Africa Alive Corridors: Transdisciplinary Research based on African Footprints
Bibliographic record
Abstract
Abstract The idea of Africa Alive Corridors (AAC) evolved from Gondwana geological mapping to a comprehensive, more inclusive and dynamic approach to transdisciplinary research known as Earth Stewardship Science. Twenty designated corridors explore the geo-biological and cultural heritage of different regions of Africa over various periods, from deep time to the Anthropocene. Each corridor reveals a specific lens through which to investigate some of the rich scientific narratives embedded within it. The concept also facilitates learning and knowledge exchange across numerous disciplines: archeology, geology, geophysics, oceanography, glaciology, biology, botany, ecology, agriculture, engineering, spatial statistics, social sciences, and the humanities. This contribution analyses ten selected corridors in southern and western Africa, the Congo Basin, East Africa, and Madagascar. The various research themes explored include Earth impact hazard, origins of humankind, Snowball Earth, coastal food systems and conservation, the biogeography of lemurs, human settlement dynamics in Cameroon, tectonically linked earthquake occurrences in Algeria and Morocco, modelling land-use changes in the Western Rift Valley, trades and civilizations of the Mali Empire, Mbira music, and contemporary art. The ongoing work on these—and ten other—corridors has considerable potential to host new international collaborations to develop the links between society and natural sciences in Africa. Ultimately, AAC will benefit all stakeholders, especially the youth, in understanding and responding to societal needs and current global challenges.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".