Spatial Distribution and Trends of Fertility Differentials in Toba Tek Singh District, Punjab-Pakistan
Bibliographic record
Abstract
This study examines socio-economic and demographic factors as fertility differentials and draws conclusions upon data collected from some selected rural and urban localities of Toba Tek Sing-Punjab. The analysis carried to examine change in fertility trends and preferences in relation to children ever born to currently married women. The ideal family size from the both localities is 3.98 which, is still reckoned high as compared to the (NGRP) National Growth Rate in Pakistan which is 3.80. The dependent variable is reproductive preference measured by a single indicator- ideal no. of children and gender in both urban and rural localities as same study was conducted by National Institute of Population Studies (NIPS) in 1990-91 and 2006-07. In Pakistan number of demographic surveys has revealed that woman of reproductive age generally prefer more children than their own preferred family size. The aim of this study is to contribute into the existing literature on the geographical patterns of fertility differentials in a district of the Punjab. This will help planners to formulate more effective fertility related policies and programmes in the country. This is also a continuum of DHS conducted in mid 1980s to elaborate fertility patterns among married couples. The goal is to dig deeper into the relationship between education and fertility has been a central focus within demography and related social sciences. Higher education is associated with higher age at first birth and lower number of children discussed the implication of findings in the context of policy framework to enhance the public awareness about the small family in context with high quality life. Higher fertility in a country like Pakistan is rooted in cultural believes about children and number, pre-natal control measures should be targeted more at women attitude to large family. This is to provide policy makers with an understanding of the potential demand for fertility control and help in formulating policies to reduce fertility and improve socio-economic climate of the district.
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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 | 0.002 |
| 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".