Bibliographic record
Abstract
This thesis is set in St. Catharines Ontario, a mid-sized city of 132,000 people, situated in the heart of the Niagara Region. Once a thriving manufacturing centre, St. Catharines has experienced two decades of traumatic economic contraction due to the collapse of the local automotive industry. Like other cities that have experienced the loss of their predominant industry, St. Catharines is struggling not only with unemployment, economic uncertainty and environmental degradation, but also with issues concerning the city’s very identity. As industrial activity played a critical role in shaping the form and character of the city, its steady disappearance has left both a functional and symbolic void in the community. \n \nThe challenges associated with deindustrialization and decentralized urbanization have had a devastating impact on St. Catharines. The city’s historic core has not only lost its role as the symbolic centre of the community, unrelenting suburban expansion has also led to the destruction of some of Canada’s most productive agricultural terrain in the surrounding vicinity. \n \nThis thesis argues that the current economic crisis offers a unique opportunity to radically reconsider St. Catharines’ urban environment. The thesis looks to the earth – the terroir – as the basis for the development of a robust vision to transform the city’s underappreciated historic core into a hub for the Niagara Region’s expanding wine industry. Essential to this vision is the extensive cultivation of urban vineyards and the planning of key pieces of urban armature around which future development will occur. The design aims to improve the overall quality-of-life offered in St. Catharines, and build a broader sense of community by enhancing the unique experience of the place and engaging citizens in the local wine enterprise.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.191 | 0.032 |
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".