Assessment of the feasibility and potential effectiveness of a baby-friendly workplace support initiative in rural Kenya: a study protocol
Bibliographic record
Abstract
Background: Employment poses a barrier in achieving the World Health Organization’s recommendation of exclusive breastfeeding for the first six months of life. Effective strategies and evidence to improve breastfeeding for women working in the agricultural sector – the main employer for women in Kenya – is lacking. This study aimed to inform (with evidence) the design and implementation of a scalable model of workplace support for breastfeeding in an agricultural setting in Kenya; as well as investigated the model’s potential operational feasibility and potential effectiveness, and its cost-effectiveness. Methods: The study employed a mixed methods approach and participatory methods at the pre-implementation, implementation and post-implementation phases. The pre-implementation phase generated evidence to inform the implementation. Mothers with children under 12 months were interviewed at the pre-implementation (2016) and post-implementation (2018) phase. Managers, supervisors, decision and policy makers, as well as other community members were also targeted. Statistical methods will include analysis of covariance and logistic regression. Additionally, cost-effectiveness and cost-benefit analyses will be done. Qualitative data will be analysed in vivo, using thematic analysis technique. Conclusions: Findings from this study aimed to inform the potential feasibility and potential effectiveness of a baby-friendly workplace support for breastfeeding initiative in an agricultural setting with a goal of improving child nutrition and health. The findings also contribute to policy and practice in Kenya by informing the development of workplace support guidelines. Trial Registration: ISRCTN registry, ISRCTN 64692465; date of registration: 21 December 2016 – retrospectively registered, http://www.isrctn.com/ISRCTN64692465.
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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 | 0.102 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".