Lack of consideration of ecological connectivity in Canadian environmental impact assessment: Current practice and need for improvement
Bibliographic record
Abstract
This study seeks to understand the extent to which ecological connectivity has been considered in EIA in Canada. Several factors that may influence the consideration of connectivity were analyzed in an evaluation of 14 environmental impact statements (EIS) obtained from the Canadian Impact Assessment Registry. Connectivity is largely absent from the EIA process, and even projects that attempted to consider connectivity lacked the rigor required to effectively assess impacts on connectivity. Projects that included connectivity as a valued component performed somewhat better, whereas the assessment of connectivity was not affected by different federal environmental acts (CEAA 1992 vs. CEAA 2012), development sectors, or proponent types. Between sections of the EIS, a significantly greater number of evaluation criteria were met in the scoping section compared to all other sections. Without adequate guidance, connectivity analysis in EIA has been conducted ad hoc, with considerable variation in quality. Including connectivity consideration in EIA legislation would provide a legal framework to address the lack of policies, standards, and assessment guidelines. We provide recommendations for integrating connectivity in EIA in Canada and elsewhere.
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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 | 0.132 | 0.239 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.023 | 0.032 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.021 | 0.011 |
| Open science | 0.009 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".