The coping strategies of ℌmen left behindℍ in the migration process in Ghana
Bibliographic record
Abstract
Previous studies report that independent transnational female migration is growing rapidly in sub-Saharan Africa. Yet, scholarship on the ‘left-behind’ in the migration process largely focuses on women and children, with little attention paid to men left behind. Using qualitative methods, with Folkman et al.’s coping theory, to examine the coping strategies of men left behind in the migration process in Ghana, this study fills an important research gap in the migration and the left-behind literature. Through the snowball sampling method, 12 in-depth interviews were conducted with men in the Accra Metropolis whose spouses were staying abroad. Participants explained that left-behind husbands cope with domestic work and care through support from family relations, careful planning and time management, eating out in food joints, and paid services from domestic workers. Participants also mentioned that these men cope emotionally through social media, religion, regular visits to spouses and engaging in extramarital affairs. The results demonstrate that in the absence of migrant spouses, husbands adapt using a variety of coping mechanisms.
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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 | 0.001 | 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 | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".