Issue Responsiveness in Canadian Politics: Are Parties Responsive to the Public Salience of Climate Change in the Question Period?
Bibliographic record
Abstract
This paper explores how politicians respond to the public salience of policy issues when determining which topics to publicly address. Using new data and state-of-the-art methodology, our study provides a fresh perspective on this fundamental question. We focus on a multi-party parliamentary system, specifically the Canadian House of Commons, with a specific emphasis on the issue of climate change. To assess the attention given by political parties to various policy issues, we analyze transcripts from the Question Period spanning from April 2006 to June 2021. To gauge the public’s level of concern for these issues, we incorporate data obtained from Google Trends. Employing an instrumental variable estimation strategy, our study causally estimates the extent to which the public salience of climate change influences elite attention. Our findings reveal that the public salience of climate change significantly influences the attention given to this issue by parties, albeit with noticeable partisan variations. Moreover, our research highlights the effectiveness of the Question Period in compelling the government to address challenging or potentially embarrassing issues. Lastly, we uncover evidence suggesting that the Liberal Party of Canada successfully increased the public salience of climate change during its tenure in government.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".