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Record W4306398658 · doi:10.31219/osf.io/5vphg

Potential energy transition in a transitional country: Initial evidence from young Vietnamese survey and Bayesian approach

2022· preprint· en· W4306398658 on OpenAlexaff
Quy Van Khuc, Phuong-Mai Tran, Thuy Nguyen, Phuong-Thao Dang, Đặng Trung Tuyến, Phu Pham, Luu Quoc Dat

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsWestern University
Fundersnot available
KeywordsEnergy conservationEnergy (signal processing)Energy transitionPopulationYoung adultSustainable developmentEconomic growthPsychologyBusinessPolitical scienceEconomicsDemographySociologyEngineeringDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

Industrialization and consumerism have aroused growing concern about energy depletion, necessitating a transition from fossil fuel to renewable energy sources. To this end, every segment of the population should shoulder responsibility for mitigating environmental problems, especially the young generation. This study contributes to the literature on environment management and development by improving the understanding of young adults’ intention to acquire energy conservation knowledge and its correlation with their demographics and environmental concerns. We employed a systematic randomized sampling method and conducted a large-scale online survey with the participation of 1454 students in 48 different universities in Vietnam. The first results show that young adults had significant environmental concerns, yet more efforts are demanded to turn perceptions into actions or contributions. Almost 83% expressed a desire for energy-saving knowledge, and roughly 50% are willing to take an energy course. We found that the young adults' perception and high income were positively associated with their decision on energy course enrolment. Demographically, women were more likely to take energy-saving courses, and those living urban areas had a higher desire for knowledge enhancement. These findings have numerous policy implications for facilitating energy transformation based on improved environmental education programs for sustainable development in Vietnam and beyond.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.014
GPT teacher head0.255
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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