Social Attractors: A Proposal to Enhance “Resilience Thinking” about the Social
Bibliographic record
Abstract
This article proposes social attractors as a way of addressing limitations in the functionalist sociology commonly applied to the social when examining ecological-social relations. It focuses on “resilience thinking” to argue the case. Resilience thinking is discussed (1) as an analytical strategy whereby ecological and social attractors perform analogous roles in a coordinated approach to ecosystems and social relations, and (2) as a social movement within the “new ecology” that institutionalized around the notion of resilence. The article begins by describing the institutionalization of resilience thinking. It then argues that functionalist assumptions about equilibrium contradict those of resilience thinking and lead to conflated views of social relations. The theoretical context of the social attractor, which stems from a synthesis of critical realism and Gramscian analysis of power, is outlined. Finally, the qualitative, nonlinear methodology that the social attractor facilitates is illustrated through a hypothetical example involving ecosocial relations.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.005 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".