Migration in West Africa: a visual analysis of motivation, causes, and routes
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
Migration in West Africa has been taking place for centuries for different reasons. Many dimensions of migration remain insufficiently documented and poorly understood. In particular, factors of migration in destination areas and areas of origin are still lacking comprehensive analysis. In this paper, we bring a new perspective to the model of push and pull factors of migration in West Africa by reviewing and analyzing interview-based case studies of migration related to Ghana, Burkina Faso, and Nigeria, as well as to the associated migration routes. The overall aim of this study was to determine the areas that individuals historically chose as destinations for migration and what they perceived to be the distinctive conditions in those areas. Hence, characteristic features about destination areas and areas of origin were identified and located in maps, whereas interrelationships among push and pull factors were illustrated by means of Sankey diagrams. With these tools, we provide a novel combination for visualizing the reasons for migration. The literature review emphasizes the complex relationships between different drivers of migration, with environmental and economic factors emerging as the most important drivers of migration in the focus countries. Moreover, the identified and mapped migration patterns suggest that individuals migrate mainly from the northern part of a particular country to its center or southern regions. This scientific approach shows that the spatial allocation of migratory movements can facilitate assessments on how to meet specific Sustainable Development Goals and to improve regional policies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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