Global industries and local development: labour in the Malagasy garment industry
Bibliographic record
Abstract
This paper examines some of the challenges and opportunities for development in Africa presented by the globalization of production through a qualitative-historical case study analysis of the condition of labour in the garment industry in Madagascar. It argues that this case demonstrates that attempts to incorporate national economies into the global economy on the basis of a comparative advantage in low-value added, labour intensive industries are unlikely to lead to significant development benefits. The paper first develops a historical overview of the development of the Malagasy export garment industry. It is situated within global and local trends towards economic liberalization, the re-orientation of development finance towards foreign direct investment, and the globalization of garment production. Three main structural features of the Malagasy Zone Franche garment industry are emphasized: the centrality of low cost labour, the dominance of low value added labour intensive activities, and reliance on access to markets in the industrialized north. These structural conditions are reinforced by the fluidity and volatility of the sector. The final section considers the impacts of these structures on labour relations in the garment industry. It argues that these structural conditions have kept wages and working conditions chronically poor. This failure to improve the condition of work is indicative of the weak structural position of peripheral economies and the challenges this poses to private sector-led development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".