Pipelines and Parks: Evaluating External Risks to Protected Areas from the Proposed Northern Gateway Oil Transport Project
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Protected areas increasingly face degradation from both internal and external stressors. One increasingly relevant external threat is oil contamination, which has well documented negative impacts on terrestrial and aquatic ecosystems. To evaluate such potential threats in environmental management, risk analysis has expanded as a discipline. Here, we derive a risk index for protected areas in British Columbia, Canada, that are located downstream from the proposed Northern Gateway pipeline along its 680 km route across the province. Using a Geographic Information System (GIS) approach, our risk model incorporates both the probability of oil -once spilled -contaminating a park and the consequence of such exposure. We identified 34 protected areas located downstream and potentially at risk. Two were within 50 meters of the proposed pipeline route. Of downstream parks, we found that some were at twice the risk of others. In general, higher risk parks were not any closer to the pipeline but were, on average, of larger areas. The Fraser River watershed, which hosts British Columbia's most economically valuable salmon runs, contained the most parks at risk. From an environmental impact assessment and park management perspective, our results can help identify and evaluate the potential adverse effects of pipeline ruptures. The information can be used to determine, systematically, which parks most urgently require spill response plans and where baseline environmental monitoring might be best deployed. Given that oil transport, a rapidly growing enterprise, is only one of many stressors that threaten natural areas, decisions concerning industrial proposals benefit appreciably from risk analysis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it