Development and Fertility Decline in the Arabian Gulf Cooperation Council Countries: The Case of the United Arab Emirates
Bibliographic record
Abstract
The Arabian Gulf Cooperation Council (GCC) countries including Saudi Arabia, Kuwait, Bahrain, Qatar, United Arab Emirates, and Oman have developed rapidly since the second half of the 20 th century, due to the increase of oil and gas revenues. The governments invested in major projects, which aimed at building the countries’ infrastructure, economy, and people. The GCC countries completely transitioned from traditional into advanced societies reaching high levels on the Human Development Index. Such development has contributed to fertility declines. In 1995, fertility rates were very high with 6.5 children per woman in Saudi Arabia, Qatar, and Oman, but in 2022 fertility rates declined threefold among them to less than 2 children per woman in all the GCC countries except Saudi Arabia (2.4) and Oman (2.7). The main objective of the research is to show the effect of some socio-economic factors on the decline in fertility rates of the GCC countries using historical and topical approaches. In addition, analytical techniques are used to analyze two questionnaires conducted in 2005 and 2020 to determine the effects of socioeconomic factors such as marital age, education, work status, and income on declining fertility in the United Arab Emirates.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".