Climate Change Policy in Canada and Germany: A Comparative Analysis
Bibliographic record
Abstract
Climate change is an important issue. This paper will look at the climate change policy of Canada and Germany. In particular borrowing from Hessing et al.'s analysis of resource and environment policy by way of looking at the dynamics of policy networks, I will compare the climate change policy of Canada and Germany. Policy network analysis looks at the intersections of state and societal actors, and helps us to understand why we might see significant policy change and progression on the one hand or no change and only incremental progress on the other. Canada has gained a reputation for being a laggard when it comes to its national climate policy, whereas Germany has been praised for its more progressive approach and ambitious commitments to climate change policy. Using a framework inspired by Dr. Mark Winfield, in combination with policy network analysis, this paper will analyze Canada and Germany’s climate policy through an analysis of their institutional frameworks, political economic context, societal forces, and the ideas and discourses around the matter. The aim of this paper is to provide an analysis of the key problem areas for Canada’s climate change policy, through a comparison of Germany’s more progressive action on climate policy. In chapter one I will introduce the importance of climate change policy. In chapter two I provide an explanation of the significance of climate change and the science behind it. In chapter three I look at climate policy in Canada through an intuitional, political economic, societal and ideational framework in the context of policy networks and argue that jurisdictional ambiguity and the strong relationships between the state and economic interests have placed a significant barrier on moving forward on climate change. In chapter four, I apply this same framework to the German context and argue that the close ties between non-economic actors such as environmental groups and state officials, along with the overall general agreement within the climate policy community that action on climate change is required, has helped to foster a progressive climate change policy in the country. In chapter five I tie my arguments for each country together to highlight the key differences in the interactions of institutions, economic interests, societal actors, and the general ideas about climate change
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.024 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".