Comparative Study on Eastern and Western Leisure Policy in the Perspective of Hofstede’s Cultural Dimensions Theory
Bibliographic record
Abstract
The leisure industry has developed rapidly since the 1950s and gradually got governments’ attention and become an important part of people’s daily life. Some western countries, such as the United Kingdom, the United Sates, New Zealand, Denmark, Australia, Canada, Sweden, Brazil and some Eastern countries like Japan, Korea and China have invested capital, introduced policies and set up facilities to support the development of the leisure industry. Research on leisure policies and leisure industry is developing both at home and abroad during these years. Based on all the research on leisure policies found from home and abroad, this paper analyzes the reasons for the differences between eastern and western policies with Hofstede’s Cultural Dimensions Theory. The thesis then draws conclusions concerning the similarities and features of eastern and western countries as well as how China can learn from these countries’ leisure policies. This research is expected to make contributions to the development of Chinese leisure policy and leisure industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".