The Canadian city of Winnipeg, Manitoba,
Bibliographic record
Abstract
followed the typical North American development pattern of suburban growth. The downtown lost some of its retail prominence when regional shopping centers were developed between 1959 and 1980. ’ Transit routing patterns also changed. More cross-town and feeder routes were added to serve the various suburban trip generators, including shopping centers. It is generally felt that regional shopping centers have a very low transit mode split, hence the need for large parking areas and the low priority placed by shopping center owners on providing for on-site transit. Nonetheless, Winnipeg Transit provides service to three regional shopping centers. Shopping Center Planning In the case of the two centers to be discussed in this paper, transit was considered during planning for expansion of the centers. Management realized that transit played a role in providing an alternative means of travel to the shopping center, thus reducing parking demand. The main influence of transit was on the internal circulation system and the number of parking spaces to be provided. Examining the overall circulation and parking system also meant parking losses would be minimized with the provision of a transit facility. The Polo Park transit facility, for example, was proposed to be located on land owned by a major retailer, who did not want a decrease in the number of parking spaces on its property. The parking layout was thus examined and revised to provide for 1,580 parking spaces after the development of the transit center and street widening, 180 more parking spaces than there were originally. The planning process for both centers involved examining the existing routing patterns and bus stop locations and developing alternative transit facilities and on-site routing. These were reviewed in terms of impact on parking, conflicts for buses, and ease of pedestrian access. Plans were reviewed by shopping center management and Winnipeg Transit staff.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".