Bibliographic record
Abstract
This research is an enquiry to find an electoral formula that conforms to Canadian constitutional values. Three core values that are pertinent to the issue of electoral systems are identified: democracy, diversity, and efficiency. Each of these core values is divided into different aspects. These aspects will form the backbone of the evaluation of different electoral systems in this work. I begin with an evaluation of the plurality model of elections, which is currently used in Canada. I demonstrate that many of the attributes of the current system are not in tune with Canadian constitutional values. Next, I examine proportional systems and demonstrate that these systems too have problems of their own. In the next stage, I make a new proposal for elections to the Canadian Parliament. I introduce a new variant of the majority model, which I call a majority-preferential two-round variant. I demonstrate that this new variant will outperform the other variants in the attainment of values. Finally, I argue that the combination of a House of Commons elected through the majority-preferential formula and a proportionally elected Senate will result in a more balanced approach to the values.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".