Educating in and for Degrowth: Training Future Generations to Prevent Environmental Collapse
Bibliographic record
Abstract
This research has been developed through a literature review on the importance of and current approach in the education system to the present environmental and ecosystemic crisis and the training of future generations in degrowth in the Spanish education system. To this end, a systematic literature review (SLR) has been carried out following the standards of the PRISMA declaration. In total, 40 articles published between January 2005 and March 2024 were selected from the following databases: Scopus, Dialnet, Web of Science and Scielo. The findings show it is a relevant topic in school education as a concern, but it is not reflected in educational practice; that it has been incorporated into the curriculum, but sporadically, decontextualised and more focused on ‘sustainable development’; also, it lacks critical questioning of the unlimited growth and consumption model that capitalism entails. The study concludes that it is crucial to incorporate degrowth in a transversal way in education at all schooling levels, and to reform the curricula of the faculties of education in all universities so that the pedagogy of degrowth is a priority in the training of future teachers.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".