Factory ‘nuns’: the ethnicization of migrant labor in the making of Tibetan carpets
Bibliographic record
Abstract
Many debates over migrant labor politics in contemporary China rely upon essentialist notions of ethnic identity. In contrast, I identify migrant labor politics as transnational processes through which women migrants from rural Tibet become ethnic workers. Drawing on post-colonial theories of ethnicity and on feminist literature on global capitalism, this article analyzes the uses of migrant laborers in a globalizing Tibetan carpet industry. First, I investigate the making of Tibetan carpets and the essentialist construction of ‘carpet weavers’ employed by Tibetan–Nepalese carpet factory owners, carpet dealers in New York City, and various participants in Lhasa, including party cadres, international non-government organizations (NGOs), and overseas investors. I argue that the functioning of the international carpet business relies upon the ethnicization of migrant labor, in which labor subjugation involves creating ethnic subjects and ethnicized boundaries. This form of labor commodification is driven by both an economic logic and a moral imperative for preserving or regenerating ‘ethnic culture.’ Second, through the lens of gender, I look closely at the ethnicization of migrant labor in post-socialist Lhasa, analyzing its significance for the labor force in the carpet industry. The women carpet weavers, who mostly come from Tibet's rural areas, I found, strive to reconcile their desires for female autonomy with labor positions that reduce them to strangers in the city. Some women attempt to overcome their experiences of alienation while actively engaging in the reproduction of the patriarchal family as well as in labor hierarchies at work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".