Doing well by doing good: logics of corporate social responsibility in Bangalore, India
Bibliographic record
Abstract
Based on 12 months of research in Bangalore, this dissertation examines the practice of corporate social responsibility (CSR) in India, an activity that became mandatory with the 2013 revision to the Companies Act. It is specifically concerned with the historical, conceptual, and sentimental dimensions of the decoupling of social policy from nation-state in India, indexed by the increasing responsibility taken for the social by transnational and local corporations. Engaging largely with CSR practitioners rather than the targets of CSR programs, and relying on data gathered through archival research, interviews, and participant observation, this work seeks to extend and adapt theorizing in the anthropology of humanitarianism to an analysis of corporate forms of social intervention. I ask the following questions: How do the logics of CSR give rise to corporate interventions into society that differ from those typically associated with nation-states? What novel iterations of governance, society, and citizenship might come into being when responsibility for population welfare is decoupled from the nation-state and comes to be shared with profit-seeking entities such as corporations? And what kinds of sentiments fuel corporate forms of social intervention in the Indian context? I demonstrate how CSR in India constitutes a hybridized and diverse set of practices with varied implications: CSR programs that claim to empower female garment factory workers while at the same time generating returns for businesses; corporations that govern entire townships; the deployment of idioms of debt and sacrifice to target expanded conceptions of the social by a corporate-partnered voluntary organization; and the recognition of selfishness and the ego in guiding charitable activity by CSR practitioners, who strive towards non-attachment in their lives and work. I contend that CSR today can be situated within a longer history of the relationship between the provision of welfare and governmental legitimacy, one that is reconstituting the meaning and practice of governance, citizenship and society, animated by corporatized logics of intervention as much as religiously-grounded humanitarian sentiments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.028 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".