Bibliographic record
Abstract
Common pool resources (CPRs) are noted for their excludability and subtractability issues and early academic commentary stressed that due to the resources' complexity and uncertainty, management efforts were futile and a "tragedy of the commons" was the end result. Recent academic commentary has challenged this end result and has elaborated institutional design principles to sustainably manage CPRs which include the need for nested institutional arrangements (NIAs). However, little is known about how to move between the two extremes, that is, how we change public policy in a move towards and the sorts of institutional innovations that lead us to greater sustainability. This research begins to unravel nested institutional arrangements. It develops a framework for what constitutes a nested institutional arrangement and measures their effect on groundwater policy changes (frequency, type, magnitude) under different conditions of uncertainty as applied to a comparative case study between the Great Lakes Basin (high uncertainty; Ontario, New York) and the Ogallala Aquifer in the U.S. Midwest (low uncertainty; Nebraska). This dimensional mapping reveals the centrality of the nature of the linkages between governance units (especially linkage functionality), linkage complementarity and the effects of diffuse authority structures. In short, it is possible to unravel what an NIA is from the various strands in the literature and to develop linkages between NIAs and outcomes for particular situations (e.g. high vs. low uncertainty areas) in relation to common pool resources (e.g. groundwater). The results provide theoretical guidance for the study of groundwater policy changes by staking out the broad parameters of a strategy for groundwater policy change.
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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".