Africapitalism: A Management Idea for Business in Africa?
Bibliographic record
Abstract
Africapitalism, a term coined by Mr Tony O. Elumelu C.O.N. – a Nigerian banker and economist is an economic philosophy that embodies the private sector’s commitment to the economic transformation of Africa through investments that generate both economic prosperity and social wealth". The concept is fast becoming a buzz word in Africa and expected to gain recognition even beyond the continent. In this chapter, we seek to provide insight about this concept. We link Africapitalism to the broader literature on business and society, and critically interrogate and explore it as a possible management idea for business in Africa in response to the onslaught of global capitalism. We argue that Africapitalism - i.e. the need for the private sector in Africa to commit to the socio-economic development of Africa - is both an imaginative management idea and a creative moral-linguistic artefact, which embodies a new space for appropriating and re-moralising capitalism in Africa. In so doing, we try to re-instate the sense of place and belongingness in the economic globalisation discourse, as a form of economic patriotism, and argue that these are the quintessential distinctiveness of Africapitalism in the global, economic world order. We also highlight emerging issues for further research, and seek to ignite a continued discussion on this theme.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".