Gold and green forests : Crafted life stories about Canadian Goldenrod and elm trees
Bibliographic record
Abstract
Sweden's fauna and flora are constantly changing. Humans have not only deliberately promoted and introduced new species in horticulture, agriculture and forestry, they have also acted as a vector for the introduction of alien species through, for example, transportation and food. When these species spread rapidly and affect biodiversity, they are deemed ‘invasive alien species’. This artistic research project explores and articulates how humans, as part of a system where nature and culture meet, affect complex functioning ecosystems through the movement of species. The starting point is the iconic elm tree and how its cultural and natural ecosystems have been wiped out in large parts of Europe by the invasive fungus Ophistoma novo ulmi. With the extinction of the elm come ecological and cultural losses. Those losses are examined and interpreted in this work, in a dialogue with nature and with people. At the same time, another species is explored, the Canadian goldenrod, which, unlike the elm, is expanding rapidly. With these explorations, life stories about the elm will be created not only for our collective memory, but also for speculation about what happens when a new and invasive alien species, such as the Canadian goldenrod, spreads. The form of my narrative is based in materials, crafts and objects. It is primarily the objects and the process that are the carriers of the stories. As a ceramicist, I use clay as a sketching material, binder and a tool for documentation. These species, the elm and the goldenrod, constitute the materiality that are part of the exploration and creation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".