Arena-Anchored Urban Development Projects and the Visitor Economy
Bibliographic record
Abstract
Cities of all sizes are actively engaged in developing various urban infrastructure projects. A common strategy used in larger North American cities is employing arena-anchored urban development projects, where a professional sports team is used as an anchor tenant of a sports facility to generate development in the city. One means of relocating economic activity is to increase visitation to the desired redevelopment area. In this paper we used the visitor economy as a lens to explore how arena-anchored projects and the professional sports teams that play there fit into a local city's tourism economy. To conduct this study, a multi case study design was used to draw data from two cities: Columbus, Ohio, and Detroit, Michigan. Interviews were goal directed and conducted in person with leaders in Columbus (n = 9) and Detroit (n = 10), and inductive and deductive approaches to coding were undertaken in the form of content analysis. The results indicate that growing the visitor economy through arena anchored urban development relies on planned placemaking via the strategic approach of bundling diverse amenities together. These findings provide valuable feedback to those cities considering arena development projects, and how the arenas may be combined with other civic amenities to undergird the local visitor economy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".