
<p>The Central Government&#8217;s decision to include caste details in the upcoming national census marks a significant shift in India&#8217;s approach to social data collection, being the first comprehensive caste enumeration since</p>



<ol start="1931" class="wp-block-list">
<li>This move holds particular importance for Pasmanda Muslims-comprising backward, Dalit, and Adivasi Muslim communities-who have historically faced socio-economic marginalization and underrepresentation.<br />The Telangana caste survey, which revealed that approximately 80% of the state&#8217;s Muslim population belongs to Pasmanda groups, has further underscored the need for such inclusive data. By capturing detailed caste information across all communities, the national census could pave the way for more targeted affirmative actions and an inclusive approach to social justice, addressing the disparities faced by marginalized groups.</li>
</ol>



<p>The struggles of Pasmanda Muslims are often marginalized due to the homogenization of the Muslim identity in India, where the community is frequently portrayed as a monolithic group. This erases the internal hierarchies and caste-based inequalities that exist within Muslim society. As a result, policies and narratives aimed at addressing Muslim marginalization often fail to account for the disproportionate exclusion and poverty faced by Pasmandas. Their distinct socio-economic challenges and demands are sidelined, further entrenching their invisibility in both public discourse and state welfare programs.</p>



<p>The National Caste Census aims to recognise the caste differences within the Muslim community, finally giving overdue acknowledgment to the specific struggle of Pasmanda Muslims. The Sachar Committee (2006) exposed the socio-economic backwardness of Muslims, noting that many Pasmanda sub-groups fare worse than even Scheduled Castes in areas like literacy, employment, and access to healthcare. By collecting detailed caste data within the Muslim community, the census can lay the groundwork for equitable policy interventions that address the layered marginalization of pasmandas.</p>



<p>Historically, Pasmanda Muslims were clearly recognized in colonial records, where the British administration meticulously documented caste divisions among Muslims, just as they did among Hindus. Reports like the 1901 and 1931 Censuses classified Muslim castes into Ashraf, Ajlaf, and Arzal categories, acknowledging the existence of hierarchy and untouchability within the community. However, post-Independence India adopted a homogenized view of Muslims as a single, undifferentiated minority, erasing internal caste stratification from policy and public discourse.<br />SC reservation for Dalit Muslims was snatched away in 1950. This shift not only rendered Pasmandas invisible in welfare schemes and affirmative action but also allowed dominant elite Muslims to monopolize representation and benefits meant for the marginalized.</p>



<p>The Caste Census must be conducted and reported with full transparency to ensure its effectiveness in addressing systemic inequalities.<br />Any attempt to underreport or obscure caste data especially due to social stigma or political pressure-would defeat the very purpose of the exercise, which is to reveal the true socio-economic realities of marginalized communities, including Pasmanda Muslims. Accurate and honest data is essential for formulating fair policies, allocating resources equitably, and ensuring representation. By disaggregating caste data within the Muslim community, the caste census can provide a factual basis for targeted policies, ensuring that Pasmandas are no longer treated as a homogeneous part of a larger religious identity but as a socially distinct group with legitimate claims to affirmative action and justice.</p>



<p><em>Adnan amar is an advocate, speaker, poll analyst and President of All India Pasmanda Muslim Mahaaz, Telangana. He tweets under @TheAdnanQamar.</em></p>

Unveiling the Margins: Pasmanda Muslims, Caste Realities, and the Promise of a Transparent Census
