Racialized English Language Learning at the University: Rethinking Educational Practices in Bogotá
Bibliographic record
Abstract
This reflexive article examines how university English language programs in Bogotá, Colombia reproduce racialized practices that favor hegemonic cultural narratives and norms. Based on a critical review of the literature on linguistic imperialism and recent studies on stereotypes, unequal access to resources and accent discrimination, the objective is to identify the power dynamics that undermine pedagogical neutrality and to propose de-racialization strategies. The methodology combines a documentary analysis of curricular materials with an inductive reflection based on classroom experiences, making it possible to map the points of tension that emerge from interactions between teachers and students. The results reveal that texts, institutional policies and evaluative practices privilege standardized forms of English linked to Western identities, marginalizing racialized voices and affecting self-esteem and academic participation. Three critical areas are reflected upon: unequal distribution of resources, racial stereotyping in teacher expectations, and the imposition of an ideal native accent. Based on these areas, proposals are formulated to redesign inclusive curricula, train teachers in intercultural sensitivity and value linguistic diversity as a pedagogical resource.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".