Conceptualising the Migration–Food Security Nexus: Lessons from Nepal and Vanuatu
Bibliographic record
Abstract
In the past decade, international development practitioners have increasingly argued that migration improves the food security of households at origin, by providing the capital necessary for agricultural intensification or food purchase. These debates have occurred largely in isolation from a discussion of the values that underpin food production and consumption in the communities that migrants call home. We question the assumption that a shift from an agricultural-based economy to an economy based on remittances increases the ability of communities to secure access to food in the face of rapid economic and cultural change. In this paper, we present two independently conducted studies from Nepal and Vanuatu that investigate the impact of out-migration on local perceptions of agricultural and residential land and the meaning given to food security. Our data reveal that the value changes associated with large-scale out-migration have the potential to make the agricultural sector at origin more vulnerable, unproductive, unsustainable or unattractive, leaving a longer-term impact on food security. We offer some reflections on the implications of these findings for the structure of the migration–food security nexus.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| 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".