A Survey of expatriate teachers in Kuwait
Bibliographic record
Abstract
The purpose of this study was to understand why qualified American and Canadian educators left their home country to teach overseas and more specifically, why they decided to live and work in Kuwait. Fifty-one participants took part in the study. Each was asked to complete a 30 question survey followed by 5 open-ended questions. In addition, demographic information was sought in order to place the data into context. The study followed a conceptual framework adopted from research conducted by Richardson and McKenna (2002) who examined the motivation of expatriates. The findings for this research were placed into context using these terms as the framework from which to operate. The findings in this study suggest that many of the participants were dissatisfied with their current situation at home, usually job related, and decided to seek opportunities abroad. This dissatisfaction was coupled with the desire to see different parts of the world and to earn a comfortable living. These participants were not interested, for the most part, in advancing their careers or enhancing their skills. They were not interested in providing their services for little or no money. The group of explorers saw an opportunity to earn a tax-free salary, a comprehensive benefit package, and opportunities for travel and adventure. These were the reasons these teachers taught overseas and more specifically, these were the reasons they chose Kuwait.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".