Accountability or Accounting? Elaboration of the Paris Agreement’s Implementation and Compliance Committee at cop 23
Bibliographic record
Abstract
This article provides an analysis of progress regarding the modalities and procedures for the Paris Agreement’s Implementation and Compliance Committee up to cop 23. I use the perspective of legal accountability to address three points of long-lasting divergence between parties: whether the Committee will be tasked to require parties to justify their performance by making specific reference to applicable legal standards; the contentious question of mandating the Committee to assess the progress of parties on the achievement of their ndc targets; and the involved party’s degree of control over the measures adopted. I conclude that a richer approach to accountability calls for granting a substantive role to practices of legal justification, assessment, and consequences within the modalities for the Committee in all three cases. Subject to political acceptance, such a mandate has the potential to foster parties’ sense of trust, reciprocity, and legal obligation toward one another. 1
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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 | 0.078 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 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".