Telangana SEEEPC Survey Reveals Caste Disparities
A detailed analysis shows SCs and STs are three times more backward than General Castes, highlighting urgent socio-economic issues in Telangana.
6 mins read
Introduction
India's caste-based welfare architecture has long suffered from one critical deficit: the absence of empirical, disaggregated data on degrees of backwardness across and within social groups. The Telangana SEEEPC Survey — covering 3.55 crore people across 242 castes — fills this void with the Composite Backwardness Index (CBI), producing the most granular state-level caste census data in independent India's history. Its core finding is unambiguous: SCs and STs are three times more backward than General Castes, and the hierarchy of deprivation runs deep even within each social group.
"Every backward caste is not equally backward — the CBI underscores the need for nuanced policies that address the hierarchy of backwardness, rather than treating social groups as monolithic categories." — Independent Expert Working Group (IEWG), Telangana
| Parameter | Data |
|---|---|
| Total population surveyed | 3.55 crore |
| Families covered | 1.12 crore |
| Castes surveyed | 242 |
| State weighted average CBI score | 81 |
| SC/ST backwardness vs. General Castes | 3.0–3.1× |
| BC backwardness vs. General Castes | 2.7× |
| People identifying as "casteless" | ~14 lakh (4%) |
Background & Context
- Survey: Socio-Economic, Educational, Employment, Political and Caste
(SEEEPC) Survey 2024, Telangana
- Analysed by: Independent Expert Working Group (IEWG)
- Report made public: April 2025 (uploaded in public domain)
- Coverage: 1.12 crore families; 3.55 crore people; 242 distinct castes
- Index: Composite Backwardness Index (CBI)
→ Higher score = greater backwardness
→ State weighted average CBI = 81
→ Dimensions: Education, Employment, Living Conditions,
Assets, Social Integration
- IEWG clarification: CBI is NOT intended to recommend caste
categorisation — it provides empirical evidence of backwardness
for nuanced, evidence-based policymaking.
Telangana's Caste Population Composition
| Social Group | % of State Population | Remarks |
|---|---|---|
| Backward Classes (BC) | 56.36% | Largest group; internally heterogeneous |
| Scheduled Castes (SC) | 17.42% | 97% more backward than State average |
| Scheduled Tribes (ST) | 10.43% | 99% more backward than State average |
| General/Other Castes | 15.79% | All 18 castes above State average |
| Identified as "casteless" | ~4% (14 lakh) | Among least backward in State |
Key Concepts
COMPOSITE BACKWARDNESS INDEX (CBI) — ARCHITECTURE
──────────────────────────────────────────────────────────────────────
State weighted average CBI score = 81 (benchmark)
ABOVE benchmark (less backward):
→ 107 castes = 33% of population
→ Includes: 64 BCs + 18 SCs + 7 STs + ALL 18 General Castes
BELOW benchmark (more backward):
→ 135 castes = 67% of population
→ Includes: 69 BCs + 41 SCs + 25 STs
Population share MORE backward than State average:
→ STs : 99% of ST population
→ SCs : 97% of SC population
→ BCs : 71% of BC population
→ GCs : 0% (all above average)
──────────────────────────────────────────────────────────────────────
Key insight: Being BC does not guarantee backwardness — 29% of BCs
are LESS backward than the State average. Policy must target the
backward within the backward, not the category as a whole.
RELATIVE BACKWARDNESS (vs. General Castes)
──────────────────────────────────────────────────────────────────────
SC CBI score: 96 → 3.1× more backward than GC (score: 31)
ST CBI score: 95 → 3.0× more backward than GC
BC CBI score: 86 → 2.7× more backward than GC
──────────────────────────────────────────────────────────────────────
The gap is not marginal — it is structural and multigenerational.
Sectoral Disparities: Education, Employment & Living Conditions
| Indicator | SC/ST | General Caste | Gap |
|---|---|---|---|
| Daily wage labourers in workforce | ~50% of SCs | ~10% | 5× |
| Private sector professionals | 5% (STs) | 30% | 6× |
| Children in private schools | <10% | ~33% | 3× |
| ST families without toilets/tap water | ~33% | ~5% | 6× |
Analytical Observation: Deprivation is multidimensional and mutually reinforcing — low private schooling access → lower skilled employment → lower income → lower asset ownership → lower social mobility. The cycle is self-perpetuating without targeted structural intervention.
