Liberalisation and the regional air network configuration from Nigeria to other West African Countries
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
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.
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.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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