Promotional impact of image formation of an aboriginal tourist destination.
Bibliographic record
Abstract
The purpose of this research is to present a thorough analysis of image formation among first-time visitors to an Aboriginal (Mi’kmaw) cultural site. The thesis is an initial attempt to examine theories in consumer behaviour and reformulate a model in the destination image literature to empirically test the influence of personal (motivation, cognition-affect) and stimulus (promotional) factors on impression of an Aboriginal tourist destination. To gather primary data, visitors to The Glooscap Heritage Centre, in the Province of Nova Scotia, Canada completed a self-administered questionnaire. In total there were 309 valid samples. Over 80% of respondents in this study were interested in exploring cultural heritage, learning about cultures and ways of life (motives) and visiting cultural attractions (cognitive). Affectively, respondents felt the destination would be a pleasant (4.37/5), relaxing (4.10/5) and exciting (4.07/5) place to visit. Survey results imply most tourists were exposed to the tour guide’s message (82%), followed by the tour operator (53%), then the brochure (29%), and finally the travel agent’s information (19%). However, exposure did not correlate with effectiveness in image formation. The brochure impacted image the most (4.33/5), next was the tour operator (4.12/5), followed by the tour guide (4.08/5) and lastly the travel agent (3.9/5). Survey results imply the destination can more effectively use its key communication tools to enhance its image. Current study findings provide important implications and can aid in the design of marketing campaigns to create and improve Aboriginal destination image. One significant undertaking in this study was to draw upon the actions of other key regions and situate thesis results in the wider context of Aboriginal tourism growth. The role of this research in relation to destination development is considered broadening the implications to a global setting beyond the immediate context of the study.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".