2 - The Migration and Informal Market Nexus: A study of Nigerien Forex Traders in Benin City
Bibliographic record
Abstract
This article attempts to understand how migrant communities in the global South shape and contribute to the establishment and operation of niche sectors and informal markets in receiving states. The article examines the impact that a community of migrants from Niger Republic have had on the foreign exchange market in Benin City, Edo State, Nigeria. The analysis is situated within the postcolonial framework while drawing on sociological frameworks and methodological tools (ethnography). By analysing the narratives of Nigerien migrants in Benin City, this paper unpacks the characteristics of the migrant forex niche, the interaction between the formal and informal forex businesses in the market, as well as the interplay between migrants and locals in the community. We argue that the nexus of intra- African migrations and informal niche markets leads to spatial, political, economic and social transformations that challenge the significance of formal markets and the limitations of undocumented status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".