Bibliographic record
Abstract
Strategically located on a steep cliff above a narrow point in the St. Lawrence River where canons could bar the passage of enemy ships, Quebec is a natural fortress. The only city on this continent, north of Mexico, which has retained its fortification walls, Quebec City boasts an extraordinary array of military buildings and defensive structures. This field session will begin with a walking tour of the upper town which will include some of its most important sites and historic institutions. The preservation of an historic district is both complex and challenging. During this walk through the streets and lanes that bear witness to the evolution of the city, we will consider the strategies required and resources needed to carry out such a project. Along our itinerary, recent examples of restoration and adaptive use of buildings and commemorative squares will help us better understand the conservation issues and challenges involved in protecting this urban environment. During your tour you will discover 300 years of military history, including a prison building constructed for the British on the site of a French redoubt, and Artillery Park, a Parks Canada site which served over the centuries as an important military complex during the French, British and Canadian periods. Our visit will include the Dauphine Redoubt and the Nouvelles Casernes or “New Barracks”, where we will discuss plans to restore this massive stone structure, the largest military building constructed during the French regime. CONTACTS
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.867 | 0.762 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".