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Record W2186744248 · doi:10.21083/ajote.v4i1.3016

Resistance to Women's Ethnic Narratives in Tanzania: Two Perspectives on Identity

2015· article· en· W2186744248 on OpenAlexvenueno aff
Sonja Darlington

Bibliographic record

VenueAfrican Journal of Teacher Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
Fundersnot available
KeywordsGender studiesEthnic groupNationalismSociologyIdentity (music)PatriarchyFeminismPoliticsIndependence (probability theory)ColonialismResistance (ecology)NarrativePolitical scienceAnthropologyLawAesthetics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.370
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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