An environmental economic model for policy analysis in Canada and the United States: Binational economic input-output life-cycle assessment (EIO-LCA)
Bibliographic record
Abstract
A new generation of global environmental problems has highlighted the importance of holistic policy-development. Despite a rhetorical bias toward a global economy there has to-date been a lack of effective and transparent tools for assessment of cross-border environmental impacts. This work addresses this need by developing new environmental economic models for Canada and the US, based on a modeling approach is known as Economic Input-Output Life-Cycle Assessment (EIO-LCA), and an innovative binational EIO-LCA model to obtain novel insights into urban planning and the effect of international trade. In applying the model, we show that low density development is more energy and greenhouse gas intensive (by a factor of 2.0 to 2.5) than high density urban core development on a per capita basis. We also show that US industries are approximately 1.15 times as energy intensive and 1.3 times as GHG intensive as their Canadian counterparts, largely due to a heavy reliance on fossil fuels in the US.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".