Shortlisted
PANEL 10: Embodied Subjectivities, Gender, and Rights
Shortlisted
- PANEL 10: Embodied Subjectivities, Gender, and Rights
Caste-Conscious Care: Reframing Dalit Suffering as Embodied Praxis and Affective Attunement
Poonia, Rubal
Panjab University
Abstract
The paper advances a caste-conscious turn in care studies. Anchored in the Indian context, it proposes a shift in responding to Dalit suffering: from a mere “matter of concern” to a “matter of care” that demands compassionate, attentive engagement. Drawing on care ethics, affect theory, and decolonial epistemologies, the study examines Dalit life writing that resists reducing care to ritualistic performance, reframing it as an embodied, environmentally situated, and socio-politically embedded praxis. This elicits affective attunement to the violated “human-ness” of the oppressed other, while articulating alternative visions of relationality and care rooted in lived Dalit experience. Central to the intervention is the figure of “cared-for subject,” which counters savarna (upper-caste) framings that objectify Dalits as abject bodies. Key texts include Yashica Dutt's Coming Out as Dalit, which depicts the psychological toll of “closeting” caste identity and performing upper-caste-ness, and Thenmozhi Soundararajan's The Trauma of Caste, which theorizes "caste soul wounds" as intergenerational trauma inscribed in the body, necessitating care that encompass embodied dimensions. Embodied care, in Dalit context, privileges reconnection with embodied wisdom, ancestral resilience, and contemplative practices. Enriched by testimonies from digital subaltern counterpublics like the Skin Stories platform, where Dalit women share experiences of intersecting marginalities, the study exposes epistemic erasures and frames institutional “carescapes” as contested, caste-saturated spaces marked by power asymmetries. Ultimately, the paper calls for a decolonial reorientation of care studies, centering caste as a constitutive axis of care rather than a peripheral variable.
Image Credit: AI-generated image. Created by the author, 2026.