Olympic bidding and social license: a micro analysis of a public debate
Bibliographic record
Abstract
Social license or public approval is often a major issue in the bid phase of the Olympic cycle and is typically sought through a referendum. Instead of the macro factors usually utilized to explain referendum outcomes, this paper adds to the literature by taking a micro approach that focuses on how local residents encounter the prospect of hosting the Games. Building from the work of economists who have examined the role of announcements about bidding as “news shocks” and “sentiment shocks” in a potential host community, this paper takes a more sociological approach by showing how bidding stimulates interaction and debate at the grassroots and utilizes extensive empirical research from two Winter Olympic cities, Calgary, and Vancouver. Local residents encounter the intrusive nature of an Olympic bid that is filled with prospective unknowns and that exists as a political policy option. Bidding stimulates and provokes conflict and debate through face-to-face verbal and non-verbal communication around six major themes, and the competing narratives that develop around costs, the IOC industry, and local priorities. It will be shown how local citizens struggle to determine their own responses to Olympic initiatives in interaction with others which contributes to the volatility of referendum outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".