Communication Factors Contributing to Mindfulness: A Study of Melaka World Heritage Site Visitors
Bibliographic record
Abstract
We investigate the effects of three communication factors (i.e. variety, interactivity, and personal connection) as used in three different types of media (i.e. exhibits, guided tours, and printed materials) on the state of mindfulness of visitors at the Malacca World Heritage Site. Mindfulness refers to a state of mind in which a person actively processes available information. For a relatively new heritage site, such as Malacca, improving a visitors’ state of mindfulness is important because mindful visitors have been shown to have superior understanding and learning, thus benefiting the heritage site’s management authorities by cultivating responsible and sustainable tourism behaviours. The survey method was employed to measure the state of mindfulness of 200 respondents visiting the Malacca World Heritage Site. The survey results indicate that each communication media has one key communication factor that significantly induces a state of mindfulness in the visitor. For exhibits, variety was found to be the key communication factor while for guided tours and printed material, the key communication factor was interactivity. In response to these findings, we outline a number of specific directions for heritage site management and authorities to identify the most effective communication factors in commonly used communication media.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".