Transnational Families in North America: Migration Trends, Policy Implications, and Well-being
Bibliographic record
Abstract
Transnational families in Canada, Mexico, and the United States (i.e., North America) face significant challenges to family cohesion and overall health as they navigate new cultural and sociopolitical contexts. Transnational family members, who maintain connections across national borders due to immigration, have unique stressors and strains impacting their psychological, social, and economic well-being, such as adjustment to new roles and shifting communication patterns. The current review explores migration trends in North America, the various consequences of caregiving across borders, and the nuances of transnational parenting. Guided by the transnationalism framework and family system theory, this review highlights the lived experiences of transnational families and broadly examines existing policies designed to support these families. By reviewing international reunification policies across Canada, Mexico, and the United States, this chapter identifies gaps and key areas where policy adjustments could better address the needs of these families. Our recommendations emphasize the necessity for more nuanced and collaborative policy approaches to augment support structures that enhance the health and well-being of transnational family systems. This review aims to provide actionable insights for policymakers in building a healthier future for all families of this demographic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".