Multinational Corporations and Civil Society: A case study Comparison of H&M and Hoang Anh Gia Lai Group in Cambodia
Bibliographic record
Abstract
This paper examines the impact both positive, and negative of two multinational corporations (MNCs), H&M and Hoang Ahn Gia Lai Group both of whom operate extensively in Cambodia. It examines the important role domestic civil society plays in resisting the worst predatory tendencies in MNCs, and how the capacity to resist may be curbed by authoritarian regimes. Furthermore, the essay examines the role of international groups as well as consumer society on holding MNCs accountable for their actions. Particular attention is paid to the impact these multinational corporations have on women and indigenous communities, who are in the Cambodia context two of the most vulnerable groups in society. Moreover, it is suggested that while multinational corporations may ameliorate their practices in some areas, this often requires sustained pressure from a variety of actors, with this being especially true when governments cannot or are unwilling to regulate the behaviour of corporations. Lastly, it is suggested that civil society in the host state is the most important actor for bringing pressure to bear on MNCs, they must be supported by either international actors, or the domestic government to truly reign in the most predatory behaviour of MNCs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".