Global Knowledge on the Move: Itineraries, Amerindian Narratives, and Deep Histories of Science
Bibliographic record
Abstract
Since Bruno Latour's discussion of a Sakhalin island map used by La Pérouse as part of a global network of "immutable mobiles," the commensurability of European and non-European knowledge has become an important issue for historians of science. But recent studies have challenged these dichotomous categories as reductive and inadequate for understanding the fluid nature of identities, their relational origins, and their historically constituted character. Itineraries of knowledge transfer, traced in the wake of objects and individuals, offer a powerful heuristic alternative, bypassing artificial epistemological divides and avoiding the limited scale of national or monolingual frames. Approaches that place undue emphasis either on the omnipotence of the imperial center or the centrality of the colonial periphery see only half the picture. Instead, practices of knowledge collection, codification, elaboration, and dissemination--in European, indigenous, and mixed or hybrid contexts--can be better understood by following their moveable parts, with a keen sensitivity toward non-normative epistemologies and more profound temporal frameworks.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.043 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".