To Go or Not to Go: Exploring Gen Z's Attitudes toward Museum Visiting
Bibliographic record
Abstract
The goal of this research is to explore the reasons why young people, in particular the Generation Z (Gen Z) cohort, visit or do not visit publicly funded museums.To remain vital, museums of all kinds (including art museums/galleries) need to continue to attract an audience.Much research has been done on the attitudes of older generational cohorts toward museum visiting, but it has not fully understood the attitudes of this younger, more tech-savvy generation.Survey and interview data were collected from undergraduate students (Gen Z members) to begin to understand their attitudes toward and motivation for museum visiting or not visiting.Three traditional goals for museums, that is, education, social cohesion and entertainment, were used as a lens to gain insight into how Gen Z views museum visiting.The results of the survey confirmed Gen Z's recognition of the museum's function in education and entertainment; the museum's function in strengthening social cohesion was not fully confirmed.The interview data provided insight into participants' perceptions of why they felt that museums were not currently doing enough to attract visitors of their age group.Participants also offered suggestions for areas where the museum could improve in the future and described their expectations.Recommendations that will help museums attract more Gen Z visitors are made.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.014 |
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; both teacher heads agree on what is shown here.
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".