THE HALIFAX IMPLOSION: A CASE STUDY OF THE HALIFAX 2014 COMMONWEALTH GAMES BID (2005-2007)
Bibliographic record
Abstract
In the summer of 2005, Commonwealth Games Canada called for applications from Canadian cities to bid for the right to be Canada’s candidate city in the international competition to host the 2014 Commonwealth Games. Five cities declared interest and contested the domestic phase of the bid: Toronto, Ottawa, Calgary, Hamilton and Halifax. On December 15th, 2005, Commonwealth Games Canada announced that Halifax would represent Canada in the international phase of the bid. The Halifax Regional Municipality, the Province of Nova Scotia, and specifically the Halifax 2014 bid committee began preparing their bid that would ultimately be judged against the other two international bids from Glasgow, Scotland and Abuja, Nigeria. Before Halifax would even be judged, their bid was withdrawn on March 8 , 2007. This thesis was a case study of one Canadian sport mega-event bid that went awry for a multitude of factors. Through document analysis and interviews with some of the key players of the bid, it was determined that the short timeframe and the political and leadership forces at play were the two biggest factors in the bid’s demise. Themes and lessons for future Canadian sport mega-event bids were exposed, and recommendations for future study provided.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".