The Relationship Between Park Satisfaction, Place Attachment and Revisit Intention in Neighborhood Parks with Physical Activity Facilities
Bibliographic record
Abstract
The urban population is increasing day by day, threatening human health. Neighborhood parks in which people can participate in physical activities have an important place in reducing the negative effects of urban life. However, not much is known much about factors such as “park satisfaction” and “place attachment”, which may play a role in the visitors’ participation in and continuation of physical activity in neighborhood parks, or the relationship between these factors. The purpose of this study was thus to examine the relationship between park satisfaction, place attachment and revisit intention. The data were obtained using the convenience sampling method from 357 park visitors who visited a park for physical activity. The methodological principles of structural equation modeling were used to test the conceptual model based on the literature review. According to the results, park satisfaction had a positive and significant effect on park attachment. In addition, park attachment played a mediating role between satisfaction and revisit intention. As a result, a theoretical and comprehensive model that revealed the relationship between park satisfaction, park attachment and revisit intention was developed. It is thought that the results will guide local governments, managers responsible for parks and park designers in maintaining open-air recreation facilities and services in urban areas.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".