Bibliographic record
Abstract
Garrett Hardin's “tragedy of the commons” metaphor is commonly invoked to account for the unfortunate state of world fisheries. But the world s oceans are no longer a global commons and have not been so for the past two decades. Open-access regimes have persisted within many exclusive economic zones (EEZs) during this time, but coastal states' authority to regulate domestic fisheries has existed for more than a generation. Faced with the prospect of Hardin's tragedy, coastal states have had more than twenty years to devise institutional constraints that would prevent it. This article asserts that the dismal experience with EEZs is in large part attributable to distributive bargaining problems that arose within coastal states in the wake of EEZ extension. Moreover, the article argues that high levels of uncertainty that characterize the early stages of institutional development have exacerbated these problems. Finally, the article demonstrates how the variety of institutional designs and paths of institutional development that are observed in the cases of Iceland, Norway, and Atlantic Canada result from the different configurations of political power and political structure within each case. While the empirical discussion is focused upon property rights and fisheries, the theoretical discussion of bargaining and uncertainty has widespread application across comparative and international politics.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".