Destination Management Organizations’ Roles in Sustainable Tourism in the Face of Climate Change: An Overview of Prince Edward Island
Bibliographic record
Abstract
Globally, destination management organizations (DMOs) are becoming increasingly known for their sustainable practices. Despite the importance of destination management organizations’ sustainability initiatives in the face of climate change, minimal research has been undertaken on the topic in Canada. DMOs on PEI can inform tourists better if they know what other adaptive strategies are taken into consideration around Canada. Our work included host-community interviews and perceptions on DMOs’ roles in improving tourism in the face of climate change. The interviews concluded that tourism officials in Prince Edward Island are becoming more conscious of climate change, but more has to be done to slow down the effects of the phenomenon. This paper also identified challenges facing DMOs in the area of sustainable tourism in the context of climate change. One of the recommendations was that DMOs should have access to techniques for mitigation and adaptation in addition to incentives that are sensitive to local situations. They may successfully advocate for climate change in this way and inform visitors if they are staying in risky places because of the consequences of climate change. The information on the standard operating procedures that DMOs use was intended to be useful to travelers, DMOs, and enterprises involved in the tourism industry. Future implications should discover new approaches for sustainability projects and to achieve a better understanding of how to enhance processes within the tourism industry, and more research on DMOs’ sustainability practices in the face of climate change could help improve this field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".