Caregiving Across International Borders: a Systematic Review of Literature on Transnational Carer-Employees
Bibliographic record
Abstract
In diaspora and transnational studies little is known about the experiences of transnational carer-employees (TCEs). TCEs provide unpaid/informal care across international borders to an adult family member, friend, or relative with disability and/or age-related needs, while also working in paid employment in the country of resettlement. The primary focus of this systematic review was to examine how cultural and historical elements of transnational caregiving influence the economic, social, and health/well-being of TCEs. This systematic review draws on quantitative and qualitative peer-reviewed literature on TCEs' experiences from Canada, the USA, or Australia between 1997 and 2017. In all, 16 articles that fulfilled the search inclusion criteria were selected. The articles were analyzed using content and thematic analysis. The review highlighted that transnational caregiving is a multi-dimensional phenomenon. There is a reciprocal relationship between adult children providing care to their parents and parents helping their children resettle in their new home. The findings suggest that TCEs provide practical, financial, and emotional care to their families abroad. To the best of our knowledge, this is the first comprehensive systematic review of the experiences of TCEs. Increasingly complex immigration experiences of transnational families require innovative policy responses from a transnational and intersectionality lens. Immigrants need support to maintain solid transnational networks and simultaneously adapt to the country of resettlement. Employers can use the findings to support TCEs in balancing unpaid care across vast geographical distances while sustaining their economic and social well-being.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".