Mother–daughter communication about sexual maturation, abstinence and unintended pregnancy: Experiences from an informal settlement in Nairobi, Kenya
Bibliographic record
Abstract
Parental communication and support is associated with improved developmental, health and behavioral outcomes in adolescence. This study explores the quality of mother-daughter communication about sexual maturation, abstinence and unintended pregnancy in Korogocho, an informal settlement in Nairobi, Kenya. We use data from 14 focus group discussions (n = 124) and 25 interviews with girls aged 12-17, mothers of teenage girls, and key informant teachers. Many girls and women believed that mothers are the best source of information and support during puberty but only a minority described good experiences with communication in practice. Girls preferred communication to begin early and be repeated regularly. Mothers often combined themes of sexual maturation, abstinence and avoiding pregnancy in their messages. Communication was facilitated by mothers' availability, warmth and close parent-child relationships. Challenges included communication taboos, embarrassment, ambiguous message content, and parental lack of knowledge and uncertainty. Neighborhood poverty undermined some mothers' time and motivation for communicating.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".