Accelerating foreign direct investment flow to Africa: from policy statements to successful strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – The growing investment gap and the declining foreign aid in recent years have compelled many African countries to turn to foreign direct investment (FDI) as a means to avoid development financing constraints. This article seeks to examine the performance of FDI flow to various regions and countries in Africa and the implication(s) on FDI of the recently launched new partnership for Africa's Development (NEPAD) programs. Design/methodology/approach - Explores strategies for accelerating the flow of FDI to Africa, especially the implications of NEPAD programs. Findings -Africa's FDI inflows are highly uneven both between regions and between countries depending on economic and political environment. In addition, if implemented successfully, NEPAD programs would help spur the flow of FDI to Africa. Originality/value - Besides the socio-economic policy recommendations, suggests marketing strategies to help increase the flow of FDI to Africa.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it