Corporate Social Responsibility: An Anthropological Approach to Understanding CSR as Global Governance
Bibliographic record
Abstract
Corporate social responsibility (CSR) has become a crucial element of development projects, and this has led anthropologists to speculate on the unintended consequences of positioning big business as givers of aid. Supported by international law and governments that deregulate businesses who practice CSR, corporations move freely across borders into countries whose communities become dependent on corporate aid dollars. Corporations assert their financial might by funneling their aid dollars through partnerships with non-governmental organizations (NGOs) in the countries where they operate. An examination of the structure of partnerships formed between and among corporations, governments, and NGOs shows that they are imbalanced in their power structure and this imbalance extends to the target populations of CSR programs. This paper examines the ramifications of these power imbalances through an assessment of Coca-Cola's activity in India and Israel alongside a review of the work of anthropologists in the area of CSR. Through this examination, I argue that CSR programs are instilling corporations with political influence that enables them to vie for global governing power, demonstrating that this dynamic has dire consequences for both the communities with whom corporations are interacting and the environment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.051 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".