Inequality is driving the climate crisis: A longitudinal analysis of province-level carbon emissions in Canada, 1997–2020
Bibliographic record
Abstract
The authors conduct a comprehensive analysis of the relationship between carbon emissions and income inequality for the Canadian provinces for the 1997 to 2020 period. The results indicate that the short-run and long-run effects of the income share of the top 10 % and the top 5 % on province-level emissions are positive, robust to various model specifications, net of multiple demographic and economic factors, not sensitive to exogenous shocks or outlier cases, symmetrical, statistically equivalent for emissions from different sectors, and their short-term effects do not vary in magnitude through time. The findings also consistently show that the estimated effect of the Gini coefficient on province-level emissions is not statistically significant. Overall, the results underscore the importance in modeling the effects of income inequality measures that quantify different characteristics of income distributions, and they are very consistent with analytical approaches regarding power concentration, overconsumption, and status competition that suggest that a higher concentration of income leads to growth in anthropogenic carbon emissions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".