Indigenous psychology in disasters: lines of care construction for the “Buen Vivir” of original peoples
Bibliographic record
Abstract
Abstract Objective In 2021, the indigenous communities Pataxó, Pataxó Hãhãhãe and Tupinambá, in the state of Bahia, Brazil, were hit by intense floods. The situation required immediate response from local health professionals, with advice from experts in public health disasters and emergencies. This case study focuses on the development of lines of care for the “Buen Vivir” of affected original peoples through collaborative work between indigenous ethnic groups and public health policy professionals. Method Analysis of the records of meetings, a training course for indigenous health professionals and three reference documents was carried out. Results Possibilities and challenges for assuring the “Buen Vivir” in the post-disaster and public health emergency response phase were addressed, guaranteeing the specificity and protagonism of the communities served. Conclusion Contributions were presented along the lines of care construction processes for the “Buen Vivir” of indigenous peoples, pursuing subsidies for public policies in accordance with the socio-historical-cultural particularities of each ethnic group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".