Bibliographic record
Abstract
The reform of Canada’s federal electoral system was a key platform promise of the Liberal party throughout the 2015 election campaign. Justin Trudeau famously proclaimed that the 2015 federal election would be the last in Canada under a first-past-the-post (FPTP) system; but, as several years followed, there was no change, and discourse surrounding the issue has largely fizzled out (Small, 41). Canada’s FPTP system has not changed since confederation, and it remains among only four other democracies worldwide that use “this archaic electoral system” (Rebick). FPTP is considered to create two main issues in Canadian politics: distortion of votes, and heightened regionalism. Voting behaviour and outcomes are currently distorted through unequal vote weight, ‘wasted votes’, and the phenomenon of strategic voting. Regionalism leads to national division, skews which issues are considered electorally important, negatively alters party behaviour, and changes how political preferences are perceived in Canada. Together, these effects are disengaging the Canadian public from political participation. This paper will explain the ways in which vote distortion and regionalism plague Canada’s current electoral system and the health of its democracy, and demonstrate how a shift towards a mixed-member proportional representation (MMPR) electoral system can alleviate those issues. Specifically, MMPR’s provision of a broader second vote nullifies the effect of wasted votes and strategic voting, while discouraging political parties from engaging in behaviour that targets specific electoral regions and produces political polarization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.375 | 0.180 |
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".