The Forest for the Trees: Trade, Investment and the China-in-Africa Discourse
Bibliographic record
Abstract
Trade and investment are topics central to the China-in-Africa discourse that has strongly emerged from the West in the last few years. Western opinion leaders, along with several African opposition parties, often characterize China's role in Africa as "colonialist," "neo-imperialist" or "predatory." Placing China's trade and investment in the continent in comparative perspective, the paper assesses the empirical validity of such charges, by examining those issues that receive disproportionate attention in the discourse: China's importation of oil from Africa, her exports of textiles and clothing to Africa and to the world in competition with Africa, as well as her ownership of a Zambian copper mine. It is concluded that China, as part of the world capitalist economy, injures African interests in many of the same ways as the principal Western states. The racialized China-in-Africa discourse, however, is largely inaccurate, reflective of Western elite perceptions of China as a strategic competitor, and acts as an obstacle to an effective critique of exploitative links between Africa and the more developed states.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".