The gazette notification for the personal enumeration part of the 2027 Census was issued on August 14. The most awaited part of this phase of the Census is the caste enumeration that will happen for the first time in independent India. This practice was a part of Census operations under British rule but was discontinued. To be sure, the Census has been counting the Scheduled Caste (SC) and Scheduled Tribe (ST) population separately even in earlier iterations. What was not
- The gazette notification does not list OBCs as a category separatelyItem number 10 in the Household Schedule which was notified on August 14 talks about caste. The exact entry is “Scheduled Caste (SC)/ Scheduled Tribe (ST)/Caste”. We will know more when the exact questionnaire is released when the self-enumeration exercise starts in Ladakh and snow bound areas of Jammu and Kashmir, Himachal Pradesh and Uttarakhand on August 17. However, it is useful to compare how the latest Census seeks information about caste with its predecessor. The 2011 Census asked two related questions on caste: first to ascertain whether a person belonged to an SC or ST group; and second, the enumerator was instructed to “write name of SC or ST from the list supplied”. What the 2027 Census way of recording caste resembles is how the 2011 Socio Economic Caste Census tried to do it. The 2011 SECC questionnaire asked two questions on caste: first, to ascertain whether a person was from an SC/ST/Other caste; and second, to record the caste name (no list was mentioned). The SECC caste data was never published officially. Neither the SECC nor the 2027 Census schedule mentions OBCs separately.
- The challenge of listing OBC sub-castesDoes the 2027 Census have a list of all sub-castes in India? It is difficult to answer this question with confidence. And at least for official purposes there might not exist a universal list on this count. However, the Indian state does have a comprehensive list of OBCs at two levels: central list of OBCs and lists maintained by various states. Unlike SC/ST groups, whose recognition as such requires central government and the parliament’s approval, states can notify sub-castes as OBCs on their own. As of now, there are 2,479 entries in the central list of OBCs. This number can be greater as a sum of states. For example, Tamil Nadu has 182 entries for OBCs in the Central list whereas the state government of Tamil Nadu has recognized 252 such entries in the state list. The Mandal Commission report, which forms the basis of the OBC reservations in India, recognised 3,743 communities as OBCs.
- Unless the Census comes up with granular data on sub-castes, it might not be very illuminating compared to what we already knowThis is the most important part. While the census has not been counting the OBC and non-SC-ST-OBC population separately, there exist government surveys which give us an estimate of the broad composition of the population on this count. The NFHS conducted in 2019-21 put the broad population share of SC-ST-OBC-Other population at 22%-9%-42%-27%. The PLFS conducted in 2025 puts the distribution at a similar 20%-9%-46%-24%. The experience from Bihar caste census, the results of which were published in 2023, suggest that the NSSO/NFHS numbers were not very off the mark.
- Herein lies the dilemma which also characterised the debate around the caste census before it was made a part of the ongoing census. If the objective was to prove conclusively in census numbers that OBCs do have a population share of close to half in India’s population, then the non-inclusion of a separate OBC category should have triggered protests. This does not seem to be happening as of now. If the aim was to study intra-group caste inequality – survey data once again shows this clearly but not on a sub-caste basis – then one might have to wait for the publication of the data to see what exactly comes out of the Census. Of course, unlike survey data, the government has never published granular details of Census data even before the debate around counting caste.
Roshan Kishore is the Data and Political Economy Editor at Hindustan Times. He heads the newsroom's data journalism team, which produces Number Theory, a daily data-driven feature for the print edition and the HT app. Number Theory uses data analysis and story-telling based on it to add value to the newsroom’s daily coverage by putting stories in a larger context on a range of issues, including politics, macroeconomy, markets, global affairs and climate. Under his leadership HT’s data journalism work has established itself as a niche product in Indian journalism and pushed the boundaries of marrying academic rigour with news sense and speed. Along with writing and editing data stories, he has also been writing a weekly political economy column called Terms of Trade for HT Premium. A trained economist with an MPhil degree from Jawaharlal Nehru University, Kishore has also been a visiting fellow at the Centre for Advanced Studies of India (CASI) at the University of Pennsylvania. Along with his journalistic work, his writings have also appeared in journals such as the Economic and Political Weekly and working papers for CASI and UNESCAP.
Abhishek Jha is Assistant Editor-Data at Hindustan Times. He uses statistical programming to generate newsworthy insights from large datasets. He is part of the team that produces Number Theory, a daily data story feature of the paper’s print edition. Since March 2024, he has been writing Weather Bee, a weekly column for the Hindustan Times website. He is a chemical engineer by training, who specialises in stories related to weather, climate, and the environment. Jha has been at HT since 2018, where he offers data-driven perspective and analysis on politics, environment, weather, climate, economy and society. His work includes data coverage of elections in India and abroad, including the 2019 and 2024 Lok Sabha elections; the disasters and extreme weather resulting from changing climate, such as floods, droughts, heat waves, cold waves, and dwindling snow cap in the Himalayas; the factors that drive poor air quality in northern India; the changing patterns of land use; the Covid-19 pandemic and its impact on labour market conditions; the changing pattern of consumer spending seen in the new consumer spending surveys; and social norms seen in the surveys such as the National Family Health Survey.
Nishant Ranjan has been working as a data journalist with Hindustan Times since 2023. In this short period, he has established a niche for creating original datasets and utilising them to produce journalistic work that pushes the boundaries of journalism. The list of datasets and stories done by him include the following: a dataset of all 717 chief ministers India has had since 1952, a dataset of all 3,350 members of India’s council of ministers, a dataset of all 190 deputy chief ministers in India and a dataset of all 279 Supreme Court judges in India (1950-2025). He has also profiled each elected Muslim MLA/MP since 1952. He is a mining engineer by training who decided to pursue a Master's in Development Studies from TISS after working in a coal mine for 10 months. He also worked as a research associate at the Centre for Policy Research, researching local governance in India. He also has a keen interest in analyzing electoral politics and political executives in India.