Cultural Keystone Species without Boundaries: A Case Study on Wild Woody Plants of Transhumant People around the Georgia-Turkey Border (Western Lesser Caucasus)
Bibliographic record
Abstract
Understanding plant significance across cultures and borders is a driving goal in ethnobotany. Often, empirical studies aim to highlight and explain variation in plant knowledge and uses between communities across national, geographic, and cultural boundaries. However, such studies underinvestigate commonality of values and practices between communities. In this cross-border study of highland pastoral communities in both Caucasian Georgia and Turkey, we propose and implement an approach that synthesizes Cultural Importance (CI) and Identified Cultural Importance (ICI) indices. We label this method a “Unified Cultural Keystone Species (UCKS)” approach. We demonstrate that such an approach is uniquely capable of perceiving shared Traditional Ecological Knowledge (TEK) and practices across cultures and borders. Our results identify three primary Cultural Keystone Species (CKS) that cut across cultural and political boundaries in the Western Lesser Caucasus. We argue that these findings allow for a more comprehensive understanding of ethnobotanical knowledge and practices in the study area. This, in turn, can enhance conservation and restoration strategies in the study region and beyond by highlighting the breadth of biocultural knowledge and value held within shared traditions and landscapes. By so doing, we show a way to heighten scientific perceptions of the importance of cultural and linguistic connections to environmental well-being in specific places.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".