Deconstruction of cultural dominance in Korean EFL textbooks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article examines patterns of cultural representations embedded in Korean EFL textbooks, using a content analysis to investigate how different cultures are reflected in textbooks and whether or not cultural biases are present. In the revised Korean national English curriculum that has been implemented since 2009, English is viewed as a language of global and cosmopolitan citizenship. The curriculum promotes cultural diversity and attempts to embrace cross-cultural and cross-linguistic differences. However, the analysis of four textbooks, which were developed according to the curriculum, reveals that they favor American English and culture. Furthermore, although the textbooks show various cultural/intercultural interactions, the interactions are primarily limited to a superficial level of discussion, and non-Korean, white, mostly American and male characters play a dominant role in the texts. As a result, this reproduces social inequalities regarding race, nationality, and gender by favoring mainstream white American male representations over others. The analysis is followed by a discussion of the reproduction of dominant knowledge, cultural biases, and inequalities embedded in the texts and suggests that teachers should take a critical approach to intercultural education in order to instill more inclusive and critical worldviews in their students.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it