Bibliographic record
Abstract
My work confronts the aftermath of war. In my woven and dyed pieces, I reflect upon the impact of war on my ÈmigrÈ Latvian household imbued with the memories of the refugee survivors. My work addresses the reality of living in Canada, within a family and a culture divided by the Iron Curtain. My use of visual icons to investigate the dislocation, historical context, personal fear, and cultural mythology reveals that the perception of my family was as much a product of the immigrant imagination as it was the experience of the Cold War. I moved to the United States in the weeks before Sept. 11, 2001. Now living in a country fighting two wars, both in the name of democracy (Operation Iraqi Freedom and Operation Enduring Freedom), the psychological legacy of my own family's experience produced discomfort and anxiety. My examination and reflections on these wars led me to produce a textile installation displaying woven portraits of the eyes of the fallen soldiers. To date I have woven all 157 Canadian solders who have died in Afghanistan and 160 US soldiers, just 2.7% of the over 6,000 who have died in both wars. The installation serves as a space of reflection, provoking a confrontation of the incongruities between the messianic mythology of war and its devastating personal repercussions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".