A inversão do COVID-19: equivocação controlada de infraestruturas de informação a partir do xamanismo ameríndio
Bibliographic record
Abstract
A pandemia do coronavírus COVID-19 revelou fragilidades nos sistemas sócio-técnicos modernos. No Sul global, ela tornou visível o projeto político/empresarial que se beneficia de opressões enquanto se esquiva de discursos internacionais de preservação das pessoas e da natureza. Através do entrelaçamento dos conceitos de inversão infraestrutural, dos estudos de infraestrutura, com os conceitos de Omama, Urihi-a, Hutukara e Xawara do xamanismo yanomami, este ensaio busca compreender as conexões político-ecológicas que se tornaram aparentes durante o fenômeno da pandemia no Brasil. O trabalho reconstrói a narrativa da pandemia a partir do mapeamento das relações históricas de opressões que emergiram durante este processo. O texto se encerra com reflexões e apontamentos metodológicos sobre possibilidades de mudança de foco nas práticas de projetos de infraestruturas de informação a partir do pensamento ameríndio.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".