Strategic environmental assessment in the electricity sector: an application to electricity supply planning, Saskatchewan, Canada
Bibliographic record
Abstract
A strategic environmental assessment (SEA) framework for electricity sector planning is developed and applied to evaluate electricity supply scenarios for Saskatchewan, Canada. The overall goal of the SEA application was to identify a preferred future electricity production path, demonstrate the application of a quantitative SEA process that operationalizes sustainability principles through the use of assessment criteria, and examine the methodological implications resulting from the application of a structured SEA framework. Results of the application identified a renewables-focused electricity supply preference, but with several implications for electricity sector investment and sustainability, including increased infrastructure requirements and increased cost of electricity. Results also demonstrate a practical approach to the operationalization of sustainability through the application of assessment criteria that are linked to higher level principles. The use of structure in the SEA process provided for replicability, transparency and the ability to quantify issues of uncertainty in Plan, program and policy (PPP) decision-making, while at the same time maintaining flexibility to tailor the SEA framework to the electricity sector context.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".