India’s 2021 Census: Caste enumeration revival exposes colonial legacies and neoliberal demographic anxieties

Indigenous and Dalit scholars critique caste enumeration as a colonial construct that reifies hierarchical social categories, arguing that community-based knowledge systems (e.g., oral histories, kinship networks) offer more nuanced understandings of social stratification. The revival of caste data collection ignores how Adivasi communities, who often reject caste labels, are further marginalized by state-imposed classifications. Traditional knowledge systems in India, such as those documented by the 'People’s Linguistic Survey of India,' reveal how language and caste intersect in ways that challenge bureaucratic enumeration.

The 1931 Census’s caste enumeration under British rule was the first to record 'Depressed Classes' separately, embedding caste into administrative structures and fueling communal politics. The 1901 Census, led by Herbert Risley, used anthropometric measurements to 'scientifically' classify castes, a practice later discredited but whose legacy persists in modern data collection. Post-independence India abandoned caste enumeration until 2011, when the UPA government reintroduced it—only to be stalled by political and logistical hurdles, reflecting deeper tensions over social justice and state power.

In Rwanda, post-genocide censuses avoided ethnic enumeration to prevent reification of divisions, opting instead for geographic and occupational data—highlighting how cultural memory shapes demographic methodologies. Brazil’s IBGE census includes 'race' categories but has faced criticism for reinforcing racial binaries that obscure Afro-Brazilian cultural diversity. Japan’s post-war census used occupation-based classifications to track social mobility, reflecting its unique historical relationship with class and caste-like structures.

Caste enumeration in India lacks a clear scientific consensus on its methodology, with critics arguing that genetic studies (e.g., the 2009 'Indian Genome Variation Consortium') undermine the biological validity of caste categories. Demographers like Christophe Guilmoto highlight how caste data is often misused to project 'population explosions' in marginalised communities, ignoring structural factors like healthcare access and education. The Indian census’s reliance on self-identification for caste (unlike the British-era 'expert' classifications) introduces new biases, as respondents may underreport or overreport based on social pressures.

Dalit artists like Savi Savarkar use poetry and performance to critique how caste enumeration reduces complex social identities to bureaucratic categories, framing it as a form of epistemic violence. Spiritual traditions in India, such as the Bhakti movement, historically rejected caste hierarchies, offering a counter-narrative to state-led social classification. Indigenous Adivasi communities often view population counts as disruptive to their cyclical, community-centered understandings of time and space, contrasting with the linear, quantitative frameworks of the census.

If caste enumeration proceeds, future models may project 'caste-based population growth' to justify regressive policies, mirroring historical eugenics-era projections in the West. Alternative demographic models, such as those used by the 'Alternative Survey of India,' incorporate caste, class, and gender to predict social outcomes more accurately than state-led censuses. Scenario planning could explore how caste data might be used to design inclusive policies (e.g., targeted welfare) or to deepen social divisions, depending on political will.

Dalit and Adivasi activists argue that caste enumeration reinforces stigma and justifies exclusionary policies, while feminist scholars highlight how it ignores intersectional oppressions (e.g., caste-gender violence). Tribal communities in central India have protested census enumerations, citing harassment and misclassification by officials. Marginalised scholars like Gopal Guru and Sharmila Rege have long critiqued how caste data is weaponized against oppressed groups, calling for participatory enumeration methods.