GOLD STANDARD PRESERVATION: ASSESSING THE EFFECTS OF FREEZING GILDED INSECTS FOR INTEGRATED PEST MANAGEMENT, AND A CRITICAL DIALOGUE ON ART–SCIENCE COLLABORATION
Bibliographic record
Abstract
Abstract In 2018, artist Cole Swanson created Monument , an evolving installation of reclaimed insects gilded in 24-karat gold leaf. Ahead of its 2024 exhibition at the Canadian Museum of Nature, Swanson partnered with conservator Erika Range to explore whether these delicate, composite specimens could safely undergo the museum’s integrated pest management (IPM) freezing protocol. Nine insects were selected and examined before and after freezing using high-resolution imaging and scanning electron microscopy (SEM). No physical damage was observed, suggesting freezing may be viable for similarly constructed bio-artworks. Beyond its technical findings, this project emerged as a dialogue between artist and conservator. Through an exchange of perspectives, this article reflects on risk, reversibility, and the shared ethics of care that underpin both artistic and scientific practice. Monument not only prompted procedural adaptation within the museum, but also became a site of interdisciplinary meaning-making. This collaboration demonstrates how material studies can be enriched through art–science partnerships, and how institutional practices may evolve through openness to experimental objects and unconventional knowledge sources. By combining studio and laboratory, aesthetics and analysis, Monument serves as both subject and catalyst for rethinking how we care for the natural world and its representations.
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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 | 0.118 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.035 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".