Executive‐parliamentary relations in Canada: Moving forward from the pandemic
Bibliographic record
Abstract
Abstract The pandemic caused governments worldwide to respond quickly to a greater array of health, economic and social issues in a more concentrated time span than previously. The Canadian public sector had developed many of the tools needed to act with agility to support the government agenda response to these challenges. With the consent of political parties, Parliament modified its operations and passed empowering legislation to provide the executive branch with sweeping powers to act. In this turbulent time, government accountability was delayed but never forgotten as a series of conversations with senior public servants revealed. This article delves into those reflections on the first year of the pandemic to discern how government operations changed and how both Parliament and the public sector can adapt to ensure that government can act effectively and efficiently but be held accountable for its decisions as it addresses more complex policy challenges in future.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.052 | 0.010 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".