Age at marriage, contraceptive use and abortion in Yemen, 1991-1997
Bibliographic record
Abstract
This paper attempts to examine the extent of influence of the three components of fertility, age at marriage, extent of modern contraceptive use and the level of abortion on fertility in the Republic of Yemen and to explore the impact of a selected set of demographic and socioeconomic variables on the three fertility components. This study uses data from Demographic and Health Surveys (DHS) conducted in Yemen in 1991/1992 and 1997. The results from this study present empirical evidence of an onset of fertility decline in the Republic of Yemen. An important component of this decline is delayed age at marriage. There has been an increase in modem contraceptive use during the last decade. However, these methods are not widely used at early stages of family formation. The most common method of family limitation among women with large families is abortion. There has been very little change if any in the widespread occurrence of abortion during the last decade. There exist significant urban-rural differences in the levels of contraceptive use and abortion. Improvements in women's education and modern sector labor participation are crucial for increasing age at marriage, and level of contraceptive use and for reducing the prevailing level of abortion.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".