The Impact of Family Planning on Women's Educational Advancement in Tehran, Iran
Bibliographic record
Abstract
The literature documenting drastic fertility declines in developing countries has largely focused on investigating the determinants of contraceptive use and the role contraceptives have played in declining fertility rates. In contrast, there has been limited research on the impact of family planning use on women’s social status. Using retrospective data from the 2009 Tehran Fertility Survey, this study examined the impact of contraceptive use on women’s educational advancement as an indicator of women’s empowerment. Multinomial logistic analyses indicated that compared with contraceptive nonusers, women using modern contraceptives before a first birth were more likely to experience a one to two year increase in education level after marriage, when controlling for other factors. Women in the most recent marriage cohorts were more likely to continue their education after marriage, especially those who were using modern contraceptives as opposed to traditional methods. Findings of this research clearly indicate that family planning use after marriage enables women to improve their education by freeing them from reproductive activities. __________________________________________________________________ *Corresponding Author, Amir Erfani, PhD., amire@nipissingu.ca, Department of Sociology, Nipissing University, 100 College Drive, Box 5002, North Bay, Ontario, Canada, P1B 8L7 December 2012 008-2012-ICRW-FE
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".