Revisiting Native Speakerism in ELT: Viewpoints of Chinese EFL Program Administrators on the Recruitment and Workplace Situations of Foreign English Teachers
Bibliographic record
Abstract
This article reports on a case study that explores the views of four EFL program administrators of a university located in central China about the hiring and workplace situations of foreign English teachers. It was found that the administrators as a whole buy into the conventional pro-nativeness ideology with regard to hiring foreign English teachers, though one of them displays critical awareness to some extent. The four administrators, except one, consider it natural and reasonable to grant more favor to foreign English teachers in payment and workload, and fail to see an academic apartheid for foreign teachers in relation to teaching task allocation and engagement in academic activities. All these findings suggest the continuity and tenacity of native speakerism among most ELT administrators, in addition to critical awareness on the part of some administrators. Moreover, this study proposes that native speakerism should be seen as an ideology against both NESTs and NNESTs, though the former still enjoy more privileges.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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 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".