Nurture : Living in the landscape summer school and exhibition
Bibliographic record
Abstract
The fourth international and interdisciplinary art methods school Living in the Landscape (LiLa) took place in between March and October 2023. This series of schools is organized by the University of Arctic’s thematic network Arctic Sustainable Art and Design (ASAD). This year (2023) we have undertaken another hybrid delivery with in situ site working in Umeå and the High Coast area of Sweden. The participating MA and PhD students and scholars this year came from several ASAD partner institutions: Umeå University (Sweden), the University of Lapland (Finland), Nord University (Norway), the University of the West of Scotland (Scotland), the University of the Highlands and Islands (Scotland), Yukon School of Art (Canada), and University of Alaska, Anchorage (Canada). The participants came from the disciplines of art education, general teacher education, fine arts, creative practice, and clothing design. This publication presents the art-based results and exhibition of the summer school and the landscape studies of the participants in the form of visual essays. The exhibition has been on display at Umeå University’s teacher education department in November 2023.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".