Enculturation, Education and Sustainable Development: Understanding the Impact of Culture and Education on Climate Change
Bibliographic record
Abstract
Education should play an important role in sustainable development. However, we were also faced with the enculturation in the education systems that contribute to the literacy of the environmental issue and challenges in maintaining sustainable development. In this review, we aimed to synthesize the recent research findings on how enculturation was developed among students through social and cultural factors and the role of education for sustainable development. In synthesizing the enculturation in the education system, we found several contributing social and cultural factors such as family cultural background and parental values, school systems, teachers’ beliefs, and the attitudes and appraisal of students used in the different school environments. Co-existing differences were also found when examining the environmental issue literacy among students from different cultures in the studies along with energy literacy and ocean literacy from cross-cultural studies perspectives. Drawing on these findings, we further add on how education for sustainable development in different cultures was integrated and emphasized in their existing school curricula to help other cultures to learn more about how education for sustainable development was developed across cultural contexts.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".