Bibliographic record
Abstract
The restructuring of world economies in the 1980s and the 1990s has given rise to debates around globalisation, feminisation and flexibility. In the light of these macroeconomic debates, this article analyses the relationship of feminisation and masculinisation to flexibility in the microeconomic context of jewellery production in the Noida Export Processing Zone (NEPZ) and Delhi. It compares ‘flexibility’ in the handmade jewellery sector, which is largely informal, to machine-made jewellery, which is quasi-formal. Most debates on flexibility focus on the supply side and the removal of ‘institiutional rigidities’ that prevent the functioning of free market forces. These debates focus on the issues of organisational flexibility, labour market flexibility and functional flexibility of the entrepreneur. This study goes beyond the employer–worker dyad to examine ‘flexibility’ for the intermediate actors involved in production. In the handmade jewellery sector in both Delhi and NEPZ, labour market flexibility is occurring with a largely masculinised labour force. In machine-made jewellery, there is a slight feminisation of flexible status but it is not marked. The gendered division of labour, thus, is only a small part of what flexibility constitutes, if at all.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".