A Methodology for the Preservation of the Architectural Heritage of Senneville, Quebec, Canada
Bibliographic record
Abstract
The town of Senneville, located at the western edge of the Island of Montreal, has thrived as a small community surrounded by large urban neighbourhoods. Once a popular location for the summer homes of wealthy Montrealers, Senneville is characterized by a series of architecturally and historically unique estates. As suburban growth continues to alter the character of the Island of Montreal, residents of Senneville have begun to fear that their community is in danger of losing its distinctiveness. The town's current bylaws inadequately prepare it for sustainable growth. As a result, the author was engaged by the municipality to survey the community and prepare architectural guidelines for its preservation. The process began by visiting, documenting and photographing each of Senneville's 350 homes. Survey sheets were created, through which criteria deemed essential to an architectural inventory were formulated. Town character, civic buildings and its public spaces were studied. Six character zones were designated for the appraisal of different architectural areas. The observation, synthesis and analysis resulted in the creation of design guidelines for preservation and development. This paper describes the process of conceiving those guidelines. It details the guidelines created for one of Senneville's character zones, the Urban, and offers a broad overall of how they might be useful in other areas.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".