Marine Boundary Delimitation for Ocean Governance
Bibliographic record
Abstract
There is a Canadian project entitled ”Good governance of Canada’s Oceans: the Use and Value of Marine Boundary Information” which involves research investigating three case studies to represent typical coastal and offshore boundary issues: the delimitation of the extended continental shelf; the creation of boundaries for a Marine Protected Area (MPA); and a provincial marine administrative boundary. In each case study the research objectives include understanding information requirements for governance, modeling boundary uncertainty, and using ocean mapping technologies to illustrate the delimitation issues. This paper outlines the progress of the research to date and highlights the significance of taking a multi-disciplinary approach in boundary delimitation. Surveyors generally assume that good boundaries make good neighbours yet a case can be made that sometimes more precise boundaries may not be the best solution. For example, social scientists have expanded the original concept of clarifying ocean boundaries to include the possibility of leaving boundaries undefined in order to promote co-management arrangements. The legal interpretations of jurisdiction, administration, and title have also broadened the concept of a 3-D marine parcel to a complex series of overlapping interests offshore. Ocean mapping technology is being used to create and communicate alternative boundary solutions, including ecological boundaries defined by bottom type. The challenges in creating a marine cadastre for Canada is also discussed. CONTACT
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.018 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".