Caste Calculus Swings Vote in Bihar Polls: A Complex Web of Alliances
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Caste continues to be a dominant force in Indian politics, with Bihar being no exception. The state's electoral history is marked by periods where specific castes have held sway, with the upper castes, backward classes, and extremely backward classes each having their turns in power. In the recent polls, the National Democratic Alliance (NDA) focused on the 110-odd castes that make up the extremely backward classes (EBCs), while the Bharatiya Janata Party (BJP) targeted the numerically smaller but prosperous upper castes. The Lok Janshakti Party and the Hindustani Awam Morcha balanced between their potent Dalit vote bases and general caste candidates. In contrast, the Opposition Grand Alliance's strategy centered on chemistry, with the Rashtriya Janata Dal (RJD) giving a lion's share of tickets to backward class candidates, primarily Yadavs. The Congress attempted to strike a balance between general castes, scheduled castes, and Muslims. However, the RJD's decision to project Vikassheel Insaan Party chief Mukesh Sahni as the surprise pick for deputy chief minister backfired, as EBCs are not a monolithic community. The results showed a complete polarisation on caste lines, with almost every community except Yadavs and a section of Muslims abandoning the Grand Alliance. The Opposition won just four of the 38 SC-reserved seats in the state, down from 17 in 2020. For the first time in almost 40 years, Yadavs are not likely to be the single-largest sub-caste in the Bihar assembly. The outcome highlights three key points: Tejashwi Yadav's failure to expand his party's base beyond the dominant Yadavs, Nitish Kumar's continued goodwill among smaller groups, and the need for a campaign to focus on material issues rather than simply appealing to marginalized castes. In 2025, the Constitution reflected the real concerns of the hinterland around jobs, education, and intergenerational mobility, but the Grand Alliance's campaign failed to address these concerns effectively.
