Mains Marathon

Approach :

• Briefly introduce the definition of caste and caste-based census in India.
• Examine the merits and demerits of conducting a caste-based census in India.
• Suggest a balanced way forward.

Introduction :

M.N. Srinivas, the eminent Indian sociologist, defines caste as a hereditary, endogamous, and typically localized social group, traditionally associated with a specific occupation and placed within a defined hierarchical order. A caste census refers to the systematic collection of data on individuals’ caste affiliations during a national population enumeration. Recently, the Indian government has approved the inclusion of caste-based enumeration in the postponed Census 2021, thereby reviving a practice that had been discontinued post-independence.

Body:

Merits of a Caste-Based Census

• Current Data Gap: While data exists for SCs and STs, there is no reliable, updated national data on OBCs and other caste groups, hindering effective policy formulation.
• Addressing Challenges from Previous Surveys: The 2011 Socio-Economic and Caste Census (SECC) in India faced significant criticism due to the lack of a comprehensive and standardized caste list, leading to a multitude of issues during data collection and analysis
  • The upcoming caste census aims to address these issues by ensuring a more accurate and inclusive process.
• Constitutional Mandate and Legal Rationale: A caste census aligns with Articles 15(4), 16(4), and 340, which provide for special provisions for socially and educationally backward classes.
  • The Supreme Court (Indra Sawhney judgment, 1992) upheld caste as a relevant factor in determining backwardness.
• Reshaping Affirmative Action: The caste census can provide updated data to reassess reservation quotas and affirmative action programs.
  • The absence of caste data has left OBC population estimates unclear; the last available data from the 1931 Census showed OBCs at 52%, which influenced the Mandal Commission’s 1980 reservation recommendations.
  • Bihar's 2023 caste survey found OBCs and EBCs make up over 63% of the state's population, fueling calls for national-level caste data to guide policy decisions on reservations and social welfare.
• Sub-Categorization Within Broad Groups: Detailed data enables the sub-categorization of OBCs, as recommended by the Rohini Commission (2017), to ensure equitable distribution of reservation benefits.
• Political and Electoral Implications: Accurate caste data can lead to better political representation of marginalized groups, especially in state and national elections.

Demerits of a Caste-Based Census

• Reinforcement of Caste Identities: Critics argue that caste enumeration may re-legitimize caste divisions, contradicting long-term goals of caste annihilation.
  • May institutionalize caste consciousness in public life rather than diminish it
• Political Exploitation and Competitive Backwardness: Accurate caste data may fuel vote-bank politics, with parties tailoring policies for electoral gain.
  • It could trigger demands for OBC/ST/SC status by politically dominant or upper caste groups, increasing pressures on reservation quotas.
  • May lead to "competitive backwardness", where groups seek lower status for benefits.
• Data Challenges and Accuracy Concerns: The SECC 2011 revealed 46 lakh caste categories due to spelling errors and unverified entries—making it unusable for policymaking.
  • Ensuring data standardization, verification, and transparency is a logistical and administrative challenge.
• Issues with Proportional Representation: Fresh caste data may challenge policies based on 1931 estimates, triggering demands for proportionate reservations and calls to revise the 51% cap set by the Indra Sawhney judgment, 1992.
• Risk to Social Cohesion
  • Groups not adequately represented or excluded may feel alienated.
  • It could aggravate tensions between reserved and non-reserved categories, as seen in the Maratha and Patidar agitations.

Way Forward

• A comprehensive caste list should be prepared by the Registrar General of India through extensive consultations with academics, civil society, caste groups, political parties and the common public.
• Community-level oversight should be involved for local validation and public trust.
• Integrate Aadhaar to reduce duplication and enhance identity verification.
• Employ Artificial Intelligence (AI) and Machine Learning (ML) to ensure accurate classification, data sorting, and pattern recognition.
• Implement the Justice Rohini Commission's recommendations to sub-categorize OBCs.
• Supplement caste data with Multidimensional Poverty Index (MPI) and social indicators.
• Allow states the autonomy to design welfare schemes tailored to their unique caste-demographic profiles.
• Use the caste census as a developmental tool, not for vote-bank politics.
• Create a transparent grievance redressal mechanism for caste-related disputes.

Conclusion

• As sociologist Andre Béteille cautioned, “while caste may be a necessary category for governance, it must not become the sole lens for citizenship.” In line with SDG 10 (Reduced Inequalities) and SDG 16 (Peace, Justice and Strong Institutions), a caste census must aim to foster equity without deepening divisions. The goal should be data-informed development, not data-driven divisiveness.