Timing and Trajectories: Shifts in Migration and Family Formation Trajectories in Nepal
Bibliographic record
Abstract
Objective: This study identifies distinct pathways of migration, marriage, and childbearing among young men in Nepal, a context characterized by short-term circular migration as well as rapid social and demographic change, and examines how these transitions vary by key socio-demographic characteristics. Background: Migration can transform marriage and childbearing by reshaping economic resources and family arrangements in countries of origin. While a small body of research has explored the fluid relationship between migration and family life, less is known about how these processes unfold in settings experiencing short-term, circular migration alongside broader social and demographic change. Method: Using longitudinal data from the Chitwan Valley Family Study (CVFS), this study employs sequence analysis to explore men's trajectories of migration, marriage, and childbearing. Cluster analysis groups these sequences, which are then examined by birth year, caste-ethnicity, and childhood socioeconomic markers. Results: The majority of men have migration experience. They most often migrate before marriage and frequently reengage after marriage and childbirth, which suggests migration may align with family processes. Migration is more common among younger respondents, reflecting its growing normalization. Caste-ethnicity shapes migration patterns, though its influence appears to shift over time, particularly among historically marginalized groups. Conclusion: This research highlights the diverse nature of male migration in terms of timing and process, as well as how these patterns vary across birth year and caste-ethnicity. Implication: The study underscores the interdependence of migration, marriage, and fertility, identifying migration as a recurrent rather than singular experience in contexts of short-term circular migration and rapid demographic change.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".