What to see and how to see it: tourists, residents, and the beginnings of the walking tour in nineteenth-century Quebec City
Bibliographic record
Abstract
During the course of the nineteenth century, tourism promoters developed prescribed guidebook itineraries and walking tours to help tourists better enjoy their leisure travel. These suggested walking tours offer historians a glimpse into the historical consciousness of visitors and, to an extent, of the local bourgeoisie. In Quebec City, the guidebook walking tour emerged in the middle of the nineteenth century as the local business of tourism became more sophisticated. Yet, while walking tours originated with local promoters seeking to highlight what they believed to be the interesting features of their city, they were quickly adapted to suit the preferences of international, particularly British and American, travelers. Acknowledging that as a cultural exchange, tourism is a site of mediated power relations, this article suggests that as a market exchange, tourism presents an imbalance of power. As tourism promoters and businesses sought to entice international travelers by anticipating their tastes for the exotic, local entrepreneurs adapted their own sense of place to conform with those tastes. Over time, the accumulated decisions of tourist promoters produced a consensus about the historic character of Quebec City that has survived since the end of the nineteenth century.
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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 | 0.001 | 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 | 0.032 | 0.018 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".