A Geographic Theorization of Zongos in Urban Ghana: A Complex Systems Approach
Bibliographic record
Abstract
While Zongos have become a permanent abode for many people, especially migrants in urban Ghana, the dynamics of these communities are quite poorly understood. This paper provides a geographic analysis of the formation of Zongos, drawing heavily on a complex systems approach to explore how various variables, including space, ethnicity, class, citizenship, migration and environmental processes intersect to form and sustain Zongos in Ghana. Essentially, the paper throws more light on the key factors that contribute to the spatial concentration of the urban poor in Zongos and concludes with the consequences of having the urban poor living in highly segregated and economically depressed neighbourhoods in Ghanaian cities. The paper argues that the formation of Zongos is not solely attributable to the fondness of migrants from northern Ghana to live among people of like background while in southern cities, but also because of the exclusionary machinations of the majority and their housing gatekeepers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".