Subaltern Educators Engaged in Empowerment of Minoritized Languages: A Case Study of the Azerbaijani Civic Nation and Turki
Bibliographic record
Abstract
This case study examines the underground linguistic, cultural, and educational activism of Turk educators in Iranian Azerbaijan during the 1990s and 2000s in Tabriz and their continued activism in exile. Faced with the denial of linguistic and cultural education in their minoritized language and socio-political suppression, they turned to underground spaces and created their pedagogies and resources for mother-tongue-based education. Once persecuted by the government due to their activism and confronted with severe challenges, they were forced to leave the country into exile. From that time forward, they have continued their efforts, and since 2020, they have been operating virtually as an educational platform under the Azerbaijani Civic Nation in Toronto, Canada. The study's subaltern theoretical framework provides a critical lens for grasping the power dynamics and contextual relations influencing these educators' approaches, resources, and strategies. Moreover, a case study methodology offers rich, in-depth, and contextual insights with data collected through multiple sources, including in-depth interviews with the co-founders of the Azerbaijani Civic Nation, alongside related documents, materials, publications, social media content, etc. This thesis greatly contributes to the discourse, promotion, planning, and pedagogy of minoritized languages, focusing on the role of subaltern educators who, in the face of all challenges, engaged in language as a means of education and a base for social solidarity, resistance, and change. The findings reveal the transformative power of alternative language pedagogies, particularly for marginalized groups, through their bottom-up, organic, collective, and intersectional approach. In doing so, they challenge established social norms and amplify non-dominant voices. Lastly, the study addresses overlooked literature on linguistically marginalized communities in Iran, focusing on activist Turk educators, and extends knowledge of activist-based education beyond the country to various marginalized communities
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".