The Clean Development Mechanism: a review of the first international offset programme
Bibliographic record
Abstract
This review article examines the primary issues, the successes and the challenges of the Clean Development Mechanism (CDM), established under the Kyoto Protocol. It is the primary international greenhouse gas (GHG) emissions offset programme in existence today, and while not perfect, it has helped to establish a global market for GHG emission reductions. It generates offsets through investments in developing countries. The CDM has managed to establish – in its relatively nearly decade of existence –a credible, internationally recognized, multibillion dollar carbon offset market with participation from a large number of developing countries and private investors. It has also created processes and methodologies that other programmes are already emulating. A vast amount of work and investment – by participating countries, the private sector, and the UNFCCC secretariat – has gone into developing the CDM's rules, procedures and institutional structures. The creation and rapid growth of a large and unprecedented international programme, however, has not been without its challenges or controversies. Issues have been raised regarding the governance of CDM, the quality of approved projects and the contribution of CDM to sustainable development.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".