Opinion | Reimagining Caste Census As A Bottom-up Tool For Social Architecture
Rather than treating the caste census as a battlefield between competing political visions, we could reimagine it as a collaborative platform for continuous social learning
The heated debates surrounding India’s caste census often get trapped in binary narratives: necessary accountability, participation and representation versus divisive politics. But what if we’re missing the forest for the trees? Can the caste census be reimagined to be something more than its traditional, statistical function, to become something transformative?
Could it instead become a dynamic platform for social architecture rather than merely a snapshot of inequality?
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Census as a Mirror, Not Just a Measurement
Most discussions frame the caste census as either a harsh mirror exposing uncomfortable truths or a dangerous tool reviving old wounds. Both perspectives treat the census as a passive instrument. But censuses throughout history have never been neutral; they actively shape the societies they measure.
When British colonial administrators conducted the first comprehensive caste census in 1871, they weren’t merely documenting existing social structures — they were crystallising fluid social categories into rigid administrative classifications. The census didn’t just count; it consolidated modern caste identity as we understand it today.
Historian Nicholas Dirks documents how many communities actively petitioned census authorities to be classified into higher castes, recognising that categorisation would determine their access to resources and standing. The census wasn’t passive; it became a battleground for social positioning that continues to this day.
From Demographic Tool to Digital Platform
What if we reimagined the caste census for the digital age? Rather than conducting it as an accounting exercise that is conducted once in a decade, it should function as a dynamic platform that continuously monitors social mobility patterns while protecting privacy and having other security safeguards.
Consider a longitudinal approach that tracks not just where communities are positioned now, but how they’re moving through educational and economic systems over time. The traditional census freezes communities in time; a dynamic platform could highlight the velocity of change — or its absence.
A 2019 study by economists from the Indian Statistical Institute revealed that the rate of intergenerational mobility for Scheduled Castes in professional occupations increased from 0.4 to 0.67 between 1983 and 2012. This is a significant shift that static census data would miss. Yet this progress remains dramatically lower than the 0.82 rate for upper castes. This points to persistent structural barriers.
Hyperlocal Targeting Rather Than Broad Categorisation
The conventional wisdom treats castes as monolithic blocks, but reality shows staggering internal variation. The Indian Human Development Survey found that the standard deviation of household income within many caste groups exceeds the differences between caste averages — suggesting that treating castes as uniform entities misses critical variations.
A caste census needs to be forward-thinking. The need of the hour is that it should operate at a decentralised, local level. It should help identify specific geographical pockets where particular communities face acute marginalisation. This would enable targeted interventions rather than broad-brush policies.
Paradox of Recognition: Fluid Identities in Fixed Categories
One of the most fascinating contradictions of the caste census is what sociologists call the “paradox of recognition" — to address discrimination against a group, you must first officially recognise and classify that group, potentially reinforcing the very categories you hope to dismantle.
An innovative approach would be implementing what I call “sunset provisions" on caste categories — explicitly designed to evolve or dissolve as specific socioeconomic indicators change. This would shift the focus from permanent identity-based reservations to outcome-oriented interventions with clear success metrics.
Denmark’s approach to socioeconomic data collection offers an instructive parallel – they track disadvantaged populations through multiple intersecting factors rather than fixed identity categories, allowing their classification system to evolve as disadvantages shift across generations.
Beyond Quotas: From Redistributive Justice to Market Design
The debate around caste census often fixates on reservation percentages, but this frame is increasingly outdated in a liberalised economy where private sector opportunities dominate. What if we used caste census data to design markets themselves?
Recent work in economic mechanism design shows how properly structured markets can overcome historical disadvantages without explicit quotas. For instance, the admissions mechanism for certain programs in universities can be redesigned using techniques from matching theory to check if diversity outcomes can be increased without changing formal reservation percentages.
The census could identify specific market failures where caste discrimination remains most acute — sectors where equally qualified candidates face differential outcomes — and design targeted interventions for those domains rather than applying uniform approaches across vastly different contexts.
The Uncounted: New Dimensions of Exclusion
Traditional caste analysis focuses on vertical hierarchies, but contemporary India has developed complex new dimensions of exclusion that evade conventional categories. A modern caste census must capture how urbanisation, migration, and digitalisation have created new vulnerabilities.
For example, research reveals that interstate migrants frequently experience forms of exclusion that don’t map neatly onto traditional caste categories. When Bihari migrants in Maharashtra reported discrimination, the census would miss this interregional dynamic if focused only on conventional caste classifications.
Similarly, the digital divide has created new hierarchies of access. Studies have found that digital literacy varies dramatically within the same caste groups based on geography and economic factors. Simple caste categories will fail to capture these complex patterns of advantage and disadvantage.
The Census as Conversation
The census should now evolve from a bureaucratic exercise, that is conducted in a top-down, paternalistic manner, into a participatory process where communities have an effective say in how it is conducted, and can actively engage in defining the categories and questions that matter to them.
When Brazil experimented with participatory census design in certain regions, they discovered significant differences between official categories and how communities understood their own identities. The resulting data proved far more predictive of actual socioeconomic outcomes than traditional approaches.
An interactive census platform could allow communities to contribute their perspectives while maintaining methodological rigor – creating not just more accurate data but fostering dialogue about how identity categories themselves should evolve in a rapidly changing society.
An Unknown Future Requires Adaptive Tools
The caste system has proven remarkably adaptive over centuries, shifting from ritual hierarchies to economic stratification to digital-age manifestations. Our measurement tools must be equally adaptive.
Rather than treating the caste census as a battlefield between competing political visions, we could reimagine it as a collaborative platform for continuous social learning — one that acknowledges the persistence of inequality while treating identity categories as changing features of the social landscape.
The most promising path forward might be designing a census explicitly aimed at its own obsolescence — one that succeeds when the categories it measures cease to determine life outcomes in India. That would be a truly radical reimagining of what a caste census could become: not just a counting of what is, but a catalyst for what might be.
Arindam Goswami is a research associate at Takshashila Institution, Bengaluru. The views expressed in the above piece are personal and solely those of the authors. They do not necessarily reflect News18’s views.
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