Bibliographic record
Abstract
In a combined Masters of Fine Art Thesis exhibition and dossier, entitled Across Boundaries, I focus primarily on transformational, productive labour as an important theoretical approach to help acknowledge the silenced trauma surrounding the Korean War in North America. My art practice focuses on an exploration of a hybrid, diasporic identity where I am situated between two cultures—my ancestral home, Korea, and the home where I was raised, Canada. Through my research trip to South Korea, I was able to discover the difficulties of the war that the two Koreas face and that is kept separate from the West. I found that the kind of traumatic losses in the war exists in what Jacques Ranciere calls the “unrepresentable.” I am driven by an installation and performance art practice that allows me to empathize with the ongoing victims of the war.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".