QUALITY OF LIFE AND SOCIAL CAPITAL IN SUSTAINABLE INTENTIONAL COMMUNITIES
Bibliographic record
Abstract
Members of eco-communities have reported high levels of both Quality of Life and Social Capital, while at the same time, living in a way that is in harmony with the environment. Quality of Life scores indicate residents’ level of well-being on a community level, and Social Capital scores indicate the degree of harmonious interactions among fellow community members. The information gathered from this research is useful in understanding contemporary society’s way of living and interacting with each other and the world. From the eco-community model, we may be able to incorporate more sustainable ways of living into current society without having to suffer from a reduced Quality of Life. The evidence has indicated that an attitude shift is in order – an attitude that places less emphasis on built capital and more emphasis on social and natural capital. In other words, interactions with friends, family, neighbors, and the environment should be valued more highly than having access to or owning goods and services and receiving a high income. From this, we can retain a high Quality of Life, and its associated emotional well-being and mental health benefits, while reducing the reliance on material consumption, along with its associated wastefulness and environmental destruction. Sustainable development and sustainable living practices can be incorporated into mainstream society based on the eco-community model. This will hopefully avert a crisis in energy consumption, and ultimately improve the good of all.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".