Dynamics of the `field': multiple standpoints, narrative and shifting positionality in multisited research
Bibliographic record
Abstract
The article contributes to the epistemological debates in feminism through the analysis of multisited research on jewellery production in India. The multisited research focuses on different localities — Noida Export Processing Zone (NEPZ), Delhi and villages of Medinipur having direct and indirect links to the global market. It analyses how the multiple sites structured by gender, class and age hierarchies reveal the multiple and fluid standpoints of different actors. The multiple standpoints of different actors feed into discursive practices of a complete exclusion of women from the production process of handmade jewellery in NEPZ, their marginal presence in Delhi, and their invisibility despite preponderance in the villages of Medinipur. These narratives constitute the subjectivity of men as `breadwinners' and of women as `housewives'. However, some women contest the discourses around marginalization of their work and present points of break in the configuration of power, questioning their subject position as `housewives'. Weaving these complex webs of narratives, I am reflexive of my multiple positionality as Indian, non-Bengali, elite, woman and the fluidity of my position as an insider/outsider in the `field'.
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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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.021 | 0.088 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".