Carbon Taxation and Policy Labeling: Experience from American States and Canadian Provinces
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A vast economics literature embraces taxation of the carbon content of fossil fuels as the superior policy approach for reducing greenhouse gas emissions. However, experience around the world suggests that carbon taxes face exceedingly difficult political hurdles. Federal experience in the United States and in Canada confirms this pattern. This article reviews sub‐federal policy development among American states and Canadian provinces, a great many of which have pursued climate policy development. With one major exception, explicit carbon taxation appears to remain a political nonstarter. At the same time, states and provinces have been placing indirect carbon prices on fossil fuel use through a wide range of policies. These tend to strategically alter labeling, avoiding the terms of “tax” and “carbon” in imposing costs. The article offers a framework for considering such strategies and examines common design features, including direct linkage between cost imposition and fund usage to build political support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it