Prevalence and Correlates of Pre-Marital Fertility (Childbearing) among Unmarried Female Youths in Chamwino District in Central Tanzani
Bibliographic record
Abstract
Fertility/childbearing among non-married female youths has been associated with several social problems to a female youth, as well as both social and health problems to a child (newborn). This study was carried out in Chamwino district in Central Tanzania between July to August, 2010 with the aim of identifying correlates of pre-marital fertility/childbearing among non-married female youths in a study area. Specific objectives of the study were to determine the extent of sexual and other risky behaviours and fertility among non-married female youths in the study area; identification of socio- demographic, and behavioral factors that are associated with pre- marital fertility among non-married female youths in the study area. This was a cross- sectional study that involved 202 non-married female youths aged between 12-24 years from four randomly selected villages from four randomly selected wards with one village from each ward. Data were analyzed for descriptive statistics such as frequencies and percentages; as well as Binary Multiple Logistic Regression for identification of factors associated with pre- marital fertility using Statistical Package for Social Sciences (SPSS) version 12. Results of this study indicated sexual practices, risky behaviours and hence pre-marital fertility/ childbearing among non-married female youths in a study population existed at a substantial rate, with 75% of study participants reported to had ever had sex, and nearly a quarter (24%) of those who had ever had sex indicated to had ever given birth. Likelihood (chances) of having pre-marital fertility among non-married female youths increased with increase in age (Odds ratio (OR = 14.9-19.80, p 0.05). Based on these findings, recommendations to reduce prevalence of pre-marital fertility among non-married female youths in the study area have been indicated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".