City Image and Perceived Tourism Impact: Evidence from Port Louis, Mauritius
Bibliographic record
Abstract
Research suggests that the images residents hold about their community influence the political support for tourism. Yet, few researchers have investigated the image that local residents have of their own area. Borrowing from the existing literature on place image and residents' perceptions of tourism impacts, a theoretical model incorporating these two lines of research is developed and tested using data collected from residents of the city of Port Louis, Mauritius. It proposes four city image attributes as the independent constructs influencing residents' perceptions toward the overall impact of tourism development. These include social attributes, transport attributes, government services attributes, and shopping attributes. Overall impact of tourism development is considered to be a determinant of the level of support for the industry. Results of the structural equation modeling analysis indicate that residents' perceived levels of shopping attributes, transport attributes, and social attributes of the city influence their level of support for the tourism industry. The hypothesis relating transport attributes to overall impacts of tourism was not supported. The study provides some important considerations for local planners attempting to make tourism more supportive in the city.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".