The Evolution of the Ethnographic Object Catalog of the Canadian Museum of History, Part 2: Systematizing, Communicating, and Reconciling Anthropological Knowledge in the Museum, ca. 1960–2018
Bibliographic record
Abstract
This article reports on the second part of a two-part study tracing the evolution of the Canadian Museum of History’s catalog of its ethnological collections from 1879 to the present day. Drawing on the insights of rhetorical genre studies, we examine how the catalog has been implicated in the formation and shaping of anthropological knowledge in the museum over the course of its history. In this second part, we trace the catalog’s evolution from internal management tool to public access tool between 1960 and 2018 and examine how it participated in the actions of systematizing, communicating, and reconciling knowledge within the museum during that time period.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.016 | 0.020 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".