Sisters and Others: The Power and Politics of WeavingSupplementary Weft Textiles in a Sa'dan Toraja Village
Bibliographic record
Abstract
The weaving of textiles in Sa'dan Toraja, a district on the island of Sulawesi in Indonesia, is layered with many social and cultural influences. Based on my ethnographic fieldwork in three Sa'dan Toraja villages, I suggest the matriarchial social organization of the village life is the most significant factor influencing the production and sales of textiles. The status and hiearchy of the matriarchies is controlled by the local belief system adhered to by the Sa'dan Toraja known as adat. Several government proposals for weaving cooperatives have been assigned and distributed throughout the Sa'dan Toraja area, however only two have been accepted by the local population due to the social and political organization of the local hierarchial matriarchies. The weaving co-operative projects are supported by local government legislation, but when it is time for distribution of the funding only the weavers belonging to the hight status matriarchies will come forward and receive the funds. Weavers from lower status matriarchies will not come forward because by doing so they would be going against the religious and socio-cultural customs governing their society. The high status matriarchies also control the weaving of textiles by not sharing their knowledge of the supplementary weft techniques and most importantly, the knowledge of warping. Without this technical skill no weaving can take place. Traditional weaving knowledge is passed from one group of sisters to their daughters and shared only within this social group; thereby, preserving their knowledge and maintaining their exclusive status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".