Policy Perspectives on Education for Sustainable Development: Taking stock of the Field in the era of the UN Sustainable Development Goals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Education for sustainable development (ESD) has become a popular avenue to advance progress toward global goals linked to climate change, social issues and economic growth. For more than three decades, ESD has risen to prominence in international policy fora as a fundamental step in the implementation of a wide range of global development objectives. Particularly, following the adoption of the UN Sustainable Development Goals (SDGs), enthusiasm for ESD has grown rapidly. However, the current moment represents a break in the wave of support for global projects like the SDGs. Catastrophes like the COVID-19 pandemic and violent regional conflicts have elicited scepticism for global cooperation and the efforts of agencies like the United Nations (UN). Consequently, in 2024, the UN Secretary-General convened the Summit of the Future (SOTF) to revitalize multilateralism and reconcile the grievances of nations. Among those grievances were demands for more critical assessments of the transformative potential and relevance of the SDGs. Provoked by the recent global momentum, this special issue highlights key perspectives regarding how the international education community has rolled out ESD initiatives during the SDG campaign, with special focus on SDG Target 4.7. The commentaries offer valuable insights into concrete actions to enrich ESD, the evolving contours of policy production, and, more deeply, critiques of the underlying forces shaping the field. Following the SOTF, the degree to which the UN was successful in assuaging scepticism and re-mobilizing support for its mission is still to be determined. Rebuilding the trust and faith of nations is a long-term effort, but certainly, the range of voices emerging offers enriching new pathways for the field of ESD and across the development spectrum.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it