The Arctic and Antarctica: Greenland Research Trips 2012 and 2015.
Bibliographic record
Abstract
Two pivotal research trips to Greenland in 2012 and 2015 extended Neudecker’s ongoing research into how the legacy of the Romantic Sublime and limited visual representations shape our perceptions of the Arctic regions. Questioning notions of wilderness in the context of current environmental and geopolitical realities this collection generates new perspectives on the contemporary Sublime. This item documents Neudecker's 2 research trips to Greenland, the first in 2012 that included a 5 day expedition with Inuit subsistence hunters, and the second in 2015 with Project Pressure to document receding glaciers. The research conducted on both trips had a significant impact on the development of subsequent works and exhibitions.Also included in this item is Lamentations, a brief essay by Neudecker reflecting on her experience during her first Greenland expedition and is included in Hinterland , a collection of essays about her work which was published by the Trondheim Kunstmuseum, in 2014. and was edited by Pontus Kyander, Director of Trondheim Kunstmuseum, Norway. Photography by Mariele Neudecker. Images used with permission. A feature in the Guardian's In Pictures documents Neudecker's visit in Greenland Glaciers through an artist's eyes:https://www.theguardian.com/environment/gallery/2016/feb/25/greenland-glaciers-mariele-neudecker-klaus-thymann-project-pressure The work is under copyright and may not be used without permission. Use of this repository acknowledges cooperation with its policies and relevant copyright law.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".