Bibliographic record
Abstract
For more than a century, posters, advertisements, and brochures have characterized Canada as a desirable tourist destination offering spectacular scenery, wild animals, outdoor recreation, and state-of-the-art accommodations. However, these explicitly commercial displays are not the only marketing tools at the country’s disposal; beginning in the 1890s, film also played a role in selling Canada. In Northern Getaway Dominique Brégent-Heald investigates the connections between film and tourism during the first half of the twentieth century, exploring the economic, pedagogical, geopolitical, and socio-cultural contexts and aspirations of tourism films. From the first moving images of the 1890s through the end of the 1950s, a complex web of public and private stakeholders in Canadian tourism experimented, sometimes in collaboration with Hollywood, with a variety of film forms – 16 mm or 35 mm, feature or short films, fiction or nonfiction, professional or amateur filmmakers – to promote Canada. Spectators, particularly Americans, saw Canada as a tourist destination on screens in motion picture theatres, schools, and fairgrounds. Rooted in settler colonial representations that celebrate the nation’s unspoiled but welcoming wilderness landscapes, these films also characterize Canada as a technologically and industrially advanced settler country. Using evidence from a wide range of archival sources and drawing from current scholarship in film history and tourism studies, Northern Getaway demonstrates how Canada was an innovator in using film to shape and project a recognizable destination brand.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.467 | 0.123 |
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".