Developing Digital Citizenship in Municipality: Factors and Barriers
Bibliographic record
Abstract
Digital citizenship refers to people who can use technology appropriately.The purposes of this research are: (1) to examine personal factors influencing the digital citizenship of people, (2) to investigate the differences in digital citizenship of people between two municipalities, and (3) to examine the barriers to digital citizenship of people.This study employs a quantitative method using an online questionnaire.The sample size was 438 people in Hat Yai Municipality and Songkhla Municipality, Thailand.The results revealed that people with different personal factors, namely gender, age, occupation, income, and level of education, had different levels of digital citizenship.This study also found that people living in different municipal locations had different digital citizenship.Moreover, the most important issue of ethics in using digital media and social networks was emphasized, followed by adaptation/changing behavior towards technology, and knowledge and understanding of using digital media and social networks.The results led to the development of communication channels to educate the public on proper digital citizenship, and the development of the internet network system to fully support digital citizenship in the future.
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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 | 0.001 |
| 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 | 0.001 |
| 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".