The Effect of Trudeau’s New Senate Selection Process in Perspective: The Senate’s Review of Commons Bills, 1997-2019
Bibliographic record
Abstract
This article examines the Senate's role in the legislative process, traditionally described as providing sober second thought. Data on the Senate's treatment of bills already approved by the House of Commons were compiled and studied for the period 1997 to 2015 to reveal: how many Commons bill were amended by the Senate; how many were not passed by the Senate; how long it took for the Senate to consider Commons legislation; and whether the Senate takes a more activist approach to bills that were subject to time allocation in the Commons. The results of this analysis provide several insights for suggestions to improve the Senate’s role in reviewing bills passed by the lower house. Important differences are found between the treatment of government-sponsored bills and private members’ bills, with the latter far less likely to make it through the Senate before the end of a session. Possible bottlenecks in the Senate’s committee stage are also highlighted as an area which needs to be addressed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".