Liberalisation and the regional air network configuration from Nigeria to other West African Countries
Bibliographic record
Abstract
This paper examines the liberalisation and the regional air network configuration from Nigeria to other West African regions. It aims to study the impacts of liberalisation on the regional spatial structure of air networks from Nigeria to West Africa in the pre and post-liberalisation. The pre-liberalisation covers between 1988–2000, and the post-liberalisation ranges from 2001 to 2018. The methodology involves using the graph theory to calculate the route and the network topology in the pre and post-liberalisation and compare the resulting index. This hypothesis was tested using the alpha index. The alpha index analysis compares the level of connection in a pre-and post-liberalisation network via graphical depictions of each period’s route and network structure and the resulting alpha index. The pre-liberalisation alpha index for the route and network was 0.297, while the post-liberalisation alpha index was 0.334. The alpha index ranged from 0 to 1 and was the perfect network for the post‐liberalisation period. In post-liberalisation, the alpha index of the route and network are higher than in pre-liberalisation. Hence, the connection is better in post-liberalisation.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".