Promoting evidence informed policy making in Nigeria: a review of the maternal, newborn and child health policy development process
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: There is increasing recognition worldwide that health policymaking process should be informed by best available evidence. The purpose of this study was to review the policy documents on maternal, newborn and child health (MNCH) in Nigeria to assess the extent evidence informed policymaking mechanism was employed in the policy formulation process. Methods: A comprehensive literature search of websites of the Federal Ministry of Health(FMOH) Nigeria and other related ministries and agencies for relevant health policy documents related to MNCH from year 2000 to 2015 was undertaken. The following terms were used interchangeably for the literature search: maternal, child, newborn, health, policy, strategy,framework, guidelines, Nigeria. Results: Of the 108 policy documents found, 19 (17.6%) of them fulfilled the study inclusion criteria. The policy documents focused on the major aspects of maternal health improvements in Nigeria such as reproductive health, anti-malaria treatment, development of adolescent and young people health, mid wives service scheme, prevention of mother to child transmission of HIV and family planning. All the policy documents indicated that a consultative process of collection of input involving multiple stakeholders was employed, but there was no rigorous scientific process of assessing, adapting, synthesizing and application of scientific evidence reported in the policy development process. Conclusion: It is recommended that future health policy development process on MNCH should follow evidence informed policy making process and clearly document the process of incorporating evidence in the policy development.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it