Bibliographic record
Abstract
By the 2010s, the view that state mismanagement and inefficiencies underlay the Congo’s economic malaise had become so commonplace as to permeate nearly all thinking about development in the country. The aim of this chapter is to challenge this line of thinking and question the Consensus wisdom of moving from domestic-owned to foreign-owned industrial mining based on a belief in the superior efficiency of the latter. By charting the rise and fall of Belgian-owned SOMINKI (1976-1997) and Canadian-owned Banro (1995-2019) in eastern Congo, its main line of argument is that foreign-owned and managed mining corporations are no less vulnerable to mismanagement, firm inefficiencies, and volatile prices than their state-owned counterparts. This included, in the case of Banro, rent-seeking behaviour, redirecting value to overseas directors and shareholders at the expense of productive capacity and to the detriment of the Congolese state and Congolese firms and labour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.926 | 0.907 |
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; both teacher heads agree on what is shown here.
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".