Intermodal connections: a movement oriented approach to placemaking in Downtown Sudbury
Bibliographic record
Abstract
The urban fabric of the city is the product of its history of development. Each development in history can be seen to improve, revitalize and reshape the city through the definition and redefinition of places, and paths of movement. In the late nineteenth and early twentieth century, many cities in North America went through a transformation aiming for places in cities with taller, larger, more durable buildings made possible by new building technologies. In the mid-twentieth century, the automobile became a major influence on urban form, often involving extensive demolition and rebuilding of places to accommodate this emerging mode of movement. In the late twentieth century there has been a significant shift in the development of urban fabric. This shift has focused on modes of movement at the human scale, and the experience of places in the city more connected to the natural environment. This thesis examines how to revitalize the City of Greater Sudbury as a whole using intermodal connections, by creating new relationships between places and paths of movement, with an emphasis on human experience and nature as essential contributors to urban form. From this network of Intermodal Connections, architectural and urban placemaking strategies can be implemented with community-oriented programs to bring people back to the Downtown core.
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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 | 0.002 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".