An assessment of the capacity of faculty-based youth friendly reproductive health services to promote sexual and reproductive health among unmarried adolescents: evidence from rural Malawi
Bibliographic record
Abstract
Despite the recognition of the influence of cultural norms on adolescent sexual behaviours\nin most societies (Kaler 2004; Chege 2005), less attention has been paid to the link\nbetween social norms and effectiveness of health facilities to promote adolescent sexual\nand reproductive health (ASRH). This thesis therefore examines the capacity of facilitybased\nyouth-friendly reproductive health services (YFRHS) to promote ASRH in rural\nMalawian societies where culture strongly influences adolescent sexual behaviours.\nThe study employs a social constructionist epistemology and a social interactionism\ntheory to understand the capacity of YFRHS in ASRH promotion in rural Malawi.\nQualitative and quantitative data were collected using a sequential exploratory design.\nSemi-structured in-depth interviews, participant observations, client exit interviews,\nsurvey, focus group discussions and review of health strategic and service utilisation\ndocuments/records were conducted. The results were generated by triangulating both\nqualitative and quantitative data.\nThe findings of the study illuminate how social norms related to social identities influence\nadolescent sexual behaviours and ASRH promotion. An exploration of the cultural\ncontext reveals a major disjuncture between an ideal norm - no premarital sex - and a\nmodelled norm where unmarried adolescents are expected to engage in unsafe sex. It also\nshows the conflicts between the cultural and scientific models of ASRH promotion.\nStructural gender asymmetry that emphasises subservience in females and hegemonic\nmasculinity also reduces adolescents’ rights and agency in SRH promotion. The health\nproviders are cultural agents. They manage diverse roles both as ‘moral guardians’ and as\n‘health promoters’ in a way that limits their effectiveness as health promoters.\nThe thesis concludes that the way facility-based YFRHS is implemented has limited\nimpact on SRH promotion among unmarried adolescents of rural Malawi. The study\nrecommends that appropriate health promotion interventions based on conscientisationoriented\nempowerment theories directed at adolescents, community and health workers\nshould be used in ASRH promotion in societies with strong cultural influence on sexual\nbehaviours.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".