Forced international migration for refugee food: a scoping review
Bibliographic record
Abstract
Recent crisis and conflicts in African countries, the Middle East and the Americas have led to forced population migration and rekindled concern about food security. This article aims to map in the scientific literature the implications of forced migration on food and nutrition of refugees. Scoping Review, and database search: databases: PubMed Central, LILACS, SciElo, Science Direct and MEDLINE. Languages used in the survey were: English, Portuguese and Spanish, with publication year from 2013 to 2018. 173 articles were obtained and after removing of duplicates and full reading, 26 articles were selected and submitted to critical reading by two reviewers, resulting in 18 articles selected. From the analysis of the resulting articles, the following categories emerged: Food Inequity; Cultural Adaptation and Nutrition; Emerging Diseases and Strategies for the Promotion of Nutritional Health. Food insecurity is a marked consequence of forced international migration, and constitutes an emerging global public health problem, since concomitant with increasing population displacements also widens the range of chronic and nutritional diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".