poorer than the top half of Dalits.
• India Human Development Survey shows that 56% of Dalit children ages 8-11 cannot read but neither can 32% of forward caste and 47% of OBC children.
• Economic growth of the past century, combined with strong affirmation action undertaken by successive governments of the independent nation, may have changed relative fortunes of various groups.
• Some jatis may have managed to pull themselves out poverty and marginalisation, while others may have sunk into it. Hence, it is time to collect data that reflects the current situation.

Drawbacks of SECC

• Even though SECC was conducted in both urban and rural areas, government has released only SECC data of rural India.
• SECC collates data regarding the caste of the people. This caste related information faces the danger of being misused by political parties for their ulterior motives.
• SECC data must be regularly updated in order to remove beneficiaries who have overcome their deprivations. This will put a huge burden on the part of the government.
• Sometimes the same caste is spelt in different ways, at other times some individuals report their jati and others upjati making it difficult to create mutually exclusive categories.

Way ahead:

• India has nearly three years before the Census of 2021 and also has data from the SECC and technologies rooted in machine learning at its disposal.
• It would be possible to set up an expert group that uses the SECC data in conjunction with other data sources such as matrimonial advertisements and State-specific
• Scheduled Castes/OBC lists to make a comprehensive list of castes and condense them into meaningful categories via machine learning tools.
• These categories could then be validated by domain experts from the Indian Council of Social Science Research (ICSSR) institutions in various States to come up with a district specific list of castes that would cover more than 90% of individuals in any given district.
• Interviewers could use this precoded list to allow respondents to self-classify with a small residual group’s responses being recorded verbatim and categorised later.
• It will take courage for a future government to collect data on caste and to use it to rationalise reservation policies. However, without better and more current data, our discourse on caste and affirmative action remains dominated by decisions made by the colonial administration.