A Review of “ <i>Learning and Sustainability in Dangerous Times</i> ” - S. Sterling (2024). <i>Learning and Sustainability in Dangerous Times</i> . Agenda Publishing.
Bibliographic record
Abstract
StephenSterling's lifelong work lies at the crossroads of sustainability, education, and the study of preferable futures for society.His most recent book, Learning and Sustainability in Dangerous Times, offers a curated selection of his past writings and also provides new chapters, exploring alternative paradigms and the meaning of education in challenging times.The book serves as both an introduction to his academic work and a contribution to the field of sustainability education.While forming a coherent whole, chapters can be read as a stand-alone piece.This book explores critical questions to achieving a sustainable society and demonstrates how learning and education can play a decisive role in such an endeavour.Central questions addressed include: What is the nature of the change in consciousness necessary for creating a more ecologically sustainable and liveable world?What changes are required in the way we view and practice education to contribute fundamentally to this shift?(p.4).Striving to articulate a "robust and convincing alternative educational paradigm" (p.69), Sterling aims to help shift education and society toward a preferable future, making a case for contributing to the ongoing Great Transition Initiative (GTI).Sterling's central argument is that achieving a sustainable future requires transcending the mechanistic view of reality, which is identified as "the root cause of today's social and ecological crises" (p.5).Whereas a mechanistic worldview is characterised by "anthropocentrism, individualism, materialism, consumerism, economism, and extractivism," a relational or ecological worldview is "consistent with the Earth-centered worldviews that characterize indigenous cultures" (p.5).The message is clear: "If we want a sustainable future, we need to think relationally" (p.177).The term "sustainable education" describes change in educational culture based upon ecological worldviews.As Sterling highlights, sustainable education is "more than an isolated 'education for sustainability' programme, it is about a shift of personal consciousness and educational culture" (p.188).This shift, he contends, is possible through transformative learning, which can lead to "qualitative shift in perception and meaning making [ : : : ] such that the learner questions or reframes his/her assumptions or habits of thought" (p.151).Building on the work of Gregory Bateson (2002Bateson ( , 2008)), Sterling explores how learning involves and affects different levels of knowing and of consciousness, and when those shift, new alternatives and perspectives are
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".