Global value chains and supplier perceptions of corporate social responsibility: a case study of garment manufacturers in Myanmar
Bibliographic record
Abstract
Abstract Suppliers are embedded simultaneously in the global value chains (GVCs) of their lead firms and in the countries in which they conduct their production activities. To explain supplier perceptions of corporate social responsibility (CSR) in GVCs, in this article, we develop a new typology by integrating buyer governance modes in GVCs and forms of supplier embeddedness (societal, network, and territorial). We advance literature on supplier perspectives on CSR in GVCs through an analysis of 19 garment manufacturers in Myanmar and their CSR perceptions, using in‐depth field‐work, interviews, and secondary data. The empirical findings indicate a variety of supplier perceptions of CSR, depending on the governance mode of the GVCs and the variegated combinations of societal, network, and territorial embeddedness. Understanding supplier CSR perceptions and their implementation in GVCs thus requires moving away from a sole focus on supplier responses to standardized codes of conduct and towards a greater consideration of different types of supplier embeddedness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".