Implications of Climate Change for Outdoor Event Planning: A Case Study of Three Special Events in Canada's National Capital Region
Bibliographic record
Abstract
Weather and climate play an important role in the success of many outdoor special events, including the quality of visitor experiences. In spite of the growing importance of event tourism to many communities in Canada and the US, research examining the influence of current weather and climate on event planning, or event tourism more broadly, is very limited. Consequently, the potential implications of climate change for event planning and tourism has yet to be explored. This article presents the findings of the first known assessment of climate change on event tourism in North America. A case study of Canada's National Capital Region was used to better understand the current impact of weather and climate on three high-profile outdoor events planned by the National Capital Commission (NCC) (Winterlude, the Canadian Tulip Festival, and Canada Day celebrations), and to assess the potential impact of climate change on the NCC's long-term event planning. Climate change is projected to have a meaningful impact on the success of some special events by altering the ability of the NCC to maintain ice-based attractions (skating on the Rideau Canal Skateway), changing tulip phenology to cause a mismatch with current Festival dates, and increasing the need for heat emergency planning during Canada Day. Possible adaptation strategies to respond to the challenges of climate change are also discussed, as are some general implications for event management.
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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 | 0.003 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".