Abortion and fertility control in Pakistan: the role of misoprostol
Bibliographic record
Abstract
Objective To examine how availability of misoprostol has impacted women's abortion-seeking behaviour in Pakistan. Design Focused ethnography. Setting A facility providing reproductive health services, including induced abortions in Chakwal, a small town in Northern Punjab, Pakistan. Population Women who came to the clinic seeking an abortion or who had had one in the last 6 months ( n =23) and all healthcare providers working in the facility ( n =14). Methods Semi-structured interviews ( n =37), a focus group discussion ( n =1) and participant observation ( n =41). Latent content analysis was conducted drawing on principles of constant comparison to generate key themes in reported experiences. Results All the respondents had sought an abortion to limit their fertility. Although some reported contraceptive use, improper use, undesirable side effects and restrictions on use had led to the unwanted pregnancy. All the women specifically requested misoprostol within days of their pregnancy, suggesting that they not only had knowledge of misoprostol as a backup in case of contraceptive failure, but may have pre-planned its use of in place of using contraception. Women reconciled their decision to undergo an abortion by describing it as a mistake, miscarriage or menstrual cycle issue. Conclusions Misoprostol's availability, ease of use and effectiveness have increased the role of abortion in fertility control.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| 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".