Revitalizing Conversations: Lessons From and About the Production of Intersubjective and Intercultural Knowledge
Bibliographic record
Abstract
Based on our present working-experience with a Mapuche kimche (sage) and a logko (spiritual and political leader), we aim at intervening in broader debates on the intersubjective and intercultural production of knowledge. To do so, we pay special attention to contemporary mandates and pervasive conceptions about forms of practicing a better, more proper anthropology. We approach the problem from three different viewpoints: (a) discomforts and disagreements with naturalized forms of initiating, certifying, informing, writing, citing, and authorizing knowledge; (b) the Mapuche etiquette to converse properly and its various bets on horizontality; (c) review of our own philosophy of language, particularly the concepts of translation and performativity.
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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 | 0.042 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.029 | 0.091 |
| Scholarly communication | 0.027 | 0.027 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".