Bibliographic record
Abstract
The global attention paid to cash remittances over the past decade has resulted in an extremely solid evidence base on international, regional and national level remitting behaviour and impacts. Little attention, however, has been paid to food remitting and its development contribution, including to the welfare and food security of sending and receiving migrant households. A review of the current state of knowledge about food remitting found considerable knowledge gaps in our understanding of the volume, driver and impacts of this phenomenon. In this paper, food remittance data from five multi-country household surveys and case study evidence are marshalled in order to demonstrate that food remitting is an important accompaniment to migration which demands much greater research attention. The paper uses the existing data to show that there is considerable spatial variability in the amounts, frequency and types of foodstuffs that flow to and from migrant origin and destination areas within countries and across borders. Both poor and better-off households in many rural areas remit food, a practice that enhances urban food security. Rural–rural, urban–urban and urban–rural food remitting are also growing in significance. Research on the relationship between remittances and development can no longer afford to ignore this neglected but extremely important form of remitting.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".