Visitor and Resident Images of Qingdao, China, as a Tourism Destination
Bibliographic record
Abstract
This article compares the images of Qingdao, China, as perceived by visitors and residents and examines whether these images are affected by information sources, age, education, and place attachment. The data were collected using a self-administered survey of 578 visitors and 337 residents of Qingdao throughout June and July of 2009. The image construct was conceptualized into two dimensions: cognitive and affective. It was found that the images perceived by visitors and residents converged primarily on cognitive images and less so on affective images. The results of a Mann-Whitney U test reveal that the main differences between the images held by visitors and residents are in 10 cognitive images (seafood, cultural attraction, highway system, traffic congestion, airline schedules, local people, beaches, weather, scenery, and hygiene and cleanliness) and in two affective images (arousing–sleepy and exciting–gloomy). Spearman's rank correlation test revealed that there is a weak positive correlation between place attachment and the images of Qingdao perceived by both visitors and residents. Age, education, and information sources are only partially correlated with visitor and resident images, with weak correlations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".