Allocating Property Rights Over Shoreline: Institutional Change in the Newfoundland Inshore Fishery
Bibliographic record
Abstract
THE NEWFOUNDLAND FISHERY played a pivotal role in the early exploration and development of North America, and provides a compelling case study of institutional change. As in the California gold rush (Umbeck 1977), private interests established a system of property rights in the absence of governmental authority. Yet the evolution of property rights in the Newfoundland inshore fishery was unique. The scarce resource in the inshore fishery was not fish — though the ease of catching them varied from year to year — but shoreline. The Newfoundland coast is characterized by limited amounts of flat and sheltered shoreline. There was a significant benefit to getting such ‘good’ shoreline, and in the absence of an agreed allocation system, ship captains would have fought over desirable locations. The key institutional challenge for the fishery was to allocate scarce ‘good’ shoreline in a manner that was both efficient and sufficiently equitable. This paper, then, does not analyze the allocation of fish stocks themselves — an issue that would become of great importance from the twentieth century — but of the shoreline used for processing fish. The paper seeks to provide economic rationales for three interrelated issues that are puzzling, at least from the perspective of economic history. In all three cases, these rationales provide both a theoretical underpinning for the course of institutional change in the Newfoundland fishery, and add new insights to scholarly understanding of institutional change more generally. First, was the “admiral system,” devised by the earliest migratory fishers to allocate shore space and govern-
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".