An Inventory of Allegations of Anti-Competitive Practices in Sub-Saharan Africa
Bibliographic record
Abstract
This paper summarises our efforts to date to assemble a comprehensive database of allegations of anti-competitive practices made in Sub-Saharan Africa publications, principally in newspapers and other periodicals. Although the findings from this approach must be interpreted with care, we believe this paper represents the first comprehensive attempt to assess the prevalence of different types of anti-competitive practices in Sub-Saharan Africa. So far we have located 120 distinct allegations of anti-competitive practices in 68 lines of business in 12 African nations since 1995. By a large margin the most frequent allegation concerns cartels, especially outside of South Africa. Allegations against foreign firms, some of which are African, range between a quarter and two-fifths of the total number of allegations, suggesting that plenty of domestic firms are the subject of allegations too. There are 12 lines of business where allegations are made in more than one Sub-Saharan African country. Many of those lines of business directly affect the well-being of the poor, those employed in the agricultural sector, and small business.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.027 | 0.037 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".