Diversification, Intensification and Specialization: Changing Land Use in Western Africa from 1800 BC to AD 1500
Bibliographic record
Abstract
Many societal and environmental changes occurred between the 2nd millennium BC and the middle of the 2nd millennium AD in western Africa. Key amongst these were changes in land use due to the spread and development of agricultural strategies, which may have had widespread consequences for the climate, hydrology, biodiversity, and ecosystem services of the region. Quantification of these land-use influences and potential feedbacks between human and natural systems is controversial, however, in part because the archaeological and historical record is highly fragmented in time and space. To improve our understanding of how humans contributed to the development of African landscapes, we developed an atlas of land-use practices in western Africa for nine time-windows over the period 1800 BC–AD 1500. The maps are based on a broad synthesis of archaeological, archaeobotanical, archaeozoological, historical, linguistic, genetic, and ethnographic data, and present land use in 12 basic categories. The main differences between categories is the relative reliance on, and variety of, domesticated plant and animal species utilized, and the energy invested in cultivating or keeping them. The maps highlight the irregular and frequently non-linear trajectory of land-use change in the prehistory of western Africa. Representing an original attempt to produce rigorous spatial synthesis from diverse sources, the atlas will be useful for a range of studies of human–environment interactions in the past, and highlight major spatial and temporal gaps in data that may guide future field studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".