International Education Teachers’ Experiences as an Educational Precariat in China
Bibliographic record
Abstract
The purpose of this paper is to extend Bunnell’s (2016) thesis that international education teachers (IETs) are forming a ‘global educational precariat’. The paper draws upon interview data from a larger study of international teachers in two international schools in Shanghai, China. In order to substantiate and develop Bunnell’s thesis, narrative inquiry was employed as a guiding methodology, which ensured that data analysis remained rooted in the participants’ lived experience but also allowed for triangulation, thereby enhancing validity. Findings confirm Bunnell’s thesis by highlighting a lack of agency, financial insecurity, and the marginalisation of professional identities as common experiences of IET precarity. The findings also challenge the notion of a global educational precariat by arguing that it may be more appropriate to conceptualise IETs in terms of a localised educational precariat rather than a global class in and of itself. The paper ends by sketching a research agenda that would involve comparing teachers’ experiences in different types of international schools in China and other contexts.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".