Bibliographic record
Abstract
Ryerson is a dynamic university in the heart of Toronto, the largest and most diverse city in Canada. In the last decade the university has undergone rapid expansion from a 9000 student polytechnic to a comprehensive university of almost 30,000 students, offering programs at all levels. The three goals of the University’s 2008 Master Plan are: urban intensification; people first (pedestrianization of the urban environment); and a commitment to design excellence. At the Master Plan announcement Sheldon Levy, Ryerson President, said “With energetic partnerships and great ideas, our aim is to move Ryerson and Toronto forward together”. Numerous inventive partnerships have been formed since then. The first new building since the Master Plan was the Ryerson Image Centre (RIC), which houses a large image bank of 20th century photo-journalism from the Black Star Agency. Next, the Mattamy Athletic Centre (MAC) rose from Maple Leaf Gardens, an iconic 1930s building famous for ice hockey, Elvis, and the Beatles. In partnership with a national grocery chain the MAC houses new student athletic facilities, an ice arena, and a huge supermarket. Third is the Student Learning Centre (SLC), to be built on Yonge Street, the major spine of Toronto. The current Library is a 1970s brutalist book warehouse. This building is completely inadequate in size, functionality and ambience for our users. The new SLC, designed by Snøhetta (Oslo) and Zeidler (Toronto) satisfies the three tenets of the Master Plan. It will provide a window and gateway to Ryerson. The transparent building will focus on student learning support, individual study and collaborative space. There will be no bookstacks. The two library buildings will be organically connected. Retail stores will occupy the street face at ground level and below, to revitalize the street. Completion is planned for 2015. This paper describes the philosophy, the landscape, the planning, the design, the collaborations, and the challenges of this exciting project.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.035 |
| Scholarly communication | 0.041 | 0.029 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.041 | 0.010 |
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".