Experiences of Visible Minority Transnational Carer-employees
Bibliographic record
Abstract
Geographical isolation and a lack of gender-sensitive and caregiver-friendly workplace policies (CFWPs) in work settings lead to adverse impacts on the economic, emotional, and physical health of Transnational Carer-Employees (TCEs). TCEs are employed immigrants who engage in caregiving to their loved ones across borders while residing in the host country. The secondary analysis conducted herein looked at the experiences, commonalities, and differences among 29 TCEs from Pakistani, Syrian, African, and South American backgrounds living in London, Ontario, before and after COVID-19. Constructivism and intersectionality informed thematic analysis of the data highlighted that among the respondents, care is a religious obligation, influenced by culture as the eldest child or those living abroad are expected to help family back home and that men provide more financial caregiving whereas women divulge in higher physical and emotional care. Results also exhibit that TCEs work in low-skilled jobs due to a lack of English proficiency, care is limited because of financial barriers, and employer support, financial relief, and increased vacation time are the recommendations by TCEs for workplace policies. This thesis further showcases that there are more similarities than differences between the four visible minority cohorts. Most participants observed satisfaction after providing transnational care, whereas a few interviewees of Syrian and African origin reported feeling overwhelmed. While many TCEs observed low income and decreased work opportunities after COVID-19, a few participants of African ethnicity, working in essential services, disclosed an increased workload post-pandemic. This research reveals that to manage their care and work duties, visible minority TCEs apply four common coping strategies in their lives: praying, keeping busy, staying active, and family support. Implications of this thesis include the promotion of CFWPs in places of employment to sustain the welfare of TCEs and the Canadian economy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".