CSR Institutionalized Myths in Developing Countries
Bibliographic record
Abstract
This article examines joint action initiatives among small- and medium-sized enterprises (SMEs) in the manufacturing industries in developing countries in the context of the ascendancy of corporate social responsibility (CSR) and the proliferation of a variety of international accountability tools and standards. Through empirical fieldwork in the football manufacturing industry of Jalandhar in North India, the article documents how local cluster-based SMEs stay coupled with the global CSR agenda through joint CSR initiatives focusing on child labor. Probing further, however, also reveals patterns of selective decoupling in relation to core humanitarian and labor rights issues. Through in-depth interviews with a wide range of stakeholders involved in the export-oriented football manufacturing industry of Jalandhar in North India, the article highlights the dynamics of coupling and decoupling taking place, and how developing country firms can gain credit and traction by focusing on high visibility CSR issues, although the plight of workers remains fundamentally unchanged. The authors revisit these findings in the discussion and concluding sections, highlighting the main research and policy implications of the analysis.
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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 | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.070 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".