Materializing Memory Through Quilted Cod: “Making Fish” as Memorial
Bibliographic record
Abstract
Cod is so central to the history of Newfoundland that the process of salting and drying it is there called “making fish.” For nearly 500 years, Newfoundlanders made fish to ship globally until 1992 when the Canadian government announced an indefinite and ongoing moratorium on its cod fishery, changing the island forever. My presentation is about my own “making fish” from textiles while researching the history of cod in Newfoundland textile arts. When I first cut pieces of fabric into the triangular shapes of a salted cod split, I wanted a garland of quilted fish for my Christmas tree in Montreal. The repetitive gestures of cutting and stitching made me reflect on my ancestors, who wove their own fishing nets to catch and make fish, and who were terribly exploited by the truck system that kept them impoverished despite their labour. I also considered cod’s role in colonialism: it was sent to the West Indies in exchange for molasses and rum—still essential ingredients in Newfoundland—during slavery. I recalled how the moratorium highlighted the urgency of sustainable practices, and remembered my awe at my late Uncle John’s knowledge as he showed me how to cod jig during the summer food fishery. I began integrating his clothes into my quilted fish, making larger splits as comfort objects. A nostalgic impulse thus turned into an art project meant to sustain cultural heritage and personal connections to the past while acknowledging the complex historical meanings of this former food staple.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".