Bibliographic record
Abstract
Utopian thinking has intersected with the practicalities of community-building for thousands of years, with today's ecovillages being one recent expression of this nexus.Many utopian or "intentional" communities founded in the aftermath of World War 2 are now over 50 years old and have demonstrated a capacity to survive numerous disturbances in that time whilst retaining their essential function, identity, and sense of common purpose.Such communities provide an opportunity to better understand which factors impact on community resilience from a social-ecological perspective, as well as illuminating the relationships between utopian thinking and resilience building in complex adaptive systems.In this paper we present a case study of Auroville, India, and aim to identify the factors that have enabled the community's resilience over the past five decades.Results are presented from a series of semistructured interviews with key stakeholders involved in management roles at Auroville and used to propose a model for community resilience at Auroville.The interview results confirm the broad applicability of the general resilience factors identified by previous researchers, especially the roles played by diversity, reserves, openness, modularity, nestedness, self-organization, and communication.The results also suggest other, more specific, factors have played a role in the social-ecological resilience of Auroville over time, including unity of purpose, creative mindset, and spiritual capital.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".