Can caste data strengthen evidence-based reservation policy without deepening caste identities? Critically analyse.

Census 2027 will be the first Census since Independence to count caste for every person, not just SCs and STs. The Cabinet Committee on Political Affairs approved this on 30 April 2025 [1]. Caste data can make reservation policy sharper. Whether it can do that without hardening caste identities depends on how it is collected and used.

How caste data strengthens reservation policy

• Ends reliance on 1931 data: OBC estimates still go back to the last full caste count, in 1931. Current numbers would let lists be reviewed against evidence under Articles 15(4), 16(4) and 340.
• Fairness within the OBC group: Sub-categorisation (the Rohini Commission's mandate) needs caste-wise data to find the groups that take most of the benefits.
• Passing judicial scrutiny: Courts ask for quantifiable data to justify quotas. Maharashtra's 2021 case showed that states cannot proceed without usable OBC figures [2].
• Exit as well as entry: Data supports the creamy-layer rule and allows advanced castes to graduate out of the lists, which arguments based only on identity cannot do.

How it may deepen identities or fail

• Competitive mobilisation: Counting caste invites demands for inclusion and bigger shares. That puts pressure on the 50% ceiling set in Indra Sawhney (1992).
• Poor method: SECC 2011's open caste field produced about 46 lakh caste, sub-caste and surname entries [3]. In Maharashtra alone, about 4.28 lakh names were recorded against just 494 listed castes, and the Centre called the data unusable [2]. Census 2027 again uses an open column for non-SC/ST respondents. OBC groups are protesting and want unique codes for every caste [4].
• Trust deficit: SECC caste data is still unpublished a decade later [2]. Slow coding done behind closed doors breeds suspicion, and suspicion feeds identity politics.
• Narrow lens: Caste alone misses overlapping deprivation of gender, region and income.

Safeguards

• The Registrar General should publish a caste-coding dictionary before the count, not sort names afterwards as SECC did [3].
• State Backward Classes Commissions should check how local names map to codes.
• Data should be released on a fixed timeline and linked to socio-economic indicators.

Overall, caste data can largely strengthen reservation policy, provided the method is open, the coding is agreed in advance and the data is used to target benefits rather than to rally groups. Counting caste in order to move beyond it fits the Directive Principles (Articles 38, 46) and SDG 10. The aim is substantive equality, not permanent caste labels.