Technologies of nation-building and the curation of Canada : immersion, interactivity, and federal mandates in Canadian heritage museums
Bibliographic record
Abstract
This thesis examines how federally funded Canadian heritage museums utilize immersive and interactive practices in exhibit design as mechanisms for constructing national identity. While institutions such as the Canadian Children’s Museum have historically relied on physical, hands-on models for engagement, the COVID-19 pandemic accelerated reliance on digital programming, virtual tours, and immersive technologies across galleries, libraries, archives, and museums (GLAM). These developments highlight the longer trajectory of Canadian heritage institutions experimenting with digital tools while also navigating financial realities, the experience economy, and shifting visitor expectations. Rather than measuring levels of immersion or interactivity, this thesis analyzes how these terms are articulated and applied in institutional discourse and exhibition practices. Drawing on institutional documentation, including financial reports, corporate and strategic plans, and interpretive materials from 2020–2025, my research situates immersive and interactive technologies within broader processes of corporatization, mediatization, and nation building. My thesis investigates how federal and provincial institutions deploy immersion and interactivity both to foster unity and collective memory and in some cases, to advance reconciliation initiatives using content analysis and case studies of the Canadian War Museum, the Canadian Museum of History, the Canadian Children’s Museum, the Royal Alberta Museum, and the Royal British Columbia Museum. The findings from this analysis demonstrate that immersive and interactive strategies in Canadian heritage museums are not wholly novel, but extend to a longer history of technological adaptation in response to crises, political priorities, and public demands. These strategies reveal tensions between educational mandates, entertainment imperatives, and commercial pressures, underscoring the complex interplay between federal funding, corporate influence, and cultural responsibility. Ultimately, my research finds that immersive and interactive practices in Canadian heritage institutions function as both tools of nation building and reflect the challenges of presenting inclusive cultural narratives within the twenty-first-century experience economy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.028 | 0.027 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".