Associations Between Logistics and Economic Growth in Africa
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
Abstract Despite macro‐economic predictions of economic catch‐up and steady‐state economic growth for all countries, in the long run, the gap between advanced and developing African countries is widening. This study investigates the association between logistics and economic growth in 32 African countries from 2007 to 2018. The results show that five of the six logistics performance indicators, under review, have weak positive economic growth effects, ranging between 0.01 and 0.03. Relatively high economic growth effects emerge from the “competence and quality of logistics” indicator. This research highlights that the growth potential in African countries depends on improvements in logistics performance and that prioritising investments to improve logistics efficiency can improve long term growth and development in Africa. Practitioners and policymakers can use the results of this study to target and prioritise specific logistics indicators based on the magnitude of their impact on economic growth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it