Happiness and Sustainability Together at Last! Sustainable Happiness.
Bibliographic record
Abstract
Sustainable happiness is “happiness that contributes to individual, community and/or global well-being without exploiting other people, the environment or future generations” (O’Brien, 2010a, n.p.). It underscores the interrelationship between human flourishing and ecological resilience. At the national and international levels, sustainable happiness has considerable relevance to the United Nations’ resolution on happiness and well-being (United Nations, 2011). Applications of sustainable happiness are discussed, with implications for fostering healthy, sustainable lifestyles and communities. The active debate about how to transform education to meet 21st-century learning needs ranges from suggestions that will merely tweak existing models through modernization, to calls for reimagining the role of education. As educators consider the future of education and the various visions that are promoted—such as 21st-century learning, Health Promoting Schools programs, social and emotional learning, and entrepreneurship education—the concept of sustainable happiness can contribute to the development of a unified vision that fosters well-being for all, forever (Hopkins, 2013). The sustainable happiness pre-service teacher education course described in this paper gives a glimpse of the benefits of doing so. The paper argues that sustainable happiness represents the evolution in happiness that is needed to set the world on a more sustainable trajectory. This makes sustainable happiness indispensable for new visions of education in the 21st century. Keywords: sustainable happiness; well-being; sustainability; education; 21st-century learning
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.025 | 0.009 |
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".