Operation Acolhida: Peace, health, and communication in the Venezuelan immigrants’ and refugees’ contexts in Brazil: Grassroots report
Bibliographic record
Abstract
Introduction: Operation Acolhida is a pioneering humanitarian initiative in Brazil, bringing together efforts from multiple institutions to assist in the settlement process of Venezuelan refugees. The Operation is a compassionate response organized by the Brazilian government to the humanitarian crisis in Venezuela. The objective of this report is to provide a detailed and well-grounded account of the experiences of Venezuelan immigrants and refugees in Brazil, highlighting the challenges they face, and the strategies implemented for their integration. Methods: An analytical summary of 6 months, of fieldwork experiences supported by a brief review of official documents, and reports from non-governmental organizations. A contextualized analysis of the implemented strategies and resulting outcomes are highlighted to inspire researchers and professionals interested in the intersection of migration settlement actions, population public health, and health communication for individual and collective peace. Results: Operation Acolhida uncovered the synergy among many social and health-related professionals providing essential health services and promoting social and cultural integration as key elements for building lasting community peace. The Operation also tackles the challenge of combating the spread of false news that could lead to xenophobia and stigma against refugees. Effective mass communication was a cornerstone of Operation Acolhida disseminating correct and transparent information and promoting a narrative of empathy and cooperation among Brazilian host communities and Venezuelans. Conclusion: The interrelation between peace and health was undeniable. A peaceful social environment was critical for the maintenance of public health. For that, wide collaboration ensured to the host society’s health robustness contributing thus to collective stability and peace. The presented insights in this grassroots report contribute to the understanding and replication of effective practices in similar humanitarian initiatives globally.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".