Creating Non-Linear Digital Stories of the Canadian Parliament Buildings and Rehabilitation Project
Bibliographic record
Abstract
The Library of Parliament offers guided tours of the Canadian Parliament Buildings in Ottawa, Canada. Trained guides lead visitors through the main spaces of the Centre Block following a carefully scripted itinerary. Unfortunately, the Centre Block will be closing in 2018 to undergo a multi-year long rehabilitation, suspending the current tour program and relocating parliamentary activities. The closing of Centre Block presented two research challenges: how to continue to engage the public in the rich history of the Centre Block and how to engage and educate the public about the rehabilitation process.Carleton Immersive Media Studio has been working with Public Services and Procurement Canada for over two years to record and model the existing conditions of the Centre Block in preparation for the rehabilitation. In this paper, we discuss three projects - the "Senate Virtual Tour", the "VR Kiosk", and "Building Canada's Parliament" - that repurpose these existing digital assets to teach an online public about the past and future of Canada's Parliament Buildings. The projects offer non-linear, self-guided, and interactive experiences that engage the visitor by offering a sense of agency. In the first example, visitors can experience the digitally assisted storytelling of the "Senate Virtual Tour" by taking a self-guided walk through the spaces of the Senate and choose from a range of artefacts that are available for closer study. The second example, the "VR Kiosk", provides passive virtual reality experience narratives focusing on the rehabilitation project, and lastly, "Building Canada's Parliament", offers interactive games and images, video, and 360-video to tell the story of the Parliamentary architecture and the rehabilitation project.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".