Review Essay - Democratic Leviathan: Defending First-Past-the-Post in Canada
Bibliographic record
Abstract
This review essay examines a number of recent books claiming to offer a defence of Canada's traditonal first past the post voting system. The works can be divided into two camps, one Conservative, the other liberal, though their logic, arguments, and evidence are surprisingly similar. Through a detailed engagement with each work, this review argues that both versions ultimately defend first past the post as an effective ‘democratic leviathan’ in that the voting system tends to produce a strong, single party legislative majority government that can rule unhindered while it remains in office. Thus, for these authors, considerations of stability and legislative efficiency trump all other concerns e.g. representation, diversity, majority rule, electoral competitiveness, etc. However, in making their case, the contributors largely fail to seriously engage opposing views or the relevant academic literatures, particularly relevant Canadian work.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".