A bibliometric study on “education for sustainability”
Bibliographic record
Abstract
The scientific production on “education for sustainability” has been growing in recent years what demonstrates the attention this subject has gathered. To better understand and characterize this trend, a bibliometric study of international papers on the subject was developed. The results show that the production has been growing since the middle of the last decade, focusing on the field of the applied social sciences, environmental sciences, energy, management, engineering, humanities and psychology. Australia, United Kingdom, United States, New Zealand, Spain, Israel and Canada are the countries that stand out, and it was possible to characterize the evolution of the production in each of these countries in the last 10 years, as well as to indicate the most used journals, the associated sub-themes, the most cited papers, the most productive authors and their affiliations. This allowed us to understand how the research on “education for sustainability” is being developed, showing its level of maturity and the most frequent themes and journals that have published more papers in the area. It was also possible to identify some themes which present research opportunities. The practical results of this study serve as a guideline for researchers, helping them to explore the available bibliography and the better ways to convey their production.
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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 | 0.009 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.121 | 0.256 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".