Reducing harmful traditional practices in Adjibar, Ethiopia: Lessons learned from the Adjibar Safe Motherhood Project
Bibliographic record
Abstract
This paper assesses the impact of the Adjibar Safe Motherhood Project and derives lessons of value to future interventions. Amongst the participatory qualitative methods used were 15 group discussions, eight semi-structured interviews, a number of opportunistic informal discussions and observation. The information gathering was complemented by a detailed review of project documents. Field visits for data collection took place over a six day period in March 2005. The project was effective in raising awareness about maternal health, and the social, economic and health consequences of various harmful traditional practices (HTPs). It has also mobilised the community to monitor and report HTPs and has strengthened referral systems for counselling, support and treatment. A number of effective strategies were identified as having contributed to project success. These are presented using the framework offered by the Ottawa Charter for Health Promotion which presents five areas of public health action: developing personal skills; strengthening community action; building healthy public policy; re-orienting health services; and, creating supportive environments. This evaluation contributes to and strengthens the expanding body of literature about effective development practices to reduce HTPs. It demonstrates that addressing HTPs takes time and long term investment; both are necessary to enable better understanding of the social and cultural reasons for HTPs before attempting to address them, and to build the community trust necessary to overcome the natural resistance to challenging such deeply entrenched practices. The project also highlighted the importance of developing a multi pronged strategy based on engagement with a broad range of stakeholders and supportive legislation.
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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 | 0.011 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".