Offshore Oil and Marine Protected Areas: Stakeholders, Conflicts and Future Directions in Nova Scotia, Canada
Bibliographic record
Abstract
Nova Scotia is invested in expanding hydrocarbon exploration offshore to boost its economy. A call for bids is carried out by the Canada-Nova Scotia Offshore Petroleum Board every year to award licenses to operators for exploration through a competitive bidding process. But offshore petroleum expansion competes for space in one of the most productive Atlantic coastal regions. Nova Scotia leads seafood exports in the country (valued at $2 billion) and a growing network of protected areas support an immense diversity of marine life. There is a complex interplay of actors in the region. Map of the Scotian shelf (King and MacLean, 1974).1 1 King, L. H. & MacLean, B. (1974). Geology of the Scotian Shelf and Adjacent Areas. 1:1,000,000. In Marine Sciences Paper Series No. 7 G.S.C. Paper No. 74-31. First edition. Ottawa: Canadian Hydrological Service. iii With a view to understand the tensions and trade-offs between marine conservation and development, and associated actors, policies and governance, I focus on the call for bids process. Any future activity in the region depends on this critical decision point. Which marine users, and to what extent, are involved in decision-making? Has the process changed over time? Does conflict arise where call for bids are close to protected areas and fishing grounds? To what extent is conflict mitigated or resolved, and in what ways? What role can marine spatial planning play to achieve sustainable outcomes? This was a collaborative research project aimed at addressing these questions through a qualitative study involving 25 marine stakeholders. Dr. Fraser and I conducted most of the interviews together in Nova Scotia, Ottawa and online. After discussions with Drs. Fraser and Carter about the analysis, I undertook the N-Vivo analysis and wrote the two articles that are my major paper (in manuscript format for separate journals). Drs. Fraser and Carter provided comments on those drafts. The first paper examines case studies of overlap between conservation and extractive resource development. The second, evaluates the effectiveness of Strategic Environmental Assessments, used to inform licensing decisions and to mitigate conflict in early stages of planning. Both articles address stakeholder difficulties and room for improvement. Marine spatial planning is discussed as a process to appease extractive resource conflicts, but it is still quite early to tell whether it will.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".