Analysis of the Competition for the Location of the Optimal Hub in the WAEMU (West African Economic and Monetary Union) Zone
Bibliographic record
Abstract
The objective of this study is to analyze the contribution of governance (political stability) as well as per capita income and traffic past measured through the number of passengers traveling by air during a period of one year within each country of the zone to the formation of a hub in the WAEMU zone. Governance has been apprehended through Kaufman indicators which summarize the six dimensions of governance. Three control variables have been added in the model to better explain per capita income and reduce bias in the estimation. To achieve this objective, the study proceeded first with a descriptive analysis which revealed the existence of a positive linear correlation between governance indicators and the level of air traffic, and then with a dynamic panel approach. To this end, the Generalized Moment Method (GMM) showed that the overall contribution of governance to economic performance is not significant in the sample, as well as for each dimension of governance taken individually. However, the results differ when dissociating the specific effect of Senegal, where political stability, government effectiveness, regulatory quality and rules and laws each have a positive and significant impact on per capita income.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".