Hiring native-speaking English teachers in East Asian countries
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
ENGLISH is the most commonly used language in the world. As it has become the language that provides access to higher education and job opportunities, and has become almost exclusively the language of diplomatic discussion and business negotiation (cf. English APEC Strategic Plan, 2004), there has been a growing interest in hiring native-speaking English Teachers (NSETs) in Asian countries. The aim of this paper is to report policies and practices that invite NSETs to Asian countries, including China and Hong Kong, Taiwan, Japan, and South Korea, with emphasis on public education sectors. Through surveying both similar policies and the implementation of policies in several Asian countries, we seek to find practical suggestions for hiring NSETs. We survey policy goals, recruitment procedures, and the qualifications of NSETs. The analysis will be based on the premise that ‘language planning cannot be understood without reference to its social contexts’ (Cooper, 1989:3).
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 | 0.001 | 0.002 |
| 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) | 0.001 | 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 it