International and internal migration and the subjective wellbeing of wives left behind in Ghana
Bibliographic record
Abstract
Abstract Husbands' labour migration has ramifications for significant family members, particularly wives left behind. However, limited studies have been conducted to examine the impacts of husbands' migration on women left behind married to international and internal migrants. Drawing on a purposive sampling survey of 298 Ghanaian women (international = 129 and internal = 169) in the Volta Region, we assessed their subjective wellbeing using three dimensions: self‐reported health, self‐reported satisfaction with life, and self‐reported happiness. The results from t‐tests show that on average, international women left behind have higher perceived health (3.72), perceived happiness (3.82) and satisfaction with life (3.19). Results from the multivariable binary logistic regression analyses reveal that while no variables predict self‐reported health for international women left behind, high frequency of communication is statistically associated with internal women left behind self‐assessed health. International women left behind who lived in nuclear households and internal women left behind who reported high wealth quintiles were both statistically associated with satisfaction with life, respectively. While demographic factors (age and duration of marriage) were significant predictors of happiness for international women left behind, neighbourhood type and frequency of communication predicted happiness for internal women left behind. The differences in variables predicting each of the subjective wellbeing dimensions demonstrate the concept's multidimensionality. It also highlights factors influencing subjective wellbeing outcomes of women left behind are not solely due to their husbands' migration. The policy implications of this study are highlighted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".