The Gerrymander and the Commission: Drawing Electoral Districts in the United States and Canada
Bibliographic record
Abstract
The political systems of the United States and Canada differ substantially — the United States uses a presidential system with a bicameral legislature and Canada uses a prime ministerial model dominated by the House of Commons. However, both states rely on a first-past-the-post plurality electoral system wherein candidates face off in single-member districts with the largest votegetter winning. As such, each nation must use some procedure to draw legislative maps so that politicians and voters may know where district boundaries end.The two nations, however, have settled upon fundamentally different models for drawing districts and for judging the validity of those districts. While political actors dominate districting in the United States, Canadian districts are drawn by independent commissions. Likewise, while American districts must be practically equal in population, Canadian districts may differ substantially to advance the interests of effective representation.This essay analyzes the differences between American and Canadian models of districting and seeks to explain the origin of those differences. Part II looks at the American model of districting and the high levels of judicial scrutiny imposed on American districts. Part III looks at Canadian districting, the rise of independent reapportionment commissions, and the broad deference Canadian courts give to them. Finally, Part IY argues that the differences between the United States and Canada are path dependent, based primarily on minor decisions made early in the two nations' histories, incidental variations that have made reform easier at different times in the two countries, and differences in settlement patterns and demographics.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".