Melting Glaciers and Rising Seas: Indigenous Digital Art in the Arctic and Pacific Islands
Bibliographic record
Abstract
This thesis analyzes two works: Rise: From One Island to Another (2018), a video-poem by Marshallese artist Kathy Jetñil-Kijiner and Kalaaleq artist Aka Niviâna, and Arkhticós Doloros (2019), a poem and performance by Kalaaleq artist Jessie Kleemann. The 350.org production of Rise: From One Island to Another (Rise) demonstrates how climate change is affecting Indigenous communities in Kalaallit Nunaat (“Greenland”) and Aelon Kein Ad (“Marshall Islands”), focusing on glacial melt and severity of floods due to rising sea levels. Arkhticós Doloros presents Kleemann’s personal engagement with melting glaciers in Kalaallit Nunaat. These works are part of a growing movement of Black, Indigenous, and People of Colour (BIPOC) artists who highlight how discourses around the anthropocene— the era in which human activity has significantly altered the environment and climate—do not fully account for the relationship between colonialism and climate change. Indigenous scholars, such as Kyle Whyte (Potawatomi) and Zoe Todd (Métis), argue for a decolonization of the anthropocene that is rooted in Indigenous ways of knowing about the land, waters, and relationships with human and non-human life. Aligned with these scholars, this thesis argues that Rise and Arkhticós Doloros call attention to the need for a decolonization of the anthropocene by advocating for Indigenous communities’ knowledges and experiences. Drawing on Hupa/Yurok/Karuk scholar Cutcha Risling Baldy and Diné scholar Melanie K. Yazzie’s notion of radical relationality—an Indigenous feminist framework that considers decolonization by establishing relationships with and through the waterways—this thesis considers Kalaallit and Marshallese artists’ relationships with and through melting glaciers and rising seas.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".