'Making it' through migration: success (im)mobility and 'development' in The Gambia
Bibliographic record
Abstract
Contemporary scholarly and journalistic literature consistently represents migration from and through The Gambia using the lens of “crisis”. While these representations normally focus on Gambian migration to European states – a movement that is highly politicized – this thesis presents a case study of Gambian migration to a less-politicized destination, North America, in order to explore the relationship between lived experiences and representations of migration absent the discourse of crisis that pervades other scholarly and journalistic works. Drawing on the mobilities paradigm, feminist geographies of migration, critical race theory, transnationalism, and literatures on bordering, humanitarianism and development, I examine, through a multi-sited case study, the experiences of Gambians who migrated to the U.S. and Canada, then compare them to the ways their experiences are represented in The Gambia. I then, through a discourse analysis, compare the relationship between lived experience and representation in the North American case study to the ways that Gambian migrants are portrayed by European actors in attempts to stem or stop migration flows. This thesis reveals that legal status intersects with class and race to impact upon migrants’ lived experiences in North America, the importance of geographic imaginaries as a form of representation in transnational communities, intimate impacts of North American bordering practices within transnational communities, and the use of discursive bordering practices to control and manage migrant flows in The Gambia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".