The Collages of Janet Kigusiuq : A Case Study in Inuit Aesthetics
Bibliographic record
Abstract
Presentation at the Inuit Art Society 2024 Annual Meeting, August 16 & 17 in Traverse City, Michigan, United States. https://inuitartsociety.org/ Richard Mohr on “The Collages of Janet Kigusiuq: A Case Study in Inuit Aesthetics” Mohr’s talk celebrates and analyzes the late-life collages of the Baker Lake artist Janet Kigusiuq (1926-2005), and does so as a vehicle to profile some historically fundamental and still common features of Inuit art. In doing so, the presentation hopes to give a reasoned account of what we intuitively understand as Inuit aesthetics and enable collectors of Inuit art to better understand why we love what we love. The talk also briefly suggests that the Kigusiuq collages pose challenges to Inuit art criticism as it is currently conducted. Richard D. Mohr is Professor Emeritus of Philosophy and of the Classics at the University of Illinois at Urbana-Champaign. He has published on Inuit art in Inuit Art Quarterly, Kolaj (Montreal), Above & Beyond (Canadian North), the Proceedings of the 2019 Inuit Studies Conference (Montreal), The Outsider (Chicago), and has frequently contributed articles to the Smithsonian’s annual Arctic Studies Center Newsletter, including “The Umiaks of Little Diomede”(2020). He explains: “We went to the Arctic for Nature but stayed for Culture.” A recorded session of his talk is published on the Youtube channel of Inuit Art Portal, https://www.youtube.com/@theinuitartportalhttps://youtu.be/RJdE0YQzpO4
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".