Carbon Emissions Embodied in Russia’s Trade: Implications for Climate Policy1
Bibliographic record
Abstract
According to the current international climate change regime, countries are responsible for greenhouse gas (GHG) emissions that result from economic activities within their national borders, including emissions from producing goods for export. At the same time, imports of carbon-intensive goods are not addressed by international agreements, including the Paris Agreement that was adopted in 2015. This paper examines emissions embodied in Russia’s exports and imports based on the results of an input-output analysis. Russia is the second largest exporter of emissions embodied in trade and the large portion of these emissions is directed to developed countries. Because of the large amount of net exports of carbon-intensive goods, the current approach to emissions accounting does not suit Russia’s interests. On the one hand, Russia, as well as other large net emissions exporters, is interested in the revision of allocation of responsibility between exporters and importers of carbon-intensive products. On the other hand, both the commodity exports structure and relatively carbon inefficient technologies make Russia vulnerable to the policy of “carbon protectionism,” which can be implemented by its trade partners. Full text available at: https://doi.org/10.22215/rera.v11i2.1192
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".