The Toronto Pan Am Sports Centre : operating challenges of a 4P project
Bibliographic record
Abstract
The purpose of this study was to determine the optimal method of uniformly operating a facility co-owned by two large public institutions. In 2014, the City of Toronto (“City”) and the University of Toronto – Scarborough Campus (“University”) will co-own the Toronto Pan Am Sports Centre (“TPASC”), a facility currently under construction for the 2015 Pan/Parapan American Games (“Games”) which, post-Games will serve the community-at-large, the University community and the high performance sport community and will house the Canadian Sport Institute - Ontario. As a Games capital project, the TPASC construction is project managed by Ontario’s 3P (public private partnership) agency infrastructure Ontario, and is arguably a public-public private partnership (4P) project due to its two public owners. Four operating options for the TPASC are identified: (1) City and University operating programs separately under one roof; (2) City or University operating the facility on behalf of both entities; (3) City and University contracting out to an unrelated third party; and (4) City and University jointly creating a corporation for the purpose of operating the TPASC. These options are applied to an evaluation framework consisting of five critical factors (vision alignment, financial viability, customer service orientation, egalitarian owner focus and \nlabour alignment). Option #4 (City and University jointly creating a coporation to operate TPASC) received the highest score and is the recommended option. Challenges related the recommended option are discussed.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.022 | 0.007 |
| Scholarly communication | 0.021 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.004 |
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".