“The cake is in Accra”: a case study on internal migration in Ghana
Bibliographic record
Abstract
What are the motivations for internal migration, and how do social relations influence the migration process? In answering these questions, this paper focuses on internal migration to Accra, the capital of Ghana. Qualitative interviews were conducted with 20 migrants in different areas of the city and analysed using narrative analysis. We found that livelihood and lifestyle dimensions work in tandem as motivations for migration. While the main reasons for moving to Accra, according to the interviewees, are related to livelihood, they are reflected and performed in culturally bound lifestyles. Furthermore, while social relations are rarely the main motivator to migrate, the social networks of migrants constitute an important enabling (or disabling) factor in shaping both livelihood and lifestyle dimensions of the migration process. Finally, we found that different ties – including emotional and economic – have different meanings across the migrants’ social network throughout the migration process.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".