Bibliographic record
Abstract
In spite of considerable research on Kenya’s fertility, questions remain. This dissertation examines three of these issues - the national and sub-national trend patterns in the country’s fertility and related proximate determinants, factors in the transitions to second and third conceptions, and the determinants of contraceptive use. Results, presented below, are based upon data which comprised five sample surveys conducted between 1977 and 2003 among women of reproductive age, as well as a community and health facility survey implemented in 1999. First, an exploratory analysis of trends in fertility and its proximate determinants shows that a pattern of later family formation and of a higher level of fertility control is associated with the more modernized and developed regions (urban areas and rural Central Province). Secondly, using survival analysis, the relative hazards of transition to the second and third conceptions for the 12-year periods during which fertility fell rapidly (1977-1989) and the pace of decline reduced (1991-2003) are compared. Among the findings, although child survival has significant effects during both periods, its influence is more pronounced during the recent period. Thirdly, multivariate analysis of the determinants of contraceptive use shows that motivation for fertility control is significant, while access to family planning services is not. That proximity to family planning services might nevertheless be important is shown by the significance of exposure to family planning messages, many of which are often communicated from the health facilities. This dissertation makes contributions in three areas. One, it confirms the dichotomy in the pattern of fertility change and its proximate determinants in the country, not so much along the usual rural-urban separation, but rather between urban areas and rural Central versus the rest of rural Kenya. Two, it shows that the decreased pace of the fertility transition in Kenya, including constant fertility over 1998-2003, might be associated with the rise in infant and child mortality since the 1990s. Three, it shows the significance of education, motivation for fertility control, and exposure to media messages about family planning in contraceptive use, thereby pointing out where policy and program effort should be directed in order to sustain the fertility transition.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".