Bibliographic record
Abstract
This Special Feature, "Nudging Evolution? Critical Exploration of the Potential and Limitations of the Concept of Institutional Fit for the Study and Adaptive Management of Social-Ecological Systems," aims to contribute toward the development of social theory and social research methods for the study of social-ecological system dynamics. Our objective is to help strengthen the academic discourse concerning if, and if so, how, to what extent, and in what concrete ways the concept of institutional "fit" might play a role in helping to develop better understanding of the social components of interlinkages between the socioeconomic-cultural and ecological dynamics of social-ecological systems. Two clearly discernible patterns provide a map of this Special Feature: (1) One pattern is the authors' positions regarding the place and role of normativity within their studies and assessment of institutional fit. Some place this at the center of their studies, exploring phenomena endogenous to the process of defining what constitutes institutional fit, whereas others take the formation of norms as a phenomenon exogenous to their study. (2) Another pattern is the type of studies presented: critiques and elaborations of the theory, methods for judging qualities of fit, and/or applied case studies using the concept. As a body of work, these contributions highlight that selfunderstanding of social-ecological place, whether explicit or implicit, constitutes an important part of the study object, i.e., the role of institutions in social-ecological systems, and that this is, at the same time, a crucial point of reference for the scholar wishing to evaluate what constitutes institutional fit and how it might be brought into being.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.044 |
| Scholarly communication | 0.009 | 0.026 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".