The Behavioral Pattern of Chinese Public Cultural Participation in Museums
Bibliographic record
Abstract
Studying the cultural participation model of the public and its influencing factors is important for the sustainable development of regional culture. Therefore, in this study, we determined which factors influence the cultural participation of the Chinese public. Firstly, we extracted the key features of the motivation and timing for a museum visit with multiple correspondence analysis (MCA), and explored the relationship of the features of different motivations with the frequency and duration of the public’s visits to the museum. Secondly, we determined the monotonicity of the influence of ordinal variables on cultural participation behavior and identified the mechanism through which the independent variable influences public cultural participation with categorical regression (CATREG). Finally, we analyzed the research data from the museum audience survey in the Hubei Provincial Museum and a national public culture participation survey. We found that education, occupation, academic discipline, income, distance, age, and sex affect the public’s museum participation. This indicates that to guarantee the public’s cultural rights and promote sustainable development, education, planning, and other aspects must be coordinated in cultural management to increase public cultural participation, rather than removing the economic threshold for public cultural participation through public finances alone.
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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 | 0.000 | 0.002 |
| 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".