Self-reported fertility impairments and help-seeking strategies among young women in Malawi
Bibliographic record
Abstract
This paper analyses wave 4 the Tsogolo la Thanzi survey of n = 1349 Malawian women aged 16–26 to explore the prevalence and predictors of self-reported fertility impairments (difficulties conceiving and/or difficulties carrying a pregnancy to term) and help-seeking strategies. Using descriptive statistics, logistic regression models, and graphic displays, the correlates of self-reporting an impairment and patterns of help-seeking strategies are examined. Nearly 13% (n = 117) of those who had ever tried to conceive reported experiencing a fertility impairment. Age was positively associated with reporting an impairment, while there was a negative association with education and with parity. Of women who reported an impairment, 85.5% sought help. Visiting a hospital or clinic was the most common response, followed closely by going to a traditional healer. Around one-quarter employed multiple help-seeking strategies, highlighting the need for various help-seeking behaviours to be viewed in tandem rather than in isolation.
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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 | 0.000 | 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) | 0.002 | 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".