Engaging Afghan men at a societal level to increase women’s access to contraception
Bibliographic record
Abstract
Mother and child mortality rates in Afghan internally displaced person (IDP) camps are high. Most women have unplanned pregnancies; many are child brides. Contraception can lower maternal mortality/morbidity from unintended pregnancy and short birth intervals, but in Afghan culture men make health decisions. Using knowledge of Afghan society gleaned from Afghan health workers, we trained respected elders and imams to start men’s groups to share practical, financial, and religious facts about contraception and promote discussion. The aim was to inform and allay misconceptions and fears so informed spousal conversation could occur; the overall objective was to allow women wanting spaced pregnancies or smaller families to gain spousal understanding and approval for use of contraception. Societal responses were monitored for one year among nine hundred families in three IDP camps where weekly men’s groups were conducted. Taking photographs captured unique ethnographic aspects of the intervention especially for those involved in this research who were not in Afghanistan and hence missed being directly engaged with the community. The maternal and infant health challenges and cultural issues addressed are global in nature; this model is globally applicable to other camps and Islamic societies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".