Reflections on return migration: Understanding how African immigrants in Canada contemplate return
Bibliographic record
Abstract
Abstract Even though research on return migration has flourished in the last decade, we still know very little about how immigrants contemplate the decision to return to the homeland. Using multinomial logistic regression, we examined the variables underpinning the return intentions of African immigrants in Canada—specifically, Ghanaians and Somalis in Toronto and Vancouver. Our key independent variables included immigrants’ socioeconomic characteristics, their time‐ and place‐utility factors, their attachments to the homeland, their integration into the Canadian society and their perceived levels of racism in Canada. We found that respondents who were born in Somalia were less likely to have return intentions, compared with those who were born in Ghana. Also, those who lived in Toronto were more likely to have return intentions relative to those who lived in Vancouver. Moreover, those who perceived the level of racism in Canada to be high were more likely to have return intentions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".