La transition vers une prospérité durable - Un modèle macroéconomique écologique stock-flux cohérent pour le Canada
Bibliographic record
Abstract
This paper presents a stock-flow consistent (SFC) macroeconomic simulation model for Canada. We use the model to generate three very different stories about the future of the Canadian economy, covering the half century from 2017 to 2067: a Base Case Scenario in which current trends and relationships are projected into the future, a Carbon Reduction Scenario in which measures are introduced specifically designed to reduce Canada's carbon emissions, and a Sustainable Prosperity Scenario which incorporates additional measures to improve environmental, social and financial conditions across society. The performance of the economy is tracked using two composite indicators constructed especially for this study: an environmental burden index (EBI) which describes the environmental performance of the model; and a composite sustainable prosperity index (SPI) which is based on a weighted average of seven economic, social and environmental performance indicators. Contrary to the widely accepted view, the results suggest that ‘green growth’ (in the Carbon Reduction Scenario) may be slower than ‘brown growth’. More importantly, we show (in the Sustainable Prosperity Scenario) that improved environmental and social outcomes are possible even as the growth rate declines to zero.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".