Is the caste Census a useful exercise?

Syllabus: GS2/ Polity and Governance

Context

• The demand for a caste Census has gained momentum with support from political parties, NGOs, and organizations like the Rashtriya Swayamsevak Sangh (RSS). 

What is a Caste Census?

• A caste Census involves collecting data on the population size and socio-economic conditions of various caste groups. 
• Advocates believe it can be instrumental in providing equitable distribution of government jobs, land, and other resources based on caste proportions.

Historical Background

• First detailed caste Census conducted in 1871-72 across major regions like Bengal and Madras.
  • However arbitrary classification led to confusion, as noted by W. Chichele Plowden in the 1881 Census report.
• 1931 Caste Census: It identified 4,147 castes, exposing challenges like different identities claimed by the same caste in different regions.
• Post-Independence: 2011 Socio-Economic and Caste Census (SECC) identified over 46.7 lakh castes/sub-castes with significant errors.

Imperatives for a Caste Census

• Understanding Demographic Realities: It helps policymakers identify gaps in resource allocation and ensure targeted interventions.
• Revisiting Reservation Policies: Existing reservation policies are based on outdated data from the 1931 Census.
  • A fresh caste Census can rationalize and update the quota system, ensuring fairness and proportional representation.
• Empowering Marginalized Groups: Recognizes the presence of underrepresented castes and sub-castes in political and economic structures.
• Political Representation: Accurate caste data can guide delimitation of constituencies and ensure equitable representation in legislative bodies.

Challenges to Accurate Data Collection

• Upward Caste Mobility Claims: Respondents claim higher social status due to the prestige associated with certain castes. Between the 1921 and 1931 Censuses, some groups reclassified themselves as higher castes.
• Downward Caste Mobility Claims: Post-independence, benefits of reservation policies have encouraged some to report themselves as belonging to lower social categories.
• Caste Misclassification: Similar-sounding surnames across regions often result in errors. Such inaccuracies lead to misrepresentation and inequitable resource allocation.
• Multiplicity of Caste Claims Within Communities: Communities with the same name may claim different varna or caste identities across regions.
  • Example: Sonars in one region identified as Kshatriya or Rajput, while in another, they identified as Brahmin or Vaishya.
• Enumerators’ Subjectivity: Census officials inadvertently misclassify respondents due to lack of knowledge or preconceived notions about caste hierarchies.
  • Example: During the Bihar caste Census in 2022, controversies arose over the inclusion of ambiguous categories like ‘hijra’ and ‘kinnar’ in caste classifications.

Way Ahead

• Establish a robust and transparent framework to conduct the caste Census, incorporating technological solutions like AI and machine learning for data accuracy.
• Conduct awareness campaigns to educate respondents about the importance of providing accurate information.
• Standardize caste categorization across states to resolve confusion over similar-sounding surnames and overlapping identities.
• Introduce mechanisms for periodic review and validation of collected data to correct inaccuracies over time.

Source: TH