Improving Energy Literacy to Facilitate Energy Transition and Nurture Environmental Culture in Vietnam
Bibliographic record
Abstract
Concern about energy depletion has risen because of industrialization and consumerism, pushing a transition from fossil fuels to renewable energy sources. To this end, every group within society, especially the youth, should be made responsible for confronting and/or mitigating environmental problems. This study advances the understanding of young adults’ intentions to learn about energy conservation and its influencing factors, as well as contributes to the literature on environmental management and environmental culture and development. We used a systematic random sample technique to conduct a large-scale online survey with 1454 students from 48 different Vietnamese universities and employed Bayesian regression model to analyze the data. The initial research indicates that young adults are highly concerned about the environment, but more work has to be done to turn perceptions into actions. The majority of respondents—nearly 83%—want to increase their energy-saving knowledge, and around 50% are interested in enrolling in an energy course. Their decision regarding participation in an energy course is largely influenced by their perception and income. Women were more inclined to take energy-saving courses, and people who lived in rural areas had a stronger desire to increase their knowledge. Our research has various policy implications for promoting energy transformation and/or nurturing environmental cultures associated with environmental education improvement in Vietnam and beyond.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".