Missing persons response: national programs and global cooperation in Brazil’s migration context
Bibliographic record
Abstract
• Identifies programs in countries linked to Brazilian immigration. • Addresses the challenge of transnational disappearances and the need for cooperation. • Describes INTERPOL’s I-Familia as a global DNA database for humanitarian identification. • Identifies structural and legal barriers to international DNA cooperation. • Proposes policy recommendations for interoperability and ethical data sharing. The search and identification of missing persons represent a pressing global issue with profound humanitarian, legal, and institutional implications. This study presents an illustrative documentary review of MP/UHR identification initiatives in countries selected for their migration-related links to Brazil and their relevance to transnational DNA cooperation (Brazil, Portugal, Spain, France, the United Kingdom, the United States, Canada, Mexico, and Belgium). Grounded in the United Nations guidelines and using peer-reviewed literature, official reports, and documentation from international organizations, the analysis examine how forensic genetics is integrated into MP/UHR workflows, the legal and governance frameworks that enable or constrain the processing of relatives’ reference profiles, and the operational arrangements that support cross-border exchange. The synthesis indicates that identification outcomes depend not only on laboratory capacity, but also on institutional coordination and the linkage of ante-mortem and post-mortem data . The study also describes international mechanisms such as INTERPOL’s I-Familia database, and humanitarian identification platforms. Although these tools show great potential, their effectiveness is limited due to inconsistent adoption across countries and variations in national protocols. The identification of missing persons must be approached as a shared international responsibility, requiring cooperation in science, law, and policy to ensure dignity, truth, and justice for families of the missing.
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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 | 0.018 | 0.035 |
| 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 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".