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The social composition of Bihar election candidates | Number Theory

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Updated on: Oct 29, 2025, 08:41:05 IST
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The first of this two-part series gave a broad social overview of Bihar’s caste composition and the caste composition of NDA and MGB (Mahagatbandhan) candidates based on a database prepared by the first author of this story. This part will offer more granular details of caste composition of candidature of parties within alliances and sub-castes within broad social groups and also the caste-wise contests at the AC level.

A voter awareness message by ECI in Patna. (PTI)
A voter awareness message by ECI in Patna. (PTI)
The social composition of Bihar election candidates
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    Among the major alliance partners, BJP and RJD have fielded the largest number of upper caste and BC candidates
    49 out of the 101 candidates fielded by the BJP are Hindu non-SC-ST-OBC or the upper castes. For the RJD, 76 out of its 144 candidates are from the backward classes (BCs). RJD has also put up the highest number of Muslim candidates among parties which are either in the NDA or MGB. Janata Dal (United) or JD (U) has put up the highest number of Extremely Backward Class (EBC) candidates. The three communist parties which are a part of the MGB, taken together, have the lowest share of upper caste candidates among alliance partners in either of the alliances that are contesting at least five seats. Two of NDA’s partners, the Lok Janshakti Party (LJP) and the Hindustani Awam Morcha (Secular) or HAM(S), both of which are led by Dalits, have a much higher share of upper caste candidates.
  • Listicle image
    At the sub-caste level, Bhumihars have the highest proportionate representation, closely followed by Rajputs
    Broad social categories have always meant very little in a polity as fragmented as Bihar. In the immediate aftermath of independence, caste-rivalry took the form of Bhumihar versus Rajput in the intra-Congress factional fight between Shrikrishna Singh and Anugrah Narayan Singh. For the last three-and-half decades, the political competition has been between two backward class leaders from Yadav (Lalu Yadav) and Kurmi (Nitish Kumar) sub-castes. This makes it important to look at candidates at the sub-caste level. An HT analysis of this data along with the respective share of castes in the state’s population from the 2023 caste-survey shows that Bhumihars and Rajputs, two historically land-owning castes, have the highest proportionate representation among NDA and MGB candidates. While the number of Yadav candidates is the largest for a single sub-caste, their relative advantage is not as high given the fact that they also have a much larger share in population (14.26%) than Bhumihars (2.87%) or Rajputs (3.45%). These numbers suggest that upper castes still hold a lot of clout in the state’s politics, which could very well be a derivative of the necessary socio-economic clout needed to contest an election rather than just the number of voters of their own sub-caste.
  • Listicle image
    RJD has given most seats to Yadavs; BJP leads in Rajputs, Bhumihars, Brahmins; JD(U) has fielded most Kurmis
    53 out of the 88 Yadav candidates from either MGB or NDA are from the RJD. The BJP, on the other hand has fielded more upper caste candidates – Bhumihars, Brahmins, Rajputs and Kayasths – than the RJD and the JD(U) put together, the other two major parties in the state. Because the BJP has not fielded any Muslim candidates, it has also been able to accommodate more EBC sub-caste candidates than the other major parties. The JD(U) has fielded 14 out of the 19 Kurmi candidates in the state.
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    Decoding the caste-wise contest in Bihar
    Bihar’s political history and even the wider narrative around Mandal politics lends itself to the stereotype of electoral politics being some sort of an upper caste versus lower caste struggle. A granular examination of the caste-wise alliance-wise contest matrix in Bihar cautions that one should stay clear of such sweeping generalisations. HT has drawn up such a matrix for 227 ACs in Bihar which excludes 16 ACs where nominations of either the NDA or MGB candidates were cancelled or the MGB has more than one candidate. 36 out of these ACs will see the same social-group contest by default because they are reserved for either SCs or STs. In the remaining 191 ACs, 83 will see a contest between candidates from the same broad social group (upper caste versus upper caste, BC versus BC, EBC versus EBC etc). 25 out of the 108 ACs which have a candidate from divergent social groups are places where the MGB has fielded a Muslim but the NDA has a Hindu. Even at the sub-caste level, 63 out of the 227 ACs analysed here will see a contest between candidates from the same sub-caste, which underlines politics as an exercise in competing ambitions rather than some wider social conflict.
  • Nishant Ranjan
    ABOUT THE AUTHOR
    Nishant Ranjan

    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.Read More

  • Roshan Kishore
    ABOUT THE AUTHOR
    Roshan Kishore

    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.Read More

  • Abhishek Jha
    ABOUT THE AUTHOR
    Abhishek Jha

    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.Read More

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