Fourteen propositions for resilience, fourteen years later
Bibliographic record
Abstract
In 2006, Walker et al. published an article titled, “A Handful of Heuristics and Some Propositions for Understanding Resilience in Social-ecological Systems.” The article was incorporated into the Ecology and Society special feature, Exploring Resilience in Social-Ecological Systems. Walker et al. identified five heuristics and posed 14 propositions for understanding resilience in social-ecological systems. At the time, the authors hoped the paper would promote experimentation, critique, and application of these ideas in resilience and social-ecological systems research. To determine the extent to which these propositions have achieved the authors’ hopes, we reviewed the scientific literature on social-ecological systems since the article was published. Using Scopus, we identified 627 articles that cited the Walker et al. article. We then identified and assessed the articles relative to each proposition. In addition, we conducted a more general Scopus review for articles that did not cite the Walker et al. article specifically but incorporated a proposition’s concepts. Overall, articles often cite Walker et al. as a reference for a definition of a heuristic or ecological resilience generally and not to reference a specific proposition. Nonetheless, every proposition was at least mentioned in the literature and used to advance resilience scholarship on social-ecological systems. Eleven propositions were tested by multiple articles through application of case studies or other research, and 7 of the 11 propositions were substantially discussed and advanced. Finally, three propositions were heavily critiqued either as concepts in resilience literature or in their application.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".