Expatriate English Instructors in Saudi Arabia: Identity Formation and Professional Challenges
Bibliographic record
Abstract
This qualitative analysis examines the intricate ways of how the English teachers in Saudi Arabia (expatriates) create and bargain their occupational and individual identities. Based on the interviews carried out among ten male educators of various cultural and linguistic backgrounds, the paper shows the multidimensional nature of problems experienced by the educators under consideration, such as institutional restriction, cultural misalignment, pedagogical confines, and professional orchestration. The article employs phenomenological approach and thematic analysis to determine such important themes as displacement of identity, development of adaptive teaching styles, negotiation of legitimacy and formation of hybrid intercultural identities. The respondents complained about being disempowered as professionals because of the rigid nature of administrative organization, discrimination in favor of nationalities, and the lack of room to advance their careers. Regardless of these, instructors have incorporated various coping styles such as pedagogical adjustment, informal peer support groups, strength of emotion, and professional development via personal efforts. The results point to the context-specific and dynamic character of teacher identity and emphasise the importance of intercultural competence, institutional care, and inclusive policies to foster teacher well-being and effectiveness. This work will expand the debate on transnational education, teacher identity, and intercultural pedagogy and provide useful information to policymakers, institutional leaders and TESOL players in the same world.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".