Implications of Caste-Census

What is the issue?

• With 2021 census approaching, the debate around having caste-based census has come up.
• It is essential to understand the implications that caste statistics would have in the country.

What was caste census's role in colonial times?

• Census of 1931 provides, to date, any information regarding the size and characteristics of various castes in India.
• Colonial Censuses, beginning with the first Census in 1871, included questions about caste.
• This generated an idea of homogeneous and classifiable community.
• It was used to divide and conquer India.
• This was done by first privileging Brahmins as interpreters of Indian culture.
• Slowly they were targeted as the roots of caste-based oppression and inequality.
• This classification was also a source of anti-Brahmin movements of 20th century.
• It thereby influenced the processes of political representation.

How does caste census impact society?

• Society - There are apprehensions that caste based census would further promote:

1. Caste-based political mobilisation
2. strong sentiments for or against reservations

• Post-Independence Censuses have thus shied away from including questions about caste.
• However, Patels, Gujjars, Jats and Marathas do not seem to care about the lack of Census data as they demand reservations.
• Also, even without caste census, caste does play a role in elections in terms of vote banks.

Does caste census play a role in economy?

• Caste data from 1931 Census and a few special purpose surveys define certain categories.
• They include Dalits, Adivasis, OBCs and upper castes.
• It is assumed these broad caste-based social categories continue to shape economic conditions in 21st century India.
• However, each of these categories consists of thousands of jatis (castes) and upjatis (subcastes).
• Hence, without accurate data for each of these, the claim that it shapes economic conditions is baseless.
• Also, the society and economy, since 1931 census, has undergone various changes, crossing these caste boundaries.

What are the transformations since 1931?

• Land - Land ownership that perpetuated the power of upper castes has lost its hold.
• Land fragmentation and agricultural stagnation have turned many upper caste landowners into marginal farmers.
• Besides, rising rural wages, particularly construction wages, has made the landless better.
• Poverty - Broadly, mean consumption expenditure of forward castes is higher than that of Dalits.
• However, clusters of poverty persist among forward castes also, as per National Sample Survey (NSS).
• The bottom fourth of forward castes are poorer than the top half of Dalits.
• Education - India Human Development Survey shows that 56% of Dalit children aged 8-11 cannot read.
• But this is also the case with 32% of forward caste and 47% of OBC children.
• Overall, some jatis have managed to pull themselves out of poverty and marginalisation.
• While other groups have had a deterioration in their status.

What is the need for caste census?

• Economic growth and affirmative action by governments have changed relative fortunes of various groups.
• Hence, it is time to collect data that reflects the current situation.
• So the social apprehensions on implications of caste census are largely invalid.
• Without caste data, the discourse on caste and affirmative action are dominated by decisions made by the colonial administration.
• Collecting data on caste is now essential to rationalise the reservation policies.

• Challenges - Sometimes the same caste is spelt in different ways, or individuals report their jati and others upjati.
• This makes it difficult to create mutually exclusive categories.

What could the methodology be?

• There is nearly three years' time before the Census of 2021.
• Data from Socio-Economic Caste Census and technologies rooted in machine learning are at disposal.
• It would be possible to set up an expert group that uses the SECC data in conjunction with other data sources.
• Comprehensive list of castes can be made and condensed into meaningful categories via machine learning tools.
• These categories could then be validated by domain experts in various States.
• It can then be used to make a district specific list of castes that would cover more than 90% of individuals in any given district.
• Respondents can then be allowed to self-identify from the precoded list.
• The residual group’s responses recorded verbatim could be categorised later.
• This is very similar to the technique through which occupational and industrial classification systems are created.

Source: The Hindu