Bibliographic record
Abstract
Developing institutions to handle human-environment interactions well is important. In relation to that, the theory of resource regimes, and the themes of fit, interplay, and scale-as originating not least in the work of Oran Young-are core. His work is very impressive. At the same time we observe two sets of issues where we think further development is needed. The first relates to the ontological underpinning of Young's conceptual framework. The second set of issues concerns the definitions of and the relationships between the concepts of fit, interplay, and scale. Regarding the former, we emphasize issues related to "marrying" different theories about human action. Regarding the latter, we note that while the three concepts have a lot of practical appeal, there are still some important challenges surfacing, not least when using them in empirical research. We analyze three challenges: the definitions of the concepts; their internal overlap; and finally, the way environmental regimes are defined and understood as opposed to the wider institutional context of the economy. Our paper offers some direction for how to move forward on the issues specified.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.004 | 0.051 |
| Scholarly communication | 0.007 | 0.019 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".