Why wouldn’t they return? Examining the return decisions through the integration-transnationalism matrix among Ghanaian immigrants from Canada
Bibliographic record
Abstract
Return migration has gained traction in the last couple of years due to the perceived benefits that are likely to be derived to the migrant, sending country and receiving country. This notwithstanding, research that examines the actual return of Black continental migrants from North America to their sending countries has been few and limited. Drawing upon a qualitative study among 15 Ghanaian return migrants from Canada, this article examines factors that shaped their return within the framework of the integration-transnationalism matrix. Within this framework, findings reveal that migrants who experience integration challenges and those who consider themselves somewhat integrated in Canada do return at some point in their migration experience. For both groups of migrants, push-pull factors such as contributing to the home country, feeling of belonging, challenges finding jobs, as well as discrimination and racism compelled them to make a return. Similarly, both groups of return migrants revealed that technology helped them engage in transnational activities by giving them firsthand information that influenced their return. These findings have implications for policy in both sending and receiving countries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".