Imperial vernacular: phytonymy, philology and disciplinarity in the Indo-Pacific, 1800–1900
Bibliographic record
Abstract
This essay examines how Indo-Pacific indigenous plant names went from being viewed as instruments of botanical fieldwork, to being seen primarily as currency in anthropological studies. I trace this attitude to Alexander von Humboldt, who differentiated between indigenous phytonyms with merely local relevance to be used as philological data, and universally applicable Latin plant names. This way of using indigenous plant names underwrote a chauvinistic reading of cultural difference, and was therefore especially attractive to commentators lacking acquaintance with any indigenous language or culture. When New Zealand anthropologists embraced this role for Māori phytonyms in the 1890s, however, they did so possessed of a relatively in-depth understanding of Māori culture and the Māori language. This discussion has three primary aims: to illuminate nineteenth-century scholarly engagements with Indo-Pacific plant classifications, in contrast to a prevailing historiographical emphasis on European disregard for this subject; to analyse how indigenous phytonyms acted as 'boundary objects' interfacing between cultures and disciplines; and to illustrate the politics of scientific disciplinarity in a colonial context.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".