Building Canada’s “National Playground”: Indigenous Labour and the Development of Rocky Mountains Park's Early Tourism Economies, 1887-1930
Bibliographic record
Abstract
Rocky Mountains Park (known as Banff National Park since 1930) is Canada’s oldest and most visited national park, receiving over four million visitors annually. While much has been written on the park’s historical development and management, less attention has been given to the impact of the park’s creation on Indigenous communities and the significant contributions Indigenous Peoples have made to its development. In this thesis, I examine the diverse roles that Indigenous Peoples played in shaping the tourism economies of Rocky Mountains Park from 1887 to 1930. I frame this exploration through three analytical vignettes. The first vignette focuses on the guiding economy, primarily centered around big game hunting that developed rapidly throughout the 1880s and 1890s. I emphasize the integral role Indigenous Peoples played in the development of the guiding economy of the park, primarily as guides, in addition to other guiding related labour while also reflecting on their gradual removal from this industry. Subsequently, I investigate the contributions of Indigenous Peoples to the souvenir economy, emphasizing the importance of Indigenous Peoples’ labour and relationships with Banff merchants to the economy’s success. Finally, I examine the participation of Indigenous communities in the key festivals of Banff’s annual tourism calendar – Banff Indian Days, the Banff Winter Carnival, and Victoria and Dominion Day celebrations – and the importance of the festivals to the park’s economic health. Collectively, I illustrate the varied and pivotal contributions of Indigenous Peoples to the establishment and prosperity of Banff National Park’s tourism economies between 1887 and 1930.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".