Environmental and sustainability education policy research: a systematic review of methodological and thematic trends
Bibliographic record
Abstract
This paper reports on a systematic literature review of policy research in the area of environmental and sustainability education. We analyzed 215 research articles, spanning four decades and representing 71 countries, and which engaged a range of methodologies. Our analysis combines quantification of geographic and methodological trends with qualitative analysis of content-based themes. Significant findings included temporal spikes in published policy research occurring in the mid-1970s, late 1990s, and after 2005, as well as geographic under-representation of Africa, South and Central America, Eastern Europe, and North and West Asia. The majority of articles reviewed were non-empirical; empirical articles overwhelmingly focused on teaching and learning directives, rather than exploring the complexity of policy development or enactment. We conclude our analysis by describing key research gaps as highlighted by the review and propose directions for moving forward policy research in environmental and sustainability education. In particular, we suggest greater research attention to critical policy theory and methodology, issues of intersectionality, and climate change education policy research. By outlining in greater detail the policy research that has been undertaken to date, the review provides a platform for a broadened diversity of policy studies in environmental and sustainability education.
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 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 | 0.045 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.039 | 0.048 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".