What Difference Does CBDR Make? A Socio-Legal Analysis of the Role of Differentiation in the Transnational Legal Process for REDD+
Bibliographic record
Abstract
Abstract This article offers a socio-legal analysis of the role played by the principle of common but differentiated responsibilities (CBDR) in the development, diffusion, and implementation of jurisdictional REDD+ activities throughout the developing world. It employs a qualitative research method known as process tracing to uncover whether and, if so, to what extent and how actors have used CBDR to support the emergence and effectiveness of the transnational legal process for REDD+. The article argues that the transnational legal process for REDD+ reflects a conception of CBDR in which developing country governments may take on voluntary commitments to reduce their carbon emissions, with the multilateral, bilateral, and private sources of financial support and technical assistance provided by developed countries, international organizations, non-governmental organizations, and corporations. This creative conception and application of CBDR has fostered the construction and diffusion of legal norms for REDD+ because it has influenced the interests, ideas, and identities of public and private actors in the North and South. However, the early challenges associated with the implementation of REDD+ reveal a worrying gap between the financial pledges made by developed countries and the costs associated with the full implementation of REDD+, as well as contradictions in the very way in which the responsibilities of various countries have been defined in the context of REDD+. The analysis has important implications for the transnational governance of REDD+, as well as for scholarship on the role of differentiation in the pursuit of effective and equitable climate change solutions.
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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 | 0.039 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.064 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| 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".