Bibliographic record
Abstract
Policy makers worldwide have increasingly considered the adoption of a carbon adjustment at the border to equalize carbon pricing on foreign goods with carbon policies imposed on domestic production. The implementation of a border carbon adjustment (BCA) in the European Union has been recently proposed by the European Commission, followed by similar plans in the United States and Canada, as an instrument designed to address concerns about competitiveness and emissions leakage resulting from the absence of a global price on carbon or an internationally coordinated carbon-pricing system. Despite its potential to address these issues, the implementation of a BCA raises concerns with respect to its impact on developing countries. A BCA will likely impose a disproportionate burden on developing countries with limited capacity to cut back emissions and thus violate the principle of common but differentiated responsibilities (CBDR) established in the United Nations Framework Convention on Climate Change. The main goal of this article is to examine CBDR's normative requirements and determine its legal implications for BCA design. The article further offers policy guidelines for implementing a CBDR-compliant BCA that addresses its ultimate purpose of reducing global greenhouse gas emissions while also supporting the development needs of less affluent countries.
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.
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 | 0.016 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".