Understanding Residents' Support for Tourism Development: The Case of Aqaba City in Jordan
Bibliographic record
Abstract
This paper aims at investigating the effects of social interaction with tourists, cultural impacts of tourist, welfare impacts of tourism, negative interference of tourism in daily life, economic cost of tourism, sexual permissiveness due to tourism, and perception of crowding on resident support towards sustainable tourism development. A total of 568 questionnaire containing 34 items was used to collect information from the local residents in Aqaba city. Multiple regression analysis was conducted to test the research hypotheses. Results of the current study revealed that there are significant impacts of six independent variables (i.e. social interaction with tourists, cultural impacts of tourist, welfare impacts of tourism, less negativeness towards interference of tourism in daily life, less economic cost of tourism, and less sexual permissiveness due to tourism) on support for sustainable tourism development; whereas crowding on resident support has not significant impact on it. Results of T-test showed that there is a significant difference in the impact of resident attitudes towards sustainable tourism development in favor of gender. On the other hand, results of ANOVA test found that there is significant difference in the impact of resident attitudes towards sustainable tourism development that can be attributed to age and educational level; whereas no significant difference in favor of personal income.
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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 | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".