Social Stratification and the Distribution of Capital in Kerala, India: Applying Bourdieu to the Centre for Research and Education for Social Transformation
Bibliographic record
Abstract
Long heralded as an oasis of caste consciousness and political mobilization against the formalized caste system in India (Devika, 2010; Steur, 2009), in truth, structural inequality arranged across caste lines persists in the state of Kerala (Mosse, 2010; Nampoothiri, 2009; Isac, 2011). In Kerala, and in India more broadly, inequality is maintained through social categorization; social networks emerging from and mirroring the divisions between castes impart dis/advantages to their members. In the midst of India’s economic liberalization, neoliberal trends including the privatization of education have ossified structures of access to higher education and, as such, competitive employment opportunities (Nampoothiri, 2009). Members of the dominant or ‘upper’ castes continue to be awarded disproportionate access to that which their society values and the tools necessary to succeed while Scheduled Caste (SC) and Scheduled Tribe (ST) communities operate at a structural disadvantage. This systemic unequal access is precisely what the Centre for Research and Education for Social Transformation (CREST) - an autonomous institution that seeks to enhance the employability of ST, SC and other eligible communities in Kerala - aims to address. I situate the ethnographic fieldwork I conducted at CREST within the theoretical framework outlined in Bourdieu’s (1986) seminal work The Forms of Capital. This approach elucidates the mechanisms through which CREST prepares ST, SC and other eligible communities’ graduates to succeed in contemporary Kerala’s competitive job market. I demonstrate how CREST facilitates the cultivation, adoption and transmission of cultural and social capital among its students and their communities, effectively increasing their capacity for socio-economic mobility. Furthermore, I discuss the potential of CREST to encourage its students’ development of critical perspectives on caste-disparity in their home state.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".