Electoral redistricting and minority political representation in Canada and the United States
Bibliographic record
Abstract
This article compares the political representation of visible minorities in Canada and the United States, focusing on differences in federal redistribution (redistricting) practices and constituency composition. Although the two countries both use territorially‐based electoral systems, they operate under different legal standards and institutional environments for the creation of ridings (districts). In the US, redistricting is a highly political process, yet must respect strict population equality standards. Litigation over redistricting is common, and courts adjudicate voting and representation under a constitutional system enforcing strong individual rights. In contrast, Canada's redistribution process is relatively nonpartisan, permits large population variances among ridings, places more emphasis on community rights, and is seldom subject to extensive court challenges. Despite these differences, the two countries exhibit striking similarities in the overall level of visible minority representation relative to population share. Conversely, Canada's population inequalities among ridings create a systematic disadvantage for visible minorities. Political attention to visible minority representation is stronger in the US, but the means to achieve it are constrained both by the judicial limits on group representation and the constitutional limits on the use of racial identity. Canada has a framework for political representation that could easily accommodate significant visible minority representation but lacks the political imperative to use it, in part because doing so would run counter to Canada's multicultural image of these groups as immigrants rather than as non‐white minorities .
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".