Attracting and Leveraging Visitors at a Charity Cycling Event
Bibliographic record
Abstract
Sport events are increasingly being recognized as integral to a destination's marketing strategy. Charity sport events are a type of event that can be leveraged by local businesses and destination marketers as a way of stimulating flow-on tourism, shaping an image and generating word of mouth. Yet, little research has been conducted in this area. Previous research has shown that length of stay in a destination and group composition can impact subsequent tourist behaviors. Thus, visitors' push and pull motivations and their influences on participants' choice of event and mode of participation (team versus individual) were assessed as a way of developing this line of research. The motives of supporting others, learning about the destination and cycling identity were predictive of event choice. Social motives and an identity tied to cycling predicted participants' mode of participation. Further, motives were distinguished between first-time and repeat visitors. First-time visitors were more motivated than repeat visitors by the physical aspects of the event and the opportunity to learn about the destination. Conversely, repeat visitors were more motivated by identities tied to the cause and the sport at hand than first-time visitors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".