Can’t carve air, can’t weave names: Plant species used in Colombian artisan crafts are not equally assessed for vulnerability at the international and national level
Bibliographic record
Abstract
Abstract Humanity has maintained cultural connections with our environments for time immemorial. Plants and artisan crafts are a prime example, as craft purpose, skill, design, and species used can vary greatly between communities and the loss of a critical plant species can result in a loss of access to cultural craft practices. To mitigate global biodiversity loss, conservationists are faced with the challenge of assessing species vulnerability to extinction and prioritizing species for conservation funding using information instruments, like the IUCN red list. This process does not necessarily consider a species’ cultural importance. In this paper we sought to address this gap for plant species used in artisan crafts in Colombia. We aim to answer the following: (1) how represented are endemic species in artisan crafts; (2) how threatened are artisan craft species according to (a) international and (b) national vulnerability status? We used the number of species-associated common names as a proxy for cultural awareness. We found that continentally regional species were far more represented in Colombian artisan crafts than national endemics. We also found a strong positive relationship between number of common names and national vulnerability assessment status, but no statistically significant relationship for international vulnerability status. Based on our results, well-known plants used in Colombian artisan crafts are more likely to be assessed nationally than internationally. While the IUCN is thorough in their recommendations, more can be done to prioritize the inclusion of conservation assessments for species based on their contributions to cultural diversity. Positionality statement We are 14 scientists and practitioners who are deeply committed to the conservation of nature and culture in a changing world. We are trained in diverse fields including ecology, evolutionary biology, botany, music, anthropology, law, and public health. We all have postgraduate academic education (Masters or PhDs underway) but most of us are early career scholars. Six of us grew up in Colombia and we represent many places including Mexico, the United States, Ireland, Chile, Brazil, Germany, and Viet Nam. None of us self-identify as Indigenous.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".