Silence in the collections -- revealing science stories through Indigenous partnership
Bibliographic record
Abstract
This article reveals the transformational value of Indigenous partnership for understanding the science stories within our collections. Indigenous objects are often poorly catalogued in the collection, with vague descriptions such as, 'perhapes [sic] prepared by Canadian Indians' belying provenance and worse, obscuring the scientific and technological contributions of Indigenous Nations. In this article, Hartman Deetz, a Wampanoag arts and education consultant and tribal citizen, and Milly Mulcahey-Knight, a white, non-Indigenous anthropologist and research assistant at the London Science Museum, collaboratively interpret two objects made of birchbark in the care of the Science Museum Group (SMG). The first is a collection of five pieces of maple sugar, stored in individual conical containers of twisted birchbark. The second is an intricately designed model birchbark canoe. Starting with vague catalogue descriptions, Hartman and Milly detail the use of the maple sugar as a medicinal plant, connected with other medicines and medical technologies in the collection. The model canoe is interpreted as a teaching tool for Ojibwe-style birchbark canoes which turned riverways into transport routes for trade and cultural exchange. This ingenious use of the flexible and waterproof birchbark also left its mark on London. As a central technology of the beaver trade, these canoes were profited off by London's elite and even remembered in the architecture of Oxford Street. The research described took place during the planning of an exhibition at the London Science Museum on Science and Technology in North America in the mid-1700s. Milly and Hartman joined the team as the curators transitioned from a two-year-long research stage into exhibition planning. Hartman acted as a paid independent cultural advisor. Milly was on a four-month placement funded by the White Rose Consortium as part of her PhD research into Indigenous and non-Indigenous partnerships in heritage work. In partnership they identified objects and interpreted Indigenous science stories, to enrich the exhibition and collections interpretations. Overall, this article demonstrates that collaborative interpretation with Indigenous experts not only adds detail to the SMG and Wellcome Collection catalogues but challenges the silencing of Indigenous contributions to science and technology.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.045 | 0.070 |
| Scholarly communication | 0.019 | 0.025 |
| Open science | 0.004 | 0.032 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".