Bibliographic record
Abstract
This chapter explores two different systems of research oversight in recent Brazilian history: the bureaucracies of the twentieth and twenty-first-century Brazilian state, and approaches developed by A’uwẽ (Xavante) aldeias over the same period in Pimentel Barbosa Indigenous Land. Focusing primarily on genetics-based research, Dent develops the concept of bureaucratic vulnerability. She argues that the way some geneticists have interpreted state regulatory systems regarding biosamples creates additional risks for Indigenous people under study. At the same time, Indigenous groups are placed in a bureaucratic double bind, where non-Indigenous experts are called on to justify and validate their claims in the eyes of the state. The protectionist state regulation contrasts with relationship-based practices that A’uwẽ interlocutors have developed over repeated interaction and years of collaboration with a group of anthropologists and public health researchers. Specifically, A’uwẽ have responded to the dual and interrelated challenges of recognition under a colonial state and the management of outside researchers through the careful modulation of researchers’ affective experience of fieldwork, working to create enduring relationships and mutual obligation.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.041 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".