Identifying tourists' preferences for Aboriginal tourism product features: implications for a northern First Nation in British Columbia
Bibliographic record
Abstract
Recent research on the Aboriginal tourism market has revolved predominantly around establishing a profile of the traveller interested in Aboriginal tourism (hereafter referred to as the Aboriginal tourism traveller). Currently, the Aboriginal tourism traveller is generally described as a mature individual who is interested in having authentic experiences of different cultures. However, there is a need for a better understanding of what specific products this particular traveller is interested in, and in what style, format or nature of delivery. The study presented in this article attempts to provide insight into this topic. In a collaborative research effort between Tl'azt'en Nation and the University of Northern British Columbia, a questionnaire containing four potential Aboriginal tourism product descriptions and 31 individual features of Aboriginal tourism products was administered to 337 visitors of northern British Columbia during the summer of 2007. Despite a primary interest in nature experiences by the majority of visitors, one-third of our sample demonstrated considerable interest in experiences of Aboriginal culture. Results suggest the need for marketing diverse Aboriginal tourism attractions to attract repeat visitors and for offering an introductory experience to Aboriginal culture for 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".