Exploring the material culture of medical artifacts in the Oblate Collection
Bibliographic record
Abstract
How can we explore object biographies when a collection has relied heavily on the donor’s narrative? This article uses three artifacts to explore the history of Ingenium’s ‘Oblate Collection’, a group of 282 medical artifacts used at L’Hôpital de L’Assomption in Grand Falls, New Brunswick, on the land of the Wolastoqiyik people. The hospital was opened in 1952 by the newly founded Secular Institute, a branch of the Oblate Missionaries of Mary Immaculate who ran 48 residential schools across Canada. Our catalogue information on the ‘Oblate Collection’ relies largely on the narrative from the donors themselves, primarily, two documents written by one of the nurses, Fabienne Rinfret, who elaborates on life working in the hospital and how the artifacts were used by the staff. Our files lack stories of patient experiences or a fuller, more inclusive sense of their local context including connections to Indigenous people and land. In order to tell a more well-rounded story of the collection, and fill out missing historical dimensions we can also look to the artifacts themselves through material culture readings and further research. Additional work with this collection will hopefully bring in more ways of knowing and different perspectives on these artifacts.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.022 | 0.048 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".