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Record W4386929540 · doi:10.7577/formakademisk.5398

Gold and green forests

2023· article· en· W4386929540 on OpenAlexaboutno aff
Anna-Karin Arvidsson

Bibliographic record

VenueFormAkademisk - forskningstidsskrift for design og designdidaktikk · 2023
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsnot available
Fundersnot available
KeywordsAlienNarrativeMateriality (auditing)DocumentationEcosystemBiodiversityTourismEcologyAlien speciesGeographyAgroforestryIntroduced speciesBiologySociologyAestheticsArtLiteratureArchaeologyComputer science

Abstract

fetched live from OpenAlex

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.064
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0640.016

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.

Opus teacher head0.072
GPT teacher head0.327
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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