Examining the Mega‐Event Space–Perception Nexus: An Advanced Epicenter Effect Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous research emphasizes that residents living within an event’s epicenter (i.e., host city) will exhibit the greatest positive and negative event legacy perceptions. However, given that mega‐events often include multiple event spaces to operationalize hosting (e.g., satellite cities), a single epicenter perspective is challenged. We examined residents’ social legacy perceptions of a mega‐event with multiple event sites to test an epicenter effect within this event ecosystem. Data were collected via surveys from 1,901 residents living within four event spaces: Host City , Satellite , Provincial , and National . Statistical analyses revealed event space significantly influenced residents’ social legacy perceptions but not linearly as previously theorized. Rather, Satellite residents perceived the highest positive legacies, not Host City residents. This evidence advances epicenter effect theorizing by highlighting how various event spaces can amplify or diminish residents’ perceptions. Event managers should leverage multiple event spaces to maximize positive legacy perceptions while minimizing negative legacy perceptions.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it