Ambitions, Profits and Loss: Zimbabwean Economic Involvement in the Democratic Republic of the Congo
Bibliographic record
Abstract
Accounts of recent Zimbabwean economic involvement in the Democratic Republic of the Congo (DRC) focus on commercial activities by military officials and political elites, and suggest that these groups' business interests precipitated Zimbabwe's involvement in the conflict. Such accounts obscure the real scope and extent of interest by the Zimbabwean business community in the DRC and ignore the historical context in which economic involvement has occurred, as well as the difficulties. Based on interviews with Zimbabwean entrepreneurs and government officials, this article analyses the circumstances under which entrepreneurs sought opportunities in a nation virtually unknown to Zimbabweans prior to 1997. It explores the effect of poor domestic economic conditions and previous Zimbabwean military involvement (but subsequent lack of business penetration) in Mozambique, on government and business resolve to exploit opportunities in the DRC. Further, it argues that military involvement was not initially motivated by profit. Rather, entrepreneurs followed military actors once military networks were in place, as entrepreneurs (and military personnel themselves) realized the commercial value of these networks.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".