Intra-Group Heterogeneity — The Sub-Categorisation Imperative
WITHIN BACKWARD CLASSES (BCs)
──────────────────────────────────────────────────────────────────────
Goldsmith caste : 75% youth English-medium educated
Padmasali caste : 75% youth English-medium educated
──────────────────────────────────────────────────
Mudiraj caste : <30% youth English-medium educated
Valmiki caste : <30% youth English-medium educated
──────────────────────────────────────────────────────────────────────
Implication: A blanket "BC reservation" benefits Goldsmith/Padmasali
disproportionately — Mudiraj/Valmiki remain structurally excluded.
WITHIN SCHEDULED TRIBES (STs)
──────────────────────────────────────────────────────────────────────
→ Sharp dropout rate differences between Gond and Lambadi tribes
→ Geographic isolation (forest-dwelling tribes) vs. semi-urban STs
creates vastly different access to education and services
WITHIN SCHEDULED CASTES (SCs)
──────────────────────────────────────────────────────────────────────
→ Wide variation in land ownership across SC sub-castes
→ Urban SCs have materially better outcomes than rural SCs
→ Some SC sub-castes approach BC-level outcomes; others remain
at the floor of the backwardness index
──────────────────────────────────────────────────────────────────────
Supreme Court alignment: Punjab v. Davinder Singh (2024) — SC
permitted sub-classification within SC/ST reservations to ensure
the most backward within reserved categories are prioritised.
The "Casteless" Population — A Revealing Anomaly
14 lakh people (4% of survey respondents) identified as "casteless."
CBI outcome:
→ Among the LEAST backward in Telangana
→ Better access to education and services than most caste groups
What this reveals:
→ Caste identity is not merely a social label — it is a structural
determinant of access to resources, networks, and opportunity
→ Its ABSENCE correlates with relative advantage — suggesting caste
itself, as an institution, generates and perpetuates deprivation
→ Constitutional implication: Caste discrimination is not incidental;
it is embedded in the social architecture
Policy note: This group likely includes urban, educated, economically
mobile individuals who have effectively "exited" caste identity —
a privilege itself correlated with prior social advantage.
Implications & Challenges
For Reservation Policy
- Monolithic SC/ST/BC categories mask vast internal heterogeneity — the most deprived sub-groups within each category are under-served by uniform reservation policies.
- Sub-categorisation within reservations is now empirically justified and judicially permitted (Davinder Singh, 2024) — Telangana data provides the evidentiary foundation.
For Welfare Scheme Design
- CBI score can serve as the eligibility threshold for targeted schemes — replacing income-only BPL criteria with a multidimensional backwardness filter.
- 135 castes (67% of population) scoring below State CBI average of 81 represent the primary target population for welfare intervention.
For Education Policy
- Private school access gap (33% GC vs. <10% SC/ST) signals that school enrolment data — the metric governments typically report — masks acute quality deprivation.
- Government schools in SC/ST-majority areas require functional upgrading: teachers, infrastructure, English-medium instruction.
Limitations of the Survey
- Self-reported data → risk of under-reporting untouchability and social exclusion practices.
- CBI is one framework — it captures relative backwardness within Telangana but does not account for absolute deprivation levels or inter-state comparisons.
Way Forward
- Adopt CBI as welfare eligibility criterion: Replace or supplement income-based BPL lists with multidimensional CBI scores for targeted scheme delivery.
- Sub-categorise reservations: Use SEEEPC data to create reservation sub-quotas within BC/SC/ST categories, prioritising the most backward sub-groups (Mudiraj, Valmiki, Gond, Lambadi).
- Quality schooling in SC/ST areas: Focus on learning outcomes, English-medium access, and teacher quality — not just enrolment figures.
- Replicate nationally: Demand a national Socio-Economic and Caste Census (SECC) — the last comprehensive attempt (SECC 2011) is now 15 years old and its caste data was never fully released.
- Address intra-ST isolation: Forest-dwelling and geographically isolated tribes (Gond) need infrastructure investment, not just reservation expansion.
Conclusion
The Telangana SEEEPC Survey is not merely a state-level census exercise — it is a proof of concept for evidence-based social justice governance. Its granular data demolishes three convenient fictions: that economic growth trickles down to caste-disadvantaged groups, that reserved categories are internally homogeneous, and that income is an adequate proxy for social deprivation. The 99% of STs and 97% of SCs who fall below Telangana's State backwardness average are not statistical anomalies — they are the evidence of a constitutional promise unfulfilled. The CBI framework, if adopted and scaled, offers India a path from symbolic reservation politics to structurally targeted social justice.
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GS1PopulationQuick Q&A
What is the Caste Backwardness Index (CBI) and how does it differ from traditional measures of social backwardness?
