Stasis and change: social psychological insights into social-ecological resilience
Bibliographic record
Abstract
Ecologists have used the concept of resilience since the 1970s.Resilience also features in many of the social and economic sciences, though in a less central role and with a variety of interpretations.Developing a fuller understanding of the concept of socialecological resilience promises advances in how science can contribute to achieving better environmental outcomes, locally and globally.Such a development requires articulation of different perspectives on resilience and critical engagement across those perspectives.We present, in some detail, a particular perspective on resilience developed by the pioneering social psychologist Kurt Lewin.We suggest that Lewin's explicit use of social-ecological systems in his framework presaged much of the current social-ecological understanding of resilience.We set out some key details of his framework, notably the characteristics of his field theory, his use of group dynamics as a vehicle for social change, his introduction and development of the principles of action research, and his three-step change model.We conclude by mentioning some areas of the framework that are under-theorized or not theorized at all.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.056 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".