Theories of institutional change and marine privatisation
Bibliographic record
Abstract
Abstract Privatisation, as a process that assigns more individual property rights, implies in most cases institutional change. Privatisation might occur on the level of society, when formal laws, but often also informal rules are changing, or it might take place on an organisational level when an asset under an open access regime, a cooperative, or a state-owned company is converted into a privately managed entity. From this perspective, it seems obvious that theories of institutional change provide a certain understanding of privatisation processes in the marine realm. Processes of marine privatisation are very heterogeneous in their characteristics: some processes are informal, some take part in the business world, others in the political realm, some are to a certain degree planned, others are emerging and have more evolutionary characteristics, some are characterised by huge power asymmetries others take place under more equal footing. Therefore, this paper interrogates a broad range of theories of institutional change. Our perspective does not proclaim or investigate superiority of one theory above the other, but rather inquires about fit . After elaborating on the theories, clarifying their focus, core concepts and assumptions, the paper illustrates the explanatory powers of the theories by looking at the case of privatisation of space in Saint Louis, Senegal. Due to strong restrictions for Senegalese fishers to fish in Mauritanian waters, the establishment of a marine protected area, and more recently the establishment of a gas field on the doorstep, fishers are confronted with an enclosure of their commons.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".