Countering colonial nostalgia and heroic masculinity in the age of accelerated climate change: The Arctic artworks of Katja Aglert and Isaac Julien
Bibliographic record
Abstract
This article explores two screen-based artworks: Katja Aglert’s Winter Event – Antifreeze (2009–18) and Isaac Julien’s True North (2004) respectively, that exemplify diverse viewpoints contesting the essentialized identities of the Arctic past. These artworks recover the histories of women, the Inuit and African American men’s involvement in polar exploration, reimagining heroic narratives from historically excluded or ignored perspectives. By employing irony and humour, these artworks expand our understanding of how media-based art can respond to the ironies of a warming planet and challenge colonial nostalgia for White male heroism. The artworks traverse not just the human imperialism of the colonial era but also the newer imperialism in the age of the Anthropocene and the Capitalocene, decentring the mythic and exotic qualities of expedition narratives. Ultimately, the irreverent artwork encourages us to rethink an aesthetics of the distanced sublime from Romantic aesthetics and its roots in European Universalism, promoting a more inclusive and intersectional approach to the Arctic and its representation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".