The Caste Backwardness Index (CBI) is a composite metric developed using data from the Social, Educational, Employment, Economic and Political Caste Survey (SEEEPC) to quantify the level of backwardness across caste groups. Unlike traditional approaches that rely primarily on caste identity or historical disadvantage, the CBI adopts a multi-dimensional framework, incorporating indicators such as education, employment, income, living conditions, and political representation.
This makes the CBI more evidence-based and granular. For instance, it highlights disparities not only between major caste categories like SCs, STs, BCs, and General Castes but also within them. The finding that "every backward caste is not equally backward" underscores the limitations of earlier classification systems that treated communities as homogeneous units.
A key distinction lies in its dynamic and comparative nature. While traditional classifications are often static, the CBI provides a relative benchmark (state average score of 81 in Telangana), enabling policymakers to identify which groups fall below or above the average. This allows for targeted interventions rather than blanket policies. For example, variations in English-medium education among BC sub-castes or land ownership differences among SC groups illustrate the need for nuanced policy design.
Thus, the CBI represents a shift from identity-based to data-driven governance, offering a more precise understanding of socio-economic inequalities.
This makes the CBI more evidence-based and granular. For instance, it highlights disparities not only between major caste categories like SCs, STs, BCs, and General Castes but also within them. The finding that "every backward caste is not equally backward" underscores the limitations of earlier classification systems that treated communities as homogeneous units.
A key distinction lies in its dynamic and comparative nature. While traditional classifications are often static, the CBI provides a relative benchmark (state average score of 81 in Telangana), enabling policymakers to identify which groups fall below or above the average. This allows for targeted interventions rather than blanket policies. For example, variations in English-medium education among BC sub-castes or land ownership differences among SC groups illustrate the need for nuanced policy design.
Thus, the CBI represents a shift from identity-based to data-driven governance, offering a more precise understanding of socio-economic inequalities.
Why is the finding that SCs and STs are three times more backward than General Castes significant for public policy?
The finding that Scheduled Castes (SCs) and Scheduled Tribes (STs) are three times more backward than General Castes is significant because it provides empirical validation of long-standing structural inequalities in Indian society. Such quantification strengthens the case for affirmative action policies by grounding them in measurable socio-economic disparities rather than solely historical arguments.
From a policy perspective, this disparity highlights the need for focused welfare interventions. For instance, the data reveals that nearly half of SC workers are engaged in daily wage labour compared to just 10% among General Castes. Similarly, only 5% of private sector professionals are STs, indicating systemic barriers in access to quality education and employment opportunities. These gaps justify targeted schemes in education, skill development, and employment generation.
Moreover, the findings have implications for resource allocation and governance priorities. Governments can use such data to prioritize investments in sanitation, schooling, and infrastructure in areas dominated by marginalized communities. For example, the fact that one-third of ST households lack basic amenities like toilets or tap water signals the need for region-specific development initiatives.
In a broader sense, the findings reinforce the importance of inclusive growth and social justice in a लोकतांत्रिक framework, ensuring that development benefits are equitably distributed.
From a policy perspective, this disparity highlights the need for focused welfare interventions. For instance, the data reveals that nearly half of SC workers are engaged in daily wage labour compared to just 10% among General Castes. Similarly, only 5% of private sector professionals are STs, indicating systemic barriers in access to quality education and employment opportunities. These gaps justify targeted schemes in education, skill development, and employment generation.
Moreover, the findings have implications for resource allocation and governance priorities. Governments can use such data to prioritize investments in sanitation, schooling, and infrastructure in areas dominated by marginalized communities. For example, the fact that one-third of ST households lack basic amenities like toilets or tap water signals the need for region-specific development initiatives.
In a broader sense, the findings reinforce the importance of inclusive growth and social justice in a लोकतांत्रिक framework, ensuring that development benefits are equitably distributed.
How does the CBI reveal intra-caste inequalities, and why is this important for designing targeted policies?
The CBI goes beyond broad caste categories to uncover intra-caste disparities, demonstrating that not all sub-groups within a caste experience the same level of backwardness. For example, among Backward Classes (BCs), about 75% of youth in Goldsmith and Padmasali communities have access to English-medium education, whereas less than 30% of Mudiraj or Valmiki youth do. Similarly, variations in land ownership among SCs and dropout rates among ST tribes like Gond and Lambadi highlight internal inequalities.
This insight is crucial because traditional policy frameworks often treat caste groups as monolithic entities. Such an approach can lead to unequal distribution of benefits, where relatively better-off sub-groups capture a disproportionate share of resources. By identifying these internal disparities, the CBI enables policymakers to adopt a more nuanced and equitable approach.
