Bibliographic record
Abstract
In the period since 1936, Quebec has gone through two eras of party politics, the first between the Liberals and the Union Nationale, the second and ongoing era between the Liberals and the Parti Québécois. This study examines elections in Quebec in terms of all relevant types of electoral bias. In both eras the overall electoral bias has clearly been against the Liberal Party. The nature of this bias has changed however. Malapportionment was crucial through 1970, and of minimal importance since the 1972 redistribution. In contrast gerrymandering, ultimately involving an ‘equivalent to gerrymandering effect’ due to the geographic nature of Liberal core support, has been not only a permanent phenomenon but indeed since 1972 the dominant effect. The one election where both gerrymandering and the overall bias were pro-Liberal — 1989 — is shown to be the ‘exception that proves the rule’. Finally, the erratic extent of electoral bias in the past four decades is shown to arise from very uneven patterns of swing in Quebec.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".