From Migrant to Transnational Families’ Mental Health: An Ethnography of Five Mexican Families Participating in Agricultural Labour in Canada
Bibliographic record
Abstract
This focused critical ethnography aimed to deepen our understanding of the impact of participating in a temporary, cyclical, low-wage migration program on the mental and emotional health (MEH) of Mexican women and their non-migrating family members. Except for global care chains research, the field of migrant mental health has paid limited attention to the importance of transnational family dynamics and the MEH of relatives beyond the workers’ children. The current study broadens this framework to examine how family-level changes brought about by migration affect the MEH not only the migrant and her children, but also extended family members. Participants included five women employed in the Canadian Seasonal Agricultural Worker Program and an average of five non-migrating members of their families in Mexico. The study combined four data generation methods: participant observation, ‘emojional’ calendars, semi-structured interviews, and sociodemographic questionnaires. Study participants’ MEH was significantly influenced by gendered selection processes and the cyclical pattern of migration. Similar impacts were observed within and across four groups of participants (workers, their children, the children’s caregivers, and extended family members) during their periods apart and together. There were significant effects of their relative’s migration on the MEH of extended family members, a population group commonly overlooked in the literature. Findings from this study suggest that public health research, programs, and policies using a transnational approach are best suited to effectively address the impacts of migration on the MEH of migrants and their non-migrating families.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".