Supporting research leadership in Africa
Bibliographic record
Abstract
The Editorial published in The Lancet Global Health and The Lancet Diabetes and Endocrinology by Davies and Mullan1Davies J Mullan Z Research capacity in Africa—will the sun rise again?.Lancet Glob Health. 2016; 4: e287Summary Full Text Full Text PDF PubMed Scopus (16) Google Scholar, 2Davies J Mullan Z Research capacity in Africa—will the sun rise again?.Lancet Diabetes Endocrinol. 2016; 4: 375Summary Full Text Full Text PDF PubMed Scopus (9) Google Scholar spotlighted Africa's need to build local health research capacity. Parachuting in research solutions from developed countries doesn't work: “African researchers are best placed to ask questions that are relevant to African issues.”1Davies J Mullan Z Research capacity in Africa—will the sun rise again?.Lancet Glob Health. 2016; 4: e287Summary Full Text Full Text PDF PubMed Scopus (16) Google Scholar Withdrawal of support from the Wellcome Trust and PEPFAR is a major setback for research development in Africa. Additional challenges include the need to develop multidisciplinary research team approaches, bridge the knowledge translation gap, and find local sustainable African research leadership. But can all of this be done at reasonable cost? MicroResearch, modelled on microfinance, is an innovative African/Canadian research partnership, which was launched in 2008. The project is aimed at building local health-care professionals' capacity to find solutions for community maternal and child health problems by: (1) training multidisciplinary local teams to identify health problems; (2) coaching teams to develop their question into a scientifically rigorous research proposal; (3) after local ethics approval, providing small funds (CAN$2000); (4) coaching teams to conduct the project and translating findings into action; (5) sharing findings through publication and forums; and (6) growing local MicroResearch African leadership.3MacDonald NE Bortolussi R Kabakyenga J et al.MicroResearch: finding sustainable local health solutions in East Africa through small local research studies.J Epidemiology Glob Health. 2014; 4: 185-193Crossref PubMed Scopus (11) Google Scholar By 2016, 27 workshops were completed with more than 700 African health professionals trained, 50 team proposals launched, 22 completed, and 22 publications, all in a gender equitable manner. Several MicroResearch projects have already led to local programme and policy changes.3MacDonald NE Bortolussi R Kabakyenga J et al.MicroResearch: finding sustainable local health solutions in East Africa through small local research studies.J Epidemiology Glob Health. 2014; 4: 185-193Crossref PubMed Scopus (11) Google Scholar All of this has been achieved for less than CAN$500 000. Thus, building research capacity for health-care worker teams to find local solutions that fit culture, context, and resources, can be done at low cost. We declare no competing interests. Research capacity in Africa—will the sun rise again?Africa has a problem. It has the greatest burden of disease and lowest density of health-care professionals in the world. This we know. We also know that although infectious diseases and maternal, child, and neonatal health are improving, the burden of non-communicable diseases (NCDs) has been steadily increasing in the past few decades. We know that the health-care successes in Africa have largely been driven by donor aid, providing vertical solutions to specific problems; however, NCDs require complex care and strong health systems. Full-Text PDF Open AccessResearch capacity in Africa—will the sun rise again?Africa has a problem. It has the greatest burden of disease and lowest density of health-care professionals in the world. This we know. We also know that although infectious diseases and maternal, child, and neonatal health are improving, the burden of non-communicable diseases (NCDs) has been steadily increasing in the past few decades. We know that the health-care successes in Africa have largely been driven by donor aid, providing vertical solutions to specific problems; however, NCDs require complex care and strong health systems. Full-Text PDF Open AccessMicroResearch: an effective approach to local research capacity developmentDespite efforts by the international community to increase research capacity in sub-Saharan Africa, significant challenges remain.1,2 Traditional approaches neglect the basic deficits in Africa's research capacity, including funding, leadership, and skills to identify and solve local community health problems. Full-Text PDF Open Access
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.
How this classification was reachedexpand
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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".