For instance, targeted scholarships, skill development programs, or micro-credit schemes can be directed specifically at the most disadvantaged sub-groups within a caste. This ensures that policy interventions are need-based rather than identity-based.
Ultimately, recognizing intra-caste inequalities enhances the effectiveness of welfare policies and contributes to inclusive and balanced socio-economic development.
This insight is crucial because traditional policy frameworks often treat caste groups as monolithic entities. Such an approach can lead to unequal distribution of benefits, where relatively better-off sub-groups capture a disproportionate share of resources. By identifying these internal disparities, the CBI enables policymakers to adopt a more nuanced and equitable approach.
For instance, targeted scholarships, skill development programs, or micro-credit schemes can be directed specifically at the most disadvantaged sub-groups within a caste. This ensures that policy interventions are need-based rather than identity-based.
Ultimately, recognizing intra-caste inequalities enhances the effectiveness of welfare policies and contributes to inclusive and balanced socio-economic development.
What are the key reasons behind the persistent disparities in education, employment, and living conditions across caste groups?
The persistent disparities across caste groups can be attributed to a combination of historical, structural, and institutional factors. Historically, caste-based discrimination limited access to education, land, and skilled occupations for marginalized communities, creating a cycle of deprivation that continues to this day.
Structurally, unequal access to resources plays a major role. For instance, the survey shows that only a small percentage of SC and ST children have access to private schooling, while one-third of General Caste children do. Similarly, the concentration of SC workers in daily wage labour reflects limited access to formal employment opportunities and skill development.
Institutional barriers also contribute significantly. These include discrimination in hiring practices, inadequate implementation of welfare schemes, and lack of representation in decision-making bodies. For example, the low representation of STs (5%) in private sector professions highlights systemic exclusion.
Additionally, geographical factors such as remote habitation of tribal communities exacerbate the problem by limiting access to infrastructure and public services. The fact that a significant proportion of ST households lack basic amenities like toilets and tap water illustrates this challenge.
Addressing these disparities requires a multi-pronged approach involving educational reforms, economic empowerment, and stronger institutional accountability.
Structurally, unequal access to resources plays a major role. For instance, the survey shows that only a small percentage of SC and ST children have access to private schooling, while one-third of General Caste children do. Similarly, the concentration of SC workers in daily wage labour reflects limited access to formal employment opportunities and skill development.
Institutional barriers also contribute significantly. These include discrimination in hiring practices, inadequate implementation of welfare schemes, and lack of representation in decision-making bodies. For example, the low representation of STs (5%) in private sector professions highlights systemic exclusion.
Additionally, geographical factors such as remote habitation of tribal communities exacerbate the problem by limiting access to infrastructure and public services. The fact that a significant proportion of ST households lack basic amenities like toilets and tap water illustrates this challenge.
Addressing these disparities requires a multi-pronged approach involving educational reforms, economic empowerment, and stronger institutional accountability.
Can you provide real-world examples from the Telangana survey that illustrate the concept of ‘hierarchy of backwardness’?
The Telangana survey provides several compelling examples of the ‘hierarchy of backwardness’, which refers to varying levels of deprivation within and across caste groups. One notable example is the disparity in education among BC sub-castes. While communities like Goldsmiths and Padmasalis show high levels of English-medium education (around 75%), others like Mudiraj and Valmiki lag significantly behind, with less than 30% access.
Another example is seen among Scheduled Tribes (STs), where differences in dropout rates between Gond and Lambadi tribes highlight uneven access to education and social mobility. Similarly, within Scheduled Castes (SCs), variations in land ownership indicate differing levels of economic security.
The survey also highlights contrasts between caste groups. For instance, nearly half of SC workers are daily wage labourers, whereas only 10% of General Castes fall into this category. Access to basic amenities further illustrates this hierarchy, with one-third of ST households lacking toilets or tap water compared to just 5% among General Castes.
Interestingly, the emergence of a ‘casteless’ category, comprising 4% of the population, shows relatively better socio-economic indicators, placing them among the least backward. This adds another dimension to the hierarchy.
These examples demonstrate that backwardness is not uniform but exists on a spectrum, necessitating differentiated policy responses.
Another example is seen among Scheduled Tribes (STs), where differences in dropout rates between Gond and Lambadi tribes highlight uneven access to education and social mobility. Similarly, within Scheduled Castes (SCs), variations in land ownership indicate differing levels of economic security.
The survey also highlights contrasts between caste groups. For instance, nearly half of SC workers are daily wage labourers, whereas only 10% of General Castes fall into this category. Access to basic amenities further illustrates this hierarchy, with one-third of ST households lacking toilets or tap water compared to just 5% among General Castes.
Interestingly, the emergence of a ‘casteless’ category, comprising 4% of the population, shows relatively better socio-economic indicators, placing them among the least backward. This adds another dimension to the hierarchy.
These examples demonstrate that backwardness is not uniform but exists on a spectrum, necessitating differentiated policy responses.
Critically analyze the strengths and limitations of using the Caste Backwardness Index as a policy tool.
The Caste Backwardness Index (CBI) has several strengths as a policy tool. Firstly, it is data-driven and multi-dimensional, capturing various aspects of socio-economic life such as education, employment, and living conditions. This makes it more comprehensive than traditional caste-based classifications. Secondly, it highlights intra-caste disparities, enabling targeted interventions and reducing the risk of resource capture by relatively advanced sub-groups.
Another strength is its ability to provide a relative benchmark, allowing policymakers to identify which groups fall below the state average. This facilitates evidence-based decision-making and prioritization of resources. The inclusion of a ‘casteless’ category also adds depth to the analysis by challenging conventional assumptions about caste and backwardness.
However, the CBI also has limitations. One concern is the potential for political misuse, as data on caste disparities can be sensitive and may be used to justify populist measures. Additionally, the index may not fully capture qualitative aspects such as social discrimination and cultural marginalization.
There are also challenges related to data accuracy and periodic updating. Without regular updates, the index may become outdated and fail to reflect changing socio-economic realities. Furthermore, reliance on quantitative indicators may overlook localized nuances.
In conclusion, while the CBI is a powerful tool for informed policymaking, it must be used alongside qualitative assessments and robust institutional mechanisms to ensure equitable and effective outcomes.
Another strength is its ability to provide a relative benchmark, allowing policymakers to identify which groups fall below the state average. This facilitates evidence-based decision-making and prioritization of resources. The inclusion of a ‘casteless’ category also adds depth to the analysis by challenging conventional assumptions about caste and backwardness.
However, the CBI also has limitations. One concern is the potential for political misuse, as data on caste disparities can be sensitive and may be used to justify populist measures. Additionally, the index may not fully capture qualitative aspects such as social discrimination and cultural marginalization.
There are also challenges related to data accuracy and periodic updating. Without regular updates, the index may become outdated and fail to reflect changing socio-economic realities. Furthermore, reliance on quantitative indicators may overlook localized nuances.
In conclusion, while the CBI is a powerful tool for informed policymaking, it must be used alongside qualitative assessments and robust institutional mechanisms to ensure equitable and effective outcomes.
As a district administrator in Telangana, how would you use CBI findings to design targeted interventions for backward communities?
As a district administrator, the CBI findings would serve as a critical evidence base for designing targeted interventions. The first step would be to identify the most backward communities in the district based on their CBI scores and analyze the specific dimensions of deprivation—whether in education, employment, or basic amenities.
For instance, if a particular ST community shows high dropout rates and poor access to sanitation, targeted measures could include residential schools, scholarship programs, and infrastructure development under schemes like Swachh Bharat and Jal Jeevan Mission. Similarly, for SC communities heavily dependent on daily wage labour, skill development programs and job linkages with local industries could be prioritized.
A key strategy would involve micro-level planning. Instead of broad caste-based schemes, interventions would be tailored to specific sub-groups. Collaboration with local self-help groups, NGOs, and पंचायत institutions would ensure better implementation and community participation.
Monitoring and evaluation would also be crucial. Regular tracking of indicators such as school enrollment, employment rates, and access to basic services would help assess the effectiveness of interventions and make necessary adjustments.
By leveraging CBI data, the administration can move towards precision governance, ensuring that resources reach the most disadvantaged sections and contribute to inclusive development.
For instance, if a particular ST community shows high dropout rates and poor access to sanitation, targeted measures could include residential schools, scholarship programs, and infrastructure development under schemes like Swachh Bharat and Jal Jeevan Mission. Similarly, for SC communities heavily dependent on daily wage labour, skill development programs and job linkages with local industries could be prioritized.
A key strategy would involve micro-level planning. Instead of broad caste-based schemes, interventions would be tailored to specific sub-groups. Collaboration with local self-help groups, NGOs, and पंचायत institutions would ensure better implementation and community participation.
Monitoring and evaluation would also be crucial. Regular tracking of indicators such as school enrollment, employment rates, and access to basic services would help assess the effectiveness of interventions and make necessary adjustments.
By leveraging CBI data, the administration can move towards precision governance, ensuring that resources reach the most disadvantaged sections and contribute to inclusive development.
Practice questions
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