Resistance to Women's Ethnic Narratives in Tanzania: Two Perspectives on Identity
Bibliographic record
Abstract
Two Tanzanian activists, Ruth Meena and Elieshi Lema, resist identification with their local ethnic groups in deference to their identity formation with nationalism and feminism. Both maintain that ethnicity is a politically charged term based on a colonial construct that favors patriarchy and describes all women’s ethnicity generically without questioning their positionality. Meena as a political scientist at the University of Dar es Salaam and Lema as a writer and editor of E & D Publishing, provide evidence for their professional roles having moved beyond ethnic boundaries due to their educational opportunities and the influence of feminist thinking. In the construction of their culture, as activists, scholars, teachers, and writers, they have re-imagined how to live their lives, so that they could actively participate in the struggle for nationhood, gender equality, educational access, economic independence and community development. Meena and Lema have also demonstrated through their writing of books and articles, the possibility for women to rewrite history with a different emphasis and orientation.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| 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".