China and the Olympics: views of insiders and outsiders
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the views of residents and foreigners of the Olympics and the host country before and after the mega‐event within the context of marketing theory on country image effects and psychology theories attribution. Design/methodology/approach This is achieved by studying the views of American and Chinese respondents of China and the Olympics before and after the Beijing Olympics. Samples of Chinese and Americans were surveyed before and after the Beijing Summer Olympics concerning their images of the Olympics, China and its people, and China as a vacation destination. Cross‐national and pre‐post comparisons are made and interaction effects are noted using MANOVA. Findings Significant cross‐national and time differences and several interaction effects are found across all three focal objects of image measurements. Large country differences are found. Despite how technically successful the Games might have looked, post‐event assessments are overwhelmingly lower. Additional differences in views and interaction effects are discussed in terms of the intended and unintended impacts of the event on local and foreign respondents. Research limitations/implications Only one location in China and one foreign country are surveyed. Practical implications The paper has important implications for both the effects of mega‐events on country images and the effects of the host country on the event brand image. These issues have relevance for countries seeking to host mega‐events and those who manage these events and make decision about where they will be held. Originality/value This is the first cross‐national study of the Olympics and their effects using before‐and‐after event measures. It also combines analyses of both the event and the place images from the perspectives of both those who live in the country and residents of other countries. Attribution theory is a useful reference theory for mega‐event assessments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".