Marketing and a Million-acre Farm: Using Culture and Islandness to Promote PEI as a Unique Tourism Destination
Bibliographic record
Abstract
Islands across the globe are enjoying tourism growth, accounting for a far greater percentage of the tourism market than their size would suggest, and collectively becoming the world’s second most popular tourist destination. Culture is an essential and fast-growing component of tourism, used by destinations to broaden their product and showcase their uniqueness. Research has found that small islands in particular can leverage culture to showcase their local identity. With 1.56 M tourists and receipts of $447 M annually, tourism is Prince Edward Island’s second-largest industry, accounting for 6.4% of its GDP and contributing handsomely to the province’s sustainability. Through Tourism PEI, its marketing arm, the Island has long employed its culture and “islandness” as a magnet for tourists. Through a review of academic and grey literature, combined with interviews of tourism marketing officials, this study explores and compares the extent to which the Island’s regions and municipalities use culture in their marketing materials and assesses how tourism players define “islandness” and use it as a distinguishing feature to attract 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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".