Telangana’s Composite Backwardness Index

The Telangana government is introducing a Composite Backwardness Index (CBI) based on data from a caste survey covering over 3.5 crore residents. Developed by an expert panel, the index uses 42 indicators across nine categories to scientifically assess caste-wise backwardness, moving beyond population-based assumptions

Redefining Backwardness: From Demographics to Measurable Disparities

1. Evolution of Caste-Based Metrics in India

• Legacy Approach: Population as a Proxy for Backwardness
  • Traditionally, backwardness was inferred from population size, rooted in the assumption that numerically larger groups faced higher marginalisation.
  • This approach was exemplified in the Mandal Commission (1980s), which surveyed only 50 lakh individuals and used 11 indicators.
• Paradigm Shift: Emphasis on Empirical Multidimensional Data
  • The Telangana model focuses on how backward a caste is, not how many belong to it.
  • The first-of-its-kind index globally shifts from quantitative caste enumeration to qualitative deprivation analysis.

2. The Composite Backwardness Index (CBI): Methodology and Structure

• Survey Design and Scope
  • Over 5 crore respondents across Telangana participated in the survey.
  • 74 detailed questions captured socio-economic, educational, and discriminatory experiences.
• Statistical Framework
• The committee identified 42 statistically significant indicators across 9 categories, such as:
  • Education
  • Housing and Infrastructure
  • Income and Debt Dependency
  • Landholding
  • Technology Access
  • Experiences of Discrimination (e.g., in temples)
• Scoring and Ranking
  • Castes were assigned scores on a 0 to 126 scale.
  • Higher scores indicate greater backwardness.
  • Castes were placed in quartiles, enabling targeted affirmative action policies.

3. Institutional Mechanism and Expert Oversight

• The Expert Working Group is headed by Justice B. Sudarshan Reddy.
• Praveen Chakravarthy, convener and data economist, spearheaded the index’s technical design.

4. Implications for Social Justice and Policy-Making

• Scientific Redefinition of Affirmative Action
  • The index enables data-validated identification of socially and educationally backward classes (SEBCs).
  • Can help redesign reservation policies based on actual deprivation rather than perceived status.
• Disaggregated and Targeted Welfare Delivery
  • Helps eliminate intra-group inequality by distinguishing between relatively better-off and extremely backward sub-castes.
• Enabling Evidence-Based Governance
  • The move lays the foundation for federal-level caste census debates and re-ignites calls for data transparency in social justice metrics.

Way Forward

• Institutionalisation of the Index Nationwide: NITI Aayog and Ministry of Social Justice could consider national adaptation of the CBI for uniform affirmative action metrics.
• Legislative Backing and Judicial Endorsement: The use of the index for reservation and welfare allocation must be supported by legal frameworks and Supreme Court scrutiny to ensure constitutionality.
• Data Transparency with Privacy Safeguards: The government should release aggregated caste-wise data for academic and policy use while ensuring data privacy and anonymity.
• Periodic Updates and Dynamic Tracking: As socio-economic conditions evolve, the CBI should be updated periodically to reflect real-time conditions of caste-based deprivation.