Deep Decarbonization in Cities: Greenhouse Gas Emissions Measurement, Monitoring, and Reporting
Bibliographic record
Abstract
Municipalities have a significant role in reducing global emissions to net-zero by 2050. Local climate action has immense potential for driving the required emissions reductions, but the practices involved in measuring, target setting, monitoring, and reporting progress remain inconsistent and understudied. As a first step in improving these processes in Canadian municipalities, this study aims to develop an understanding of the current and historical state of measurement, target setting, monitoring, and reporting in the local climate action processes of Canadian municipalities and uncover insights into the best practices associated with higher emissions reductions. Qualitative data was collected from existing reports and documents from the Partners for Climate Protection (PCP) Program, developed and managed by ICLEI Canada and the Federation of Canadian Municipalities. Reports consisted of emission inventories, climate commitments, implementation updates, and other relevant documentation with information on measurement, target setting, monitoring, and reporting practices submitted as part of the PCP milestone review process. An evaluation framework was developed from the relevant literature on the topics and used to determine if the empirical results from Canadian municipalities validate or extend the literature on measurement, target setting, monitoring, and reporting. Through content analysis, this study contributed to several areas of the literature by validating previous findings and extending the literature to incorporate new findings on reporting levels, scope 3 emissions, and carbon sinks and storage. The results also extended the literature by identifying the involvement of council members and community-wide entities in monitoring procedures, the use of various reporting channels in sharing information, and the inclusion of monitoring procedure details in reporting, as additional key variables associated with high emissions reductions. These results will help inform the practices and strategies of municipal practitioners and provide information to government decision-makers to help identify policy opportunities. Finally, the evaluation framework from this study and the dataset developed in summarizing the empirical data can be used for triangulation, further analysis, or as a baseline comparison by future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".