Reform of the Electoral System in Canada and in Hungary
Bibliographic record
Abstract
I IntroductionReform of the electoral system is and has been a timely topic in both Canada and Hungary.In Canada, the reform was part of Justin Trudeau's election manifesto and, as his party won the majority of the seats in 2015, a reform process began. 1 However, as we explain later, it was abandoned in February 2017. 2 In Hungary, although the system was reformed in 2011, the electoral system is subject to heated debate for reasons discussed later in this paper.In autumn 2017, eight opposition political parties took part in a deliberation process aiming to propose a new electoral system.3 To assess the chances, impact, and democratic consequences of a possible reform, many factors need to be taken into consideration.First, the current electoral and party systems need to be examined in order to gain a full understanding of the mechanisms and shortcomings of the current systems.Deficiencies emerged in both Canada and Hungary with respect to the distribution of seats compared to the percentage of votes, which, according to the reformist voices, require the reform of the current majoritarian systems towards more proportional ones.Second, the rules regarding reform and the main institutional actors play an important role as well.These include who has the power to amend the system and whether the amendment of the constitution is needed.It also covers the reform procedure, and whether János Mécs* Reform of the Electoral System in Canada and in HungaryTowards a More Proportional Electoral System?
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.011 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".