Research excellence in Africa: Policies, perceptions, and performance
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
<p>Our paper discusses various\nfeatures of research excellence in Africa, framed within the context of African\nscience granting councils and pan-African research excellence initiatives. Our\nsurvey, collecting responses from 106 researchers and research coordinators\nacross Africa, highlights the diversity of opinions and preferences with\nregards to Africa-relevant dimensions of research excellence and related\nperformance indicators. </p><p>The results of the survey confirm\nthat research excellence is a highly multidimensional concept. Our analysis\nshows how some of those dimensions can be operationalised into quantifiable\nindicators that may suit evidence-based policy discourses on research quality\nin Africa, as well as research performance assessments by African science\ngranting councils. Our indicator case study, dealing with the top 1% most\nhighly cited research publications, identifies several niches of\ninternational-level research excellence in the African continent while\nhighlighting the role of scientific cooperation as a driving force. </p><p>\n\n\n\nTo\ngain a deeper understanding of research excellence in Africa, it is important\nto take into account the practical challenges faced by researchers and research\nfunding agencies to align and reconcile socioeconomic interests with\ninternational notions of excellence\nand associated research performance indicators. African research excellence\nshould be customised and contextualised\nin order to be responsive to African needs and circumstances. <br /></p>
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 | 0.072 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.071 | 0.109 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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