Growth and the Environment in Canada: An Empirical Analysis
Bibliographic record
Abstract
Standard reduced‐form models are estimated for Canada to examine the relationships between real per capita gross domestic product and four measures of environmental degradation. Of the four chosen measures of environmental degradation, only concentrations of carbon monoxide appear to decline in the long run with increases in real per capita income. The data are also tested for the presence of unit roots and for the existence of cointegration between each of the measures of environmental degradation and per capita income. ADF and Phillips‐Perron tests indicate unit roots in the logs of the measures of all variables. The Engle‐Granger test and Johansen's maximum eigenvalue test suggest that a long‐term relationship between per capita income and the measures of environmental degradation does not exist. Causality tests also indicate bidirectional causality, not unidirectional causality, from income to the environment. The results suggest that Canada does not have the luxury of being able to grow out of its environmental problems. The implication is that to prevent further environmental degradation, Canada requires concerted policies and incentives to reduce pollution intensity per unit of output across sectors, to shift from more to less pollution‐producing outputs and to lower the environmental damage associated with aggregate consumption.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".