The Availability and Efficiency of Health Insurance to Expatriates: Empirical Findings from Saudi Arabia
Bibliographic record
Abstract
Health Insurance represents the largest sectors among all types of insurance in Saudi Arabia with a Gross Written Premiums of 51% of the whole insurance market in Saudi Arabia. The high growth of health insurance sector in Saudi Arabia was driven by the obligation mandated by the Ministry of Health "MOH" and Council of Cooperative Health Insurance "CCHI" for expatriates and their families living in Saudi Arabia to have their health insurance, affected mid of 2014. However, the regulations didn’t specify the types and quality of health insurance used. The regulations also didn’t take into consideration the salaries of the expatriates which might affect their financial positions in case of policy cancelation. No studies have been conducted on the Saudi Arabian health insurance market to explore the efficiency and quality of expatriates’ health insurance policy. This paper attempts to fill the gap. The main aim of this study was to explore the availability and efficiency of health care system to expatriates. The quality of health insurance policy relies on the selections made by the employers. The research used qualitative methodology for collection of primary data. A total of 324 responds were received and considered usable for the research. The results were astonishing that most of the participants have their own health insurance policy, however not all service are available to them. Most of the participants clarified that their health insurance policy, did not cover of most of the risk they encountered, it did not cover the medical treatment expenses, as well as the surgery and operation expenses. Such results will put financial burden on expatriates in case their health insurance claims been canceled.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".