When lack of data gets in the way of affirmative action
PremiumInformation inadequacies should not hamper the country’s reservation programme
March 2022 saw two important court judgements on reservation policies in two different Indian states, with one common link. In Maharashtra, the state government had carved out a separate 27% Other Backward Classes (OBC) quota in local body elections. This was struck down by the Supreme Court, since it did not meet the mandatory triple test laid down by the court. Specifically, the court cited a lack of rigorous empirical study and research for the state’s decision on this OBC quota.
In Tamil Nadu, the state assembly had passed a bill providing internal reservations of 10.5% for the Vanniyar community (of Vanniakula Kshatriyas) in jobs and education (bit.ly/3JEL2cM). The Supreme Court struck this down as well, saying that there is no substantial basis for this legislative action aimed at providing a quota specifically for a single OBC community. This same case was first decided by the Madras high court, which had stated that “the enactment was passed by the state without any quantifiable data" and without any objective criterion (bit.ly/3JyziZh). This is the core problem that was identified by both these judgements: a lack of evidence-driven policymaking for reservations.
A common problem of wide divergences: While reservations are applicable all across India, it is no secret that there are wide state-level differences across many parameters. For example, about 55% of Maharashtra’s population is eligible for reservations, as most of the state’s people are classified as Scheduled Caste, Scheduled Tribe or OBC, while in Tamil Nadu, a much higher 97.2% of the state population is classified likewise.
Now, OBCs constitute about 33.8% of Maharashtra’s population, whereas in Tamil Nadu, a whopping 76% of the population is classified as OBC, though this vast group of people is further divided (bit.ly/3xlcQjO) into Most Backward Classes (MBCs), Backward Classes (BCs), Backward Class Muslims (BCMs) and Denotified Communities (DNCs). Further, in Maharashtra, the total number of seats reserved for OBC/SC/ST candidates is capped at 50%, as per a directive of India’s top court in the Indra Sawhney case. However, in Tamil Nadu, a much higher 69% of seats fall under the reserved category, which is clearly an exception to that Supreme Court ruling. In fact, half the seats in Tamil Nadu are reserved solely for OBC candidates.
Despite these varied approaches towards reservations and the country’s tremendous multi-decade investment in affirmative action, a lack of reliable caste-level data remains a constant factor that hampers improvements of the programme.
We must collect the right data: Reservations were designed for impact at the caste level. Their impact is easier to assess at a group level, whether it is OBCs, SCs or STs. However, whether individual castes within those groups have benefitted or not remains unclear.
As per the Rohini Commission report, over 1,000 OBC caste groups have not received any benefit whatsoever from India’s reservation programme (bit.ly/3uxiAFf), signifying a huge imbalance in the distribution of its benefits.
The country’s lack of targeted data collection around reservations remains a major miss, which makes space for an imbalance between caste groups in access to opportunities. Thus, there is a dire need to collect the right data at the caste level to make the reservation system more effective. Doing so would not only help us understand the population of each group, but also their socioeconomic and political backwardness and the benefits that have accrued from reservations so far.
What data to collect? The government already captures the OBC/SC/ST status of individuals at the school level. However, this needs to filter further down to the level of caste identity (bit.ly/3O69WW7).
This would allow us to easily estimate the population levels of each caste group. Further, this would also allow us to review the proportion of students attending government schools from each caste group, which in turn would offer us a peek into relative levels of deprivation between different castes.
The proliferation of affirmative action: Hundreds of government schemes today are administered for OBCs, SCs, and STs across the country, through both the Central and state governments. Capturing the specific caste data of these beneficiaries, especially of welfare schemes like those in place for food distribution and jobs under the Mahatma Gandhi National Rural Employment Guarantee Act, would help us understand the proportion of each group that’s forced to avail of these benefits.
Many state governments are running a digitization programme for caste certificates (bit.ly/3xjkifa) . By linking this data with Aadhaar, a database can be created to track reservation benefits across all castes.
The two recent Supreme Court judgements have shown the dire need to build evidence for furthering the cause of social justice. Capturing appropriate data holds the key to building this evidence, which should include measurements of the impact of reservations at the caste and community level, and not merely at a group level.
State and central governments have been quick to implement digitization in many fields. These administrations should show the same vigour in the reservation programme by creating a robust data-backed evidence architecture for assessing and implementing affirmative action.
Omkar Sathe & Sahil Deo are, respectively, associate partner and co-founder of CPC Analytics