The multiperspectival nature of place names: Ewenki mobility, river naming, and relationships with animals, spirits, and landscapes
Bibliographic record
Abstract
Abstract The article examines the process of production and change of place names based on data collected in 2017 among the Okhotsk Ewenki, the easternmost Indigenous community in Siberia, Russia. Through ethnographic and semiotic analysis, we show that Ewenki place names are not simply reproduced, but rather generated and transformed through empathic contact and engagement within a semiotic circle of shared knowledge and praxis among humans and other beings encountered, especially in ambulatory travel. We consider place names as complex signs which evolve from landscape, mobility as a spatial practice, and relationships with nonhuman beings. Through ecosemiotics and nonhuman ontology, we examine how the concept of shifting landscapes and interactions with different environmental agents, especially animals, contribute to the production of space and place names and their changes. We also show that the responsible voicing of the land with place names is related to Ewenki understandings of territorial prerogatives, and rights, which are perceived as being shared with other beings.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".