Constructing and Deconstructing 'Victory, 1918' at the Canadian War Museum
Bibliographic record
Abstract
This article explores the history behind the creation of the Canadian War Museum’s exhibition, Victory, 1918: The Last Hundred Days. The exhibition presented the story of the Canadian Corps during the Hundred Days campaign of the First World War and the Canadian contributions to Allied victory. What follows is a glimpse into the challenges of exhibition development. Together, artifacts, personal stories, films, works of art, immersive spaces, reconstructions and colourized historical photographs created an engaging visitor experience while communicating key concepts about the Hundred Days.\nCet article explore l’histoire de la création de l’exposition Victoire 1918: Les cent derniers jours du Musée canadien de la guerre. L’exposition présentait l’histoire du Corps canadien lors de la campagne des Cent Jours de la Première Guerre mondiale et les contributions canadiennes à la victoire des Alliés. Voici donc un aperçu des défis liés au développement de l’exposition. Grâce aux objets, histoires personnelles, films, oeuvres d’art, espaces immersifs, reconstructions et des photographies historiques colorisées, l’exposition permet aux visiteurs de vivre une expérience captivante tout en leur expliquant les concepts clés des Cent Jours.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.036 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".