Engagement in the Knowledge Economy: Regional Patterns of Content Creation with a Focus on Sub-Saharan Africa
Bibliographic record
Abstract
Increasing digital connectivity has sparked many hopes for the democratization of information and knowledge production in sub-Saharan Africa. To investigate the patterns of knowledge creation in the region compared to other world regions, we examine three key metrics: spatial distributions of academic articles (traditional knowledge production), collaborative software development, and Internet domain registrations (digitally mediated knowledge production). We find that, contrary to the expectation that digital content is more evenly geographically distributed than academic articles, the global and regional patterns of collaborative coding and domain registrations are more uneven than those of academic articles. Despite hopes for democratization afforded by the information revolution, sub-Saharan Africa produces a smaller share of digital content than academic articles. Our results suggest the factors often framed as catalysts in the transformation into a knowledge economy do not relate to the three metrics uniformly. While connectivity is an important enabler of digital content creation, it seems to be only a necessary, not a sufficient, condition; wealth, innovation capacity, and public spending on education are also important factors.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 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".