A comparative assessment of the clean development mechanism and Alberta's carbon offset system
Bibliographic record
Abstract
This thesis is an assessment of Alberta’s Carbon Offset System (ACOS) using the Kyoto Protocol’s Clean Development Mechanism (CDM) as a comparator. ACOS is a hybrid policy, having features of both command-and-control and market based instruments. The objective of implementing ACOS within Alberta’s overall greenhouse gas (GHG) emissions mitigation strategy is to provide a cost-effective alternative for regulated facilities to meet their emissions reduction obligations. Offsets generated pursuant to the ACOS are permitted as equivalent alternatives to actual emission reductions under the Specified Gas Emitters Regulation (SGER). The integrity of the emissions intensity limits within the SGER is dependent on the ability of ACOS to generate real, permanent, additional and verifiable offsets that can be substituted for actual emission reductions without any net loss to the environment. The aim of this thesis is to draw lessons from fifteen years of CDM’s “learning by doing” experience and to make recommendations for the reform of the ACOS. This thesis highlights the urgent need for cross-disciplinary and empirical research on the workings of the ACOS; it also highlights the fact that cost-effectiveness is an illusion and the concept of neutrality upon which carbon offsetting is premised needs to be reconsidered as the process of commodification does not result in offsets that are perfectly substitutable with actual emissions reductions. Proposals for reforming the ACOS include imposing limits on the use of offsets, recommending market oversight for offset trades that are currently traded over-the-counter, narrowing the scope of ACOS to a single gas system and enhancing the verification process by eliminating conflict of interest dilemmas.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".