Application of a contribution to sustainability test by the Joint Review Panel for the Canadian Mackenzie Gas Project
Bibliographic record
Abstract
Ultimately, the enhancement we need to deliver through environmental assessment is confidence that every approved undertaking will move us positively towards a desirable and durable future. In Canada, the most promising steps in this direction have been in several major project assessment reviews with public hearings and independent panels that applied a contribution to sustainability test. The most recent and advanced case is the review of a proposed C$16.2 billion natural gas infrastructure undertaking in the Northwest Territories. The Panel's application of the contribution to sustainability test compared the cumulative effects, equity and legacy implications of a range of project pace and scale alternatives. The Panel concluded that the project would offer positive overall contributions only if 176 recommendations were implemented. While the Panel's process was slow and the governments accepted only the most modest recommendations, the Panel's review set a new standard of analytical practice. This paper examines how the review was done and assesses its strengths and limitations, with particular attention to the design and application of the contribution to sustainability test.
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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 | 0.419 | 0.424 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.015 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".