CASTE LISTING POSES MAJOR CENSUS CHALLENGE, EXPERTS WARN

GS-1: Indian Society

Key Points:
  • Experts highlight that compiling a definitive list of castes and communities will be the primary hurdle for caste enumeration in the upcoming Census.
  • India lacks a current, comprehensive caste database beyond constitutional SC, ST, and OBC lists.
  • The 1931 Census, the last to fully enumerate castes, recorded over 4,147 distinct groups.
  • The 2011 SECC failed to produce reliable caste data due to exaggerated responses and classification issues.
In-Depth Analysis: Existing Data Overview:
  • The Anthropological Survey of India’s People of India project (1992-1999) identified 4,635 communities, including numerous sub-castes.
  • Over 3,651 OBCs, 1,170 SCs, and 850 STs exist, but many are duplicated across states or listed under varying names.
Challenges in Enumeration:
  • No standardized caste list exists for enumerators.
  • The Registrar General of India must create a consolidated list through public consultations.
  • In the 2011 SECC, respondents provided over 46 lakh caste names based on surnames or social identity, rendering the data unusable.
Linguistic and Regional Complexities:
  • Enumerators must navigate regional naming variations and linguistic differences within communities.
  • Communities may self-identify inconsistently, complicating classification.
Classification Challenges:
  • Post-enumeration, grouping castes into categories is difficult.
  • The 1931 Census struggled to classify groups, often listing them under overlapping categories like caste, tribe, or race.
Scientific/Technical Terms:
  • Census Enumeration: A systematic process to collect socio-demographic data.
  • SECC: A 2011 initiative to gather caste and economic data, though its caste findings were not officially released.
Significance:
  • Accurate caste enumeration could enable data-driven affirmative action, social justice initiatives, and targeted welfare programs.
  • Without methodological rigor, the process risks becoming politicized or statistically flawed.

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