Research in social anthropology with indigenous peoples in Brazil and the study of social anthropology with autochthonous peoples in the context of Brazil and other National States: Australia, Canada, and Argentina
Bibliographic record
Abstract
The text, “Research in social anthropology with indigenous peoples in Brazil and the study of social anthropology with autochthonous peoples in the context of Brazil and other National States: Australia, Canada, and Argentina”, aims, following the profile of this section of the Anuário Antropológico, to publicize the contributions to the Programme through a brief account of my own trajectory at the PPGAS/DAN/UnB. I begin with the period in which I was a student of the first PhD group, between 1981 and 1988 under the academic direction of Professor Julio Cezar Melatti, period in which I gained a background on the style of social anthropology with indigenous peoples that is undertaken in Brazil, and over thirty-five years, since 1989, as a professor of the DAN and as a CNPq researcher. In the latter period, I collaborated, initially, in two research projects coordinated by Professor Roberto Cardoso de Oliveira, on Styles of Anthropology in National Contexts, and later focusing on Nationality and Ethnicity on Borders. In both cases, I focused my attention on social anthropology with indigenous societies, in Brazil and in other national states – Australia since 1992, Canada since 1995, and more recently Argentina since 2016. On the research line about nationality and ethnicity on borders, I started in 2000, examining the Macushi and Wapishana peoples on the Brazil-Guyana border and, since 2008, my research has included work on the criminalisation of indigenous peoples in the prison system of Roraima. This article aims to highlight the most relevant aspects of my academic production in the discipline, in theoretical and methodological terms, according to my own assessment, and also to demonstrate how the existing academic environment at the PPGAS fosters the development and improvement of practices of the production of knowledge